Cost, Financing and School Effectiveness of Education in Malawi A future of limited choices and endless opportunities Development Research Group The World Bank Africa Region Human Development Working Paper Series 32802 Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized
The views expressed herein are those of the authors and do not necessarily reflect the opinions or policies of the World Bank or any of its affiliated organizations
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to background characteristics, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6Table 7: Enrollment by type of secondary school, Pupil Teacher Ratio and
percentage of qualified teachers, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7Table 8: Possible areas of policy intervention—outcomes (objective) . . . . . . . . . . . . . . . .10Table 1.1: Social and economic indicators (latest year available) . . . . . . . . . . . . . . . . . . . . .14Table 1.2: Evolution in population, GDP, and total government revenue and expenditures . .14Table 1.3: Output and employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15Table 1.4: Evolution in the dependency ratio, 1990–2000 . . . . . . . . . . . . . . . . . . . . . . . . . .16Table 1.5: Trends in public spending on education, and comparison to total government
spending, 1993/94–2001/02, in percentages . . . . . . . . . . . . . . . . . . . . . . . . . .18Table 1.6: Comparative information on government recurrent spending on education
as a percentage of government current revenue, excluding grants, and as a percentage of GDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19
Table 2.1: Distribution of enrollment, by level of schooling, 2000 . . . . . . . . . . . . . . . . . . . .22Table 2.2: Absolute enrollment numbers and gross enrollment ratios over time . . . . . . . . . .24Table 2.3: Repetition and dropout rates, EMIS 2000 and DHS 2000 . . . . . . . . . . . . . . . . .27Table 2.4: PSLCE results and transition to different types of secondary schools . . . . . . . . . .30Table 2.5: Students with disabilities integrated in primary schools . . . . . . . . . . . . . . . . . . .31
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Table 2.6: Absolute enrollment and gross enrollment ratios in secondary18 . . . . . . . . . . . .32Table 2.7: MSCE pass rates prior years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34Table 2.8: Secondary school transition rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35Table 2.9: Primary teacher training graduates over time . . . . . . . . . . . . . . . . . . . . . . . . . . .36Table 2.10: Secondary education teacher graduates, Unima and Domasi . . . . . . . . . . . . . . . .37Table 3.1: Share of personal emoluments in recurrent expenditures . . . . . . . . . . . . . . . . . . .46Table 3.2: Per pupil annual recurrent expenditure (in 1993/94 kwacha) . . . . . . . . . . . . . . .47Table 3.3: Unit costs for a year of education, by level of education, 2000/01 . . . . . . . . . . .47Table 3.4: Decomposition of public unit costs, 2000/01 . . . . . . . . . . . . . . . . . . . . . . . . . . .48Table 3.5: Average emoluments per staff (in 1993/94 kwacha) . . . . . . . . . . . . . . . . . . . . . .49Table 3.6: Growth of teaching staff and pupil–teacher ratios . . . . . . . . . . . . . . . . . . . . . . .50Table 3.7: Annual household expenditures on primary education, 2001 . . . . . . . . . . . . . . .52Table 4.1: Index of efficiency in the different cycles of study, 1999/00 . . . . . . . . . . . . . . . . .56Table 4.2: The relationship between the number of teachers and pupils
in public or subvented primary schools, 1999/00 . . . . . . . . . . . . . . . . . . . . . .59Table 4.3: Regression results with and without using district dummy variables
(percentage correct) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66Table 5.2: Students per textbook in primary, by standard . . . . . . . . . . . . . . . . . . . . . . . . . .67Table 5.3: Time spent on school and homework in primary by grade . . . . . . . . . . . . . . . . .68Table 5.4: Number of school days missed by primary school children
during the 2001 school year . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68Table 5.5: Percent of children 0–3 years of age with stunting in the Eastern
and Southern Africa region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71Table 5.6: Correlates of school variables with retention and exam pass rates . . . . . . . . . . .74Table 6.1: Primary school enrollment ratios according to background characteristics,
200280Table 6.2: Gross enrollment rates in std. 1–4 versus std. 5–8 . . . . . . . . . . . . . . . . . . . . . . .80Table 6.3: Secondary school enrollment ratios, by gender, according to background
characteristics, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81Table 6.4: Retention standards 1–8 and 1–4 by division and by gender, 2000 . . . . . . . . . . .82Table 6.5: MSCE and JCE results, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84Table 6.6: Incidence of public education expenditure by level and quintile . . . . . . . . . . . . .84Table 7.1: Unit cost in USD by college, UNIMA and Mzuzu University, 2000/01 . . . . . . . .90Table 7.2: University enrollment and lecturer numbers by university and college, 2001 . . . .90Table 8.1: Primary projections: enrollment, repetition, and PqTR, 2001–2015 . . . . . . . . .101Table 8.2: Secondary projections: enrollment, PCR, repetition, GER and PqTR,
Feasibility (F), Political Risk (P) and Success Probability (S) (low, medium or high) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .104
List of FiguresFigure 1: Enrollment by sex and level of education, 2000 . . . . . . . . . . . . . . . . . . . . . . . . . .6
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Figure 2: MSCE pass rates by type of school, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7Figure 3: Teachers allocation in public primary schools . . . . . . . . . . . . . . . . . . . . . . . . . . .8Figure 1.1: Recurrent expenditure by functional classification, in percentages of total . . . . . .17Figure 1.2: Development expenditure by functional classification, in percentages of total . . .17Figure 2.1: Structure of Malawi’s education system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22Figure 2.2: Proportion of children who ever enrolled in primary by age . . . . . . . . . . . . . . . .24Figure 2.3: Enrollment rate by age, different sources, 2000 . . . . . . . . . . . . . . . . . . . . . . . . .25Figure 2.4: Gross enrollment rates by level of schooling, 2000 . . . . . . . . . . . . . . . . . . . . . . .26Figure 2.5: Enrollment trends by standard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26Figure 2.6: Estimated survival rate primary and secondary, 2000 (cross-sectional method) . .28Figure 2.7: Primary school completion rate over time, two population estimates . . . . . . . . . .29Figure 2.8: Enrollment in secondary education by type of school . . . . . . . . . . . . . . . . . . . . .33Figure 2.9: MSCE pass rates by type of school, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34Figure 3.1: Real recurrent and development expenditures, 1993-2003 (millions of kwacha) .43Figure 3.2: Real recurrent expenditures: MOEST and subvented organizations . . . . . . . . . . .43Figure 3.3: MOEST recurrent expenditures in real terms . . . . . . . . . . . . . . . . . . . . . . . . . . .44Figure 3.4: Real recurrent expenditures of subvented organizations . . . . . . . . . . . . . . . . . . .44Figure 3.5: Real development expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45Figure 4.1: Teachers allocation in publicly funded primary schools . . . . . . . . . . . . . . . . . . . .57Figure 4.2: Comparison of degree of randomness in teachers allocation to individual
primary schools for selected Sub-Saharan African countries . . . . . . . . . . . . . .58Figure 4.3: Teacher allocation in all CSS, CDSS, and grant-aided secondary schools . . . . . .62Figure 4.4: Percentage of qualified teachers in different types of secondary schools . . . . . . . .62Figure 5.1: SACMEQ test score, Southern and Eastern Africa . . . . . . . . . . . . . . . . . . . . . . .66Figure 6.1: Enrollment by gender and level of education, 2000 . . . . . . . . . . . . . . . . . . . . . .79Figure 6.2: Survival in primary, urban9 vs. rural (cross-sectional method) . . . . . . . . . . . . . .82Figure 6.3: Proxy std. 4 and std. 8 completion rates by gender . . . . . . . . . . . . . . . . . . . . . . .83Figure 7.1: Enrollment in tertiary per 100,000 inhabitants, Sub-Saharan Africa . . . . . . . . . .88Figure 7.2: University enrollment by subject area, 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . .88Figure 7.3: Student to lecturer ratios at tertiary level in Sub-Saharan Africa, 2000/01 . . . . . .92
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his study is part of a series of educa-tion country status reports (CSRs)being prepared by World Bank staffin collaboration with national teams
from various Sub-Saharan countries. Theimmediate objective is to enhance the knowl-edge base for policy development. Morebroadly, CSRs create a basis for engaging adiverse audience in dialogue on education sec-tor policies and for developing a shared visionfor the future. These processes have becomeincreasingly important as governments renewtheir commitment to reduce poverty, and theinternational donor community pledges to pro-vide the needed financial assistance.
In this new dynamic of international devel-opment assistance, the World Bank has orient-ed its corporate mission toward supportinggovernments in the fight against poverty, mak-ing the task its defining priority. In practice thestrategy is articulated through a two-prongapproach: support for policies that accelerateeconomic growth combined with explicitmeasures to promote a more equitable distri-bution of the benefits from growth. Humandevelopment, especially through investments ineducation, plays a central role in both process-es. This fact receives recognition in the empha-sis placed on education in the debt relief
arrangements under the Heavily Indebted PoorCountries (HIPC) Initiative. Governments havealso invariably treated education as a prioritysector in their Poverty Reduction StrategyPapers (PRSPs). The case for placing addition-al emphasis on the education sector is particu-larly strong in Malawi, where prospects foreconomic growth depend on the ability todiversify the economy in a country with a lim-ited natural resource base and declining termsof trade affecting traditional sectors. There isnow a need to focus on learning outcomes andquality, which have not kept pace with the con-siderable improvement of access to educationachieved following the 1994 Free Primary Edu-cation Policy that increased enrollment from 2million to 3 million pupils overnight.
In Malawi, as in other low-income coun-tries, two specific goals in education stand out:ensuring that all children complete basicschooling of adequate quality; and managingthe production of graduates at post-basic lev-els, in terms of quantity and skill level and mix,to match the demand for skilled labor. To ful-fill these objectives, an infusion of resources,from both domestic and international sources,may well be needed. However, an equallyimportant requirement is to ensure that cur-rently available resources are used efficiently
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Foreword
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and equitably. The evidence suggests that inmany Sub-Saharan countries, substantial scopefor progress exists in this regard. Some coun-tries have indeed already embarked on reformsfor improving the performance of their educa-tion systems. In the 1990s, for example, poli-cies to encourage more effective use of teachersthrough multi-grade teaching and double shift-ing were put in place to boost coverage. Moreremains to be done, particularly to tackle thestructural constraints that encumber the edu-cation system. The challenges include definingan appropriate division of responsibilitybetween the public and private sectors forfinancing and delivering education services,setting sustainable levels of teacher remunera-tion, and creating institutional arrangementsfor effective systems management. Reform inthese areas are key to improving the quality oflearning outcomes, which in turn will be cru-cial for progress toward the Education for Alltargets.
In order to identify appropriate measuresand address the structural issues, a first step isto develop a country-specific knowledge basethat sheds light on the key weaknesses in theeducation system. In a large number of theSub-Saharan countries, however, that knowl-edge base remains sparse, reflecting the sys-tematic neglect of analytical work in the past.In order to re-capitalize it, the World Bank hasinitiated the preparation of CSRs, using a stan-dard format to consolidate the available infor-mation in a policy-relevant manner.
Two features characterize the CSRs, oneconcerning their technical content, the otherthe process by which they are accomplished.With regard to content, five aspects are worthmentioning. First, the CSRs pay close attentionto issued of equity and the distribution of pub-lic resources for education, given the impor-tance of these topics in the HIPC and PRSPcontext. Second, the analysis relies on com-monly available administrative data as well ashousehold surveys, an approach that hashelped to improve the consistency and robust-
ness of the statistical results. Third, the CSRsput a sharper focus on outcomes by emphasiz-ing indicators beyond the usual gross and netenrollment ratios. In particular, it documentsthe schooling careers of children as reflected inthe shares of the population that enter grade 1and attain the various grades in the education-al ladder. The more detailed approach hashelped to sharpen the socio-economic, genderand geographical disparities in education, aswell as to clarify the sources of the disparities.A fourth example of the technical content ofCSRs is the use of school-level data to assessthe scope for improving service delivery to thepoor. Finally, the CSRs also make use of dataon student learning—where they are avail-able—to gauge the education system’s per-formance in this important domain, and toidentify cost-effective measures for progress.
Regarding the process for preparing theCSRs, the main feature is that they are prod-ucts of a partnership between the World Bankand national teams from the various countries.The form of this partnership varies acrosscountries depending on the specific circum-stances. In the case of Malawi, the CSR wasdeveloped in close collaboration with the Min-istry of Education and Human Resources (for-merly the Ministry of Education, Science andTechnology) and other Government agencies.It is important to note that CSRs are diagnos-tic documents whose purpose is to help identi-fy the policy questions rather than to offersolutions and make recommendations. Theprocess of policy development is more appro-priately led by the national team, and the avail-ability of a CSR provides a good basis for dis-seminating the findings and stimulating abroad national dialogue that informs the coun-try’s medium-term budget planning exercise. Inthe case of Malawi, the CSR has been exten-sively used to target interventions under theEducation Sector Support Project 1 (ESSUP1)and to further a broad based dialogue with alldonors and stakeholders. Further, the CSR canplay a useful guiding role in the Government’s
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preparation of an education sector plan forMalawi, which will set the directions forreforms and investments in the sector in com-ing years. For the World Bank’s part, the docu-ment is helping to facilitate ongoing discus-sions to improve the management of thesystem, its internal efficiency, and most impor-tantly, to improve quality.
The publication of the CSR for Malawi isintended to institutionalize our collectiveknowledge about the country’s education sec-tor and the nature of the policy challenges, andto share that knowledge as widely as possible.
It is my hope that as new knowledge emergesin the course of implementing the country’sdevelopment strategy, the CSR will be updatedto track progress in overcoming those con-straints in the education sector that currentlyimpede poverty reduction in Malawi andwhich may in the long run slow economicgrowth.
Birger FredriksenSenior Education AdvisorAfrica RegionThe World Bank
Acknowledgements
his report has been preparedthrough a process of close collabora-tion between the World Bank andthe Government of the Republic of
Malawi to collect and analyze informationabout the status of the education system inMalawi. A large number of people have con-tributed to the study, which was conductedunder the general supervision of Søren Nelle-mann. The Bank team included also Bart VanUythem, Sajitha Bashir, Cathal Higgins,Michael Mambo, Rae Galloway, Kirsten Maj-gaard and Yves Tencalla. Technical guidancewas provided by Alain Mingat, RamahatraRakotomalala, and Jee-Peng Tan. Commentsand support were provided by Suhdir Chitale,Antonio Nucifora, Dandan Chen, and BirgerFredriksen. Peer reviewers were Vincent Gre-aney, Harry Patrinos, and Lianqin Wang. TrishTierney has provided editorial assistance andElsie Lauretta Maka has overseen the produc-tion of the report.
The Malawian technical working groupconsisted of senior policy makers and technicalstaff from the Ministry of Education and
Human Resources (formerly the Ministry ofEducation, Science and Technology), led byHonorable Minister Y. Mwawa and includedamong others Z.D. Chikhosi, Principal Secre-tary, K. Mwale, Director of Planning, Augus-tine Kamlongera, Grace Banda, Ken Ndala,and Sutapa Choudhury. The report furtherbenefited from important contributions byMarelize Görgens from the EDMU, EsmeKatzamira from CERT, Simeon Hand and stafffrom MIE, and Wilfred Görtler from GTZ,and from representatives of other parts of gov-ernment, including Ministry of Finance andEconomic Planning, Ministry of Labor andVocational Training, TEVET, National Statis-tics Office, the University of Malawi andMzuzu University.
Helpful comments and information werereceived from a number of donors in Malawi,including Dfid, UNICEF, JICA, UNDP, CIDA,USAID and WFP. The report was financed bythe World Bank, with contributions from thegovernments of Malawi and Norway throughthe Norwegian Education Trust Fund.
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List of Abbreviations
CDSS Community Day Secondary SchoolCE Central East DivisionCIDA Canadian International Development AgencyCSS Conventional Secondary SchoolCW Central West DivisionDANIDA Danish International Development AssistanceDEC Distance Education CentreDFID Department for International DevelopmentDSTD Department for School and Teacher Development (at MIE)DTED Department of Teacher Education and Development EFA (– FTI) Education For All (- Fast Track Initiative)EMAS Education Methods Advisory ServiceEMIS Education Management Information SystemFPE Free Primary EducationGDP Gross Domestic ProductGER Gross Enrollment RatioGNP Gross National ProductGoM Government of Malawi HRMD Human Resource Management and Development IHS Integrated Household SurveyJCE Junior Certificate of EducationJICA Japan International Cooperation AgencyKFW Kreditanstalt fur Wiederaufbau (Germany)MANEB Malawi National Examination BoardMASAF Malawi Social Action FundMCDE Malawi College of Distance EducationMIE Malawi Institute of EducationMIITEP Malawi Integrated In-service Teacher Education ProgramMK Malawi Kwacha
MLA Monitoring Learning AchievementMOEST Ministry of Education, Science and Technology
(now Ministry of Education and Human Resources)MOF Ministry of Finance MSCE Malawi School Certificate of EducationMTEF Medium Term Expenditure FrameworkMU Mzuzu UniversityNER Net Enrollment RatioNLS National Library ServiceORT Other Recurrent TransactionsPE Personal EmolumentsPEP Primary Education ProjectPER Public Expenditure ReviewPIF Policy and Investment Framework (strategic document for the education sector
in Malawi, developed by the Ministry of Education, outlining the goals by2012)
Poly Board Polytechnic Board of GovernorsPSLCE Primary School Leaving CertificatePRISAM Private Schools Association of MalawiPTA Parent Teacher AssociationPTR Pupil Teacher RatioPqTR Pupil Qualified Teacher RatioSACMEQ Southern African Consortium for Monitoring Educational QualitySE South East DivisionSEP Secondary Education ProjectSH Shire Highlands DivisionSSTEP Secondary School Teacher Education ProjectSW South West DivisionTDC Teacher Development CentreTSC Teacher Service CommissionTTC Teacher Training CollegeT&L Teaching and Learning (materials)UOM / Unima University of MalawiUSAID United States Agency for International Development
GOVERNMENT FISCAL YEAR
July 1—June 30
CURRENCY EQUIVALENTS
(Exchange Rate effective October 29, 2003)Currency Unit: Malawi Kwacha (MK)
US$ 1.00 = 105.5 MK
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Africa RegionAfrica Region Human DevelopmentWorking Paper Series
ducation in Malawi is experiencing aserious and debilitating crisis of lowquality, low efficiency, limited capaci-ty and a shortage and inequitable dis-
tribution of human and financial resources.The education environment is further under-mined by a very high pupil qualified teacherratio (PqTR) in primary as a result of a short-age of trained teachers and the limited capaci-ty of the teacher training system—approxi-mately 40 percent of primary and 70 percent ofsecondary teachers are untrained; inadequatelearning materials and school infrastructure;overcrowded classrooms; and a teacherdeployment system whereby teacher numbersvary significantly across schools and grade lev-els and between urban and rural areas. Tocompound the problem, the HIV/AIDS pan-demic is killing teachers and parents, raisingabsenteeism rates of both teachers and pupilsbecause of illnesses and the need for more helpin the household. With more than half thepopulation chronically malnourished, especial-ly during the hunger period from January toApril, absentee rates are further raised andlearning outcomes reduced. The poor learningconditions, the HIV/AIDS pandemic and
chronic malnourishment has resulted in veryhigh repetition and dropout rates. Despite thefact that more than 95 percent of all Malawianchildren eventually begin school, only about60 percent complete standard 6 and some 4out of 10 pupils (40 percent) complete stan-dard 8.
As a successful outcome of the 1994 imple-mentation of Free Primary Education (FPE)—which increased enrollment from 2 million to 3million — most Malawian children, includingthe poorest, now enroll in school. While thegovernment has maintained spending perpupil, regrettably the quality of education hasbeen increasingly eroded. Learning outcomesare negligible: the Southern Africa Consortiumfor the Measurement of Educational Quality(SACMEQ) study revealed that less than 1 per-cent of pupils in standard 6 reach a desirablelevel in reading (20 percent reach a minimumlevel). Given the limited learning outcomes andthe low grade attainment, the wastage ofresources is evident and the room for efficien-cy improvements enormous.
Against this picture a stark reality confrontsMalawi: it is a small country with only 10 mil-lion people and with a natural resource basethat is limited to agriculture but highly depend-ent on the export of tobacco. The reality is that
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2 Cost, Financing and School Effectiveness of Education in Malawi
in the next decades the Malawian economy islikely to remain characterized by a dualisticstructure of employment, with a dominant tra-ditional sector and a relatively small modernsector. The basic objective is to provide thetype of human capital that best fits thedemands of the two sub-sectors, while simulta-neously helping the economy to move from itstraditional to its modern sector and alleviatingpoverty, in the long run.
Macroeconomic Context andEducation Expenditures
The development of education is determinedlargely by macroeconomic and demographicconditions. Throughout the 1990s, Malawi’seconomy grew by approximately 3 percent—orslightly less than 1 percent above populationgrowth. GDP per capita was approximatelyUS$175 in year 2001 and Malawi remains oneof the poorest countries in the world. Total pub-lic expenditures as a share of GDP rose fromabout 25 to 33 percent over the same period.Total education expenditure in real terms hasremained largely the same since 1994/95. AsTable 1 shows, by the end of the nineties, recur-rent education expenditure as a proportion ofGDP in Malawi was somewhat below countrieslike Uganda (3.2%) and Kenya (6.3%)—coun-tries that are also expanding enrollment as aresult of a free primary education policy. How-ever, in the past couple of years, recurrentspending on educations has recovered inMalawi, reaching 3.6% of GDP in 2001/02, thelast year for which official data are available.
One notable feature in Malawi is the factthat the share of recurrent expenditures allo-cated to higher education (15–20 percent) ishigher than the share allocated to secondaryeducation (10–15 percent). This is significantbecause approximately 275,000 pupils areenrolled in secondary education while onlyabout 4,000 students are enrolled in highereducation institutions.
Per Pupil Spending. The per-student costs ofsecondary and higher education are moreexpensive than primary education in most coun-tries. In Malawi, however, the discrepancies inspending per pupil are so substantial that theyraise concerns about the equitable distributionof resources. As can be seen in Table 2, below,the unit cost at the university level is betweenUS$2,500–3,000, while it is around US$10 inprimary compared to around US$35 in otherSSA countries, and roughly US$40 in secondaryas a whole. The latter is affected by the very lowunit costs (approximately US$20) and underfunded Community Day Secondary Schools(CDSS) where the bulk of secondary studentsare enrolled. In comparison, the spending perstudent in the traditional Conventional Sec-ondary Schools (CSS) is approximately US$100.As Table 2 shows, compared to other countriesin the region the unit cost for secondary and ter-tiary education appear very unbalanced.
Household Financing. Despite the abolish-ment of primary school tuition fees in 1994,households still bear a considerable share ofeducation financing. Nearly all households inMalawi paid for one or more types of schoolsupplies during the year 2001. The majority offamilies reported paying for textbooks and
Table 1: Comparative information on government recurrent education spending as a percentage of governmentcurrent revenue, excluding grants, and as a percentage of GDP
Malawi Mozamb Kenya Rwanda Uganda Zambia Zimbabwe African1998/99 2000/01 (1998) (1999) (2000) (2000) (1998) (1997) Countries
Educ. Recurr. exp. as % of gov. curr. Rev. 17.3 15.0 18.1 26.2 32.6 30.1 12.3 28.3 17.8Educ. recurr. exp. as % of GDP 2.5 2.8 2.0 6.3 3.2 3.2 2.3 7.1 3.04
Source: Bruns, B. et al. 2002. For Malasi, authors’ calculations are used.
Executive Summary 3
uniforms and approximately half reported con-tributing to the school development fund. Inprimary, mean household expenditures on edu-cation average approximately 80 percent ofper pupil public expenditures. These householdexpenditures are regressive and the pooresthouseholds contribute more of their income toeducation than the wealthiest Malawians. Fur-thermore, household spending on educationincreases by grade level. A student in grade 3incurs 50 percent more costs than a student instandard 1 and one in standard 6 spends 4.7times the expenditure of a standard 1 student.Given the high levels of poverty in the country,and the susceptibility of agricultural and ruralincomes to climatic shocks, this relatively highdependence on household financing introducesgreater instability—especially in the financingof critical learning materials, repairs and con-struction costs. The high levels of householdexpenditures are not only regressive but arepossibly important determinants in forcing stu-dents to drop out in the early stages of primaryeducation.
Enrollment Rates and Impact ofHIV/AIDS
The formal education system in Malawi fol-lows an 8–4–4 structure, i.e. 8 years of primary(Standard 1–8), 4 years of secondary (Form1–4) and 4 years, or more, of university leveleducation. The primary and secondary levelsare administered by the Ministry of Education,Science and Technology (MoEST)1 through its
head quarters, the six education divisionoffices and the 33 district education offices. Asa result of the FPE policy, the total number ofstudents enrolled in primary education grewalmost overnight from less than 2.0 million in1993/94 to almost 3.0 million in 1994/95 andto about 3.2 million in 2001. About 70 percentor 2.3 million are enrolled in lower primary(standards 1 to 4). There were an estimated275,000 students in secondary in 2000, 12,000students at primary teacher training colleges,4,000 students at universities, and about 1,500students were attending technical and voca-tional training institutes.
Concurrently, the national gross enrollmentrate (GER) increased from 88 percent in1991/92 to 120 percent in 1994/95 and hasremained at about that level since. Enrollmentin secondary multiplied by almost four between1991/92 and 2000, with the GER now at about27 percent. Malawi has 6 primary TeacherTraining Colleges (TTC) and approximately50,000 primary teachers, although some maybe ghost teachers. However, because of theexpansion there continues to be an acute short-age of qualified primary and secondary teach-ers. In secondary, even though the student toteacher ratio (PTR) is at about the desired 40:1,the PqTR is 120:1. The total stock of secondaryteachers is about 7,500, of which less than athird are qualified secondary teachers.
Impact of HIV/AIDS. In 2001 the officialnumber of primary teachers that died was 900.In addition about 700 left the primary educa-tion system owing to normal attrition. BecauseHIV/AIDS will continue to affect the mortality
Table 2: Comparison of unit recurrent public spending per pupil
Ratio to Primary As proportion of GDP/capita
Mozam- Anglophone Mozam- Anglophone Malawi bique Kenya Zambia Africa* Malawi bique Kenya Zambia Africa*
* Group of 7 countries.Source: World Bank Sector Studies.
4 Cost, Financing and School Effectiveness of Education in Malawi
rate of teachers and the system will continue toexpand, the replacement of both primary andsecondary teachers as a result of deaths causedby AIDS will likely increase to approximately3,700 teachers a year. HIV/AIDS will alsoincreasingly affect attendance and retention ofboth teachers and students. The adverse effectson the annual training and replacement ofteachers, as well as on efforts to improve reten-tion and access of growing numbers of children— who will be orphaned or required to takecare of their parents — has significant implica-tions for achieving universal primary educationin Malawi.
Quality of Education
The combination of relatively low publicspending on education per pupil, inadequatenumbers of qualified teachers, poor learningconditions and externalities affecting bothteachers, parents and children has resulted in adeterioration in learning outcomes. Table 3shows the performance of Malawi’s fourthgraders in a test of numeracy, literacy and LifeSkills administered in a number of Africancountries. Malawi’s performance is slightlybelow the average of all the sampled countries.However, for literacy its score is the lowest ofall countries and for numeracy it ranks close to
the weakest. Performance in Life Skills test isbest of all countries and this balances the weakresults in the other two areas.
The low literacy results are confirmed by theSACMEQ study testing the reading skills inEnglish of standard 6 pupils. The acquisitionof minimum and desirable mastery levels wasextremely poor, with less than one percent ofall measured pupils reaching the desirable mas-tery level while about 22 percent reached theminimum mastery level. The study also foundthat Malawi had the lowest percentage ofpupils who met the minimum and desirablemastery levels of reading literacy when com-pared to six other countries in the region. Theimplication for Malawi is the need to addresssome of the underlying structural problems toimprove learning outcomes. Some of thesestructural problems relate to the curriculumbeing taught, teachers qualification and yearsof experience, school practice and the subjectcontent knowledge and pedagogic contentknowledge being taught under the current in-service teacher training program. Factorsexogenous to the school are also important,such as mother tongue, availability of books athome, homework, and nutrition. More thanhalf the population is chronically malnour-ished. School inputs, such as teaching andlearning materials, classroom materials, andschool furniture are inadequate or dilapidated
adversely affecting the conditions for learning.In many schools the lower standards are taughtunder the open sky, which often leads to thecancellation of classes during the rainy season.Over one third of standard 6 pupils do nothave an English textbook. Overall, MoESTrecords the pupil to textbook ratio for threemajor subjects as shown in Table 4.
Finally, as shown in Table 5, the discrepan-cy in the PTR between lower grades and high-er grades further complicates the conditionsfor effective teaching and learning especially inthe lower grades. As can be seen the averagePTR in standard one is 100, but many schoolsand classes exceed this number. There are clearimplications for effective teaching. In addition,the high PTR increases the number of repeatersas pupils are not being helped, and this in turnleads to a continuing high number of studentsenrolled in the lower grades. The high PTRbecomes both a cause and effect of poor learn-ing outcomes and low retention.
Repetition, Dropout, Survival andCompletion
The poor learning environment leads to lowlevels of retention, which in turn adverselyaffect achievement. While Malawi, despite itsweak school infrastructure and lack of suffi-cient classrooms, has almost succeeded in pro-viding access for all children with the abolitionof fees, universal primary education for all
remains elusive as a result of the low survivalthroughout primary. Although more than 95percent of all children enter primary at somepoint most repeat several grades. The level ofrepetition is high throughout primary, and issignificantly higher in lower primary than inupper primary, with the exception of standard8. The average is about 25 percent, while 40percent of all children repeat standard 1. TheMonitoring Learning Achievement (MLA,1999) study for 11 African countries recordedthe highest repetition rates of all countries inMalawi in the first four grades of primary.
The high number of repeaters and over-agepupils has increased the GER. The GER forstandard 1–4 is 167 percent (1999/2000), butis only 70 percent for standard 5–8. The lowGER in upper primary reflects the fact that alarge proportion of the children eventuallydrop out. While repetition levels are high in theearly school years, dropout rates are modest inthe lower grades, but by the end of standard 6,about 40% of the pupils have dropped out,and at the end of standard 8, about 60%.
The survival rate, or probability that a grade1 student will still be in school by standard 8,has actually diminished since the beginning ofthe nineties prior to the introduction of FPE.However, due to a higher intake of students toprimary school than before, more children inabsolute numbers and as a percentage of school-age children, do complete primary. Thus,Malawi is on the right track by having hugelyimproved primary coverage and to a lesser
Table 4: Students per textbook in primary, by standard
Table 5: Pupil teacher ratios, standard 1 – 8, 2000
Std 1 Std 2 Std 3 Std 4 Std 5 Std 6 Std 7 Std 8
100 76 64 52 45 39 33 28
6 Cost, Financing and School Effectiveness of Education in Malawi
extent completion, but needs now to focus onreducing dropout and repetition in primary.
In secondary education approximately 60percent of students enrolled in Form 1 proceedto Form 4 (grade 12). Repetition, and earlyand late entry, further impact on pedagogicalprocesses because of the broad range of skillsand maturity in each class. By addressing thewide age-range of pupils, the system couldimprove efficiency, lower repetition anddropout rates and thus increase survival andcompletion rates. However, these are not theonly determinants affecting attainment inMalawi. Other issues like gender, geographiclocation and type of school determines the lev-els of achievement and attainment.
Equity
Enrollment and access to education in thelower grades in Malawi is fairly gender-equi-table. However, as Figure 1 shows the gender
gap widens as students progress. In primarythe percentage of girls was 48 percent in year2000, 40 percent for secondary, 35 percent forprimary teacher training and 26 percent forhigher education. While the survival rates forboth boys and girls are about the same, there isa significant discrepancy of about 20 to 30 per-centage points between the survival of anurban versus a rural pupil.While there aremany reasons for this gap—including a betterpupil to teacher ratio in urban areas—it is alsorelated to a higher degree of poverty in therural areas. In general, as shown in Table 6,poverty is a strong predictor of enrollment andsurvival—with the poorest segment of the pop-ulation having close to a 20-percentage pointlower net enrollment rate than the wealthiest.At the secondary level, urban youth, aged14–17, are three times more likely than theirpeers in rural areas to attend secondary school(NER 21 versus 7 percent). Regional differ-ences in the secondary NER are also consider-able, and follow a pattern similar to that at the
Table 6: Primary school gross and net enrollment ratios, by sex, according to background characteristics, 2002
Residence Region Wealth index quintile
Urban Rural North Central South Lowest 2nd 3rd 4th Highest Total
Results are for the de jure household population age 5–24.
0.00%
10.00%
20.00%
30.00%40.00%
50.00%
60.00%
70.00%
80.00%
Primary Standard1-4
Standards5-8
Secondary PrimaryTeacherTraining
Highereducation
Boys Girls
Figure 1: Enrollment by gender and level of education, 2000
Source: Authors’ calculations, using data from NANEB database.
Executive Summary 7
primary level. Differences in access by socio-economic background at the secondary levelare large, with a GER of 62 percent among thewealthiest youth and 11 percent among thepoorest youth.
In secondary education a particular inequityarises from the type of school in which a pupilenrolls. Figure 2 shows the results of the MalawiSchool Certificate of Education (MSCE) finalexam at the end of secondary in 2002 by type ofenrollment. While the figure may indicate thatwith the exception of the Community Day Sec-ondary Schools (CDSS) outcomes were fairlyeven, the fact is that close to 75 percent of stu-dents are enrolled in CDSSs. The low pass ratein the CDSSs is not surprising since, in general,the CDSSs are under-funded and staffed byunqualified teachers (and the expenditures perstudent are about one-fifth of the expendituresin CSS). The inequitable access to good second-ary education and the acute shortage of trainedsecondary teachers become evident when theenrollment by type of school, PTR and percent-age of qualified teachers are considered asshown in Table 7 below. While there is no majordifference in the PTR ratio across the types of
schools, it is clear that the majority of studentsin CDSS do not have access to sufficient numberof qualified teachers.
Internal Efficiency
Given the high repetition and dropout rates inprimary, 60 percent of the public resources atthis level are used either on children who dropout before finishing primary or on childrenrepeating a year. Put another way, Governmentfinances 20 school years to generate a singlegraduate from primary school. Thus the cost togovernment is an additional 12 years of perpupil spending relative to a scenario with nodropout or repetition (8 years). This inefficientuse of scarce resources should be a matter ofserious concern. For secondary, the situation issignificantly better: a little less than one quar-ter of the public resources are used on repeti-tion years or on children who drop out: itrequires 5.2 schooling years instead of 4 yearsto produce a graduate.
Teacher deployment and teacher manage-ment. The quality of an education system is
0.00%10.00%20.00%30.00%40.00%50.00%60.00%70.00%
Community Day
Private
Night School
Gov Boarding
Gov Day
Grant Aide d
Total
Figure 2: MSCE pass rates by type of school, 2002
Table 7: Enrollment by type of secondary school, Pupil Teacher Ratio and percentage of qualified teachers, 2000
Type of schools Number of students Pupil–teacher ratio Percentage Qualified Teachers
Source: Authors’ calculations, using data from NANEB database.
8 Cost, Financing and School Effectiveness of Education in Malawi
generally associated with the provision of qual-ified teachers to that system. Therefore, effi-ciency concerns are related to the way this crit-ical resource is distributed and managed. Sinceteachers’ salaries are the largest educationexpenditure item, their deployment also has animpact on unit cost and on the ensuing equi-table distribution of resources.
A crucial aspect of teacher deployment hasto do with clear criteria to provide schools ofsimilar enrollments with comparable numbersof teachers. This feature can be represented bya straight line graph (policy), as shown in Fig-ure 3, and in the case of Malawi, a primaryschool of 500 pupils would always have 8teachers and a school with 1,000 pupils wouldalways have 16 teachers. Figure 3 indicatesthat in Malawi there is a wide variability in thenumber of teachers available to schools thatenroll a similar number of pupils. The dataindicate that schools with 1,000 pupils canhave anywhere between 5 to 40 teachers. Sim-ilarly, in schools with 40 teachers enrollmentsvary between 500 and 3,800. These data cor-responds to 34 percent ‘randomness’. Theinconsistency in teacher deployment can partlybe explained by differences in allocationsamong the districts, especially between urbanand rural districts and inadequate monitoringand management tools to ensure adequate andfair deployment.
This situation is further aggravated by sig-nificant differences in pupil to qualified teacher
ratios between urban and rural districts. Inurban districts, the PqTR is between 60 and70, in rural districts it is on average twice ashigh. Inconsistency in teacher deployment isalso evident within individual districts. In sec-ondary, teacher deployment shows an evenlower consistency than primary; the degree ofrandomness is 59 percent. When reviewingpupil to teacher ratios and pupil-to-qualifiedteacher ratios, strong differences are alsoapparent. In urban areas, PTRs and PqTRs arerespectively 28:1 and 59:1 whereas the sameindicators for rural areas are 36:1 and 131:1.By type of school, two thirds of CDSS teacherswere unqualified to teach secondary but thiswas only true for less than 10 percent in CSSs.
Among the countries in Sub-Saharan AfricaMalawi is one of countries with the least con-sistent deployment of primary teachers. Amore equitable deployment of teachers will becritical to improving attainment and achieve-ment and more efficient use of scare resources.It is clear that the Government’s ability toaddress some of the internal constraints andefficiency issues will determine how wellimprovement to the attainment and achieve-ment can be made. However, there are otherand serious issues affecting the demand foreducation and the delivery of educationservices.
Externalities
In Malawi externalities plays a significant rolein the demand and supply of education servic-es. Absenteeism is a particular contributingfactor to low learning. Ninety-seven percent ofprimary pupils were absent one or more daysduring the 2001 school year. On average,pupils who were absent from school missed atotal of 17 days during the year. The main rea-sons for absenteeism during the previousschool year were: illness—86 percent; funer-als—61 percent; did not want to go—39 per-cent; school clothes dirty—34 percent; too
0
10
20
30
40
50
0 500 1000 1500 2000 2500
Number of pupils
Num
ber o
f tea
cher
sFigure 3: Teachers allocation in public primaryschools
Source: Authors’ calculations, using EMIS 2000.
Executive Summary 9
hungry—28 percent; any type of work—12.5percent; no money for fees—10 percent.Teacher absenteeism in Malawi is reported aschronic but the frequency varies widely. Insome schools, a teacher’s time-on-task was aslow as 1–2 hours each day. The main reasonssuggested for this level of absenteeism wereattendance at funerals of colleagues, errands,collecting salaries or just “out for a moment”.Geographic location of schools also presents achallenge. While 64 percent of children inurban areas live within 15 minutes of the near-est school, this is only true for 33 percent ofrural children. In more than one-third of ruralareas children are required to walk for at leasthalf an hour to school.
Prevalence and consequences of malnutri-tion affect the opportunity costs of education.Malawi has one of the highest levels of stunt-ing in children in Eastern and Southern Africa;almost half the children under 3 years of ageare stunted. From the Demographic andHealth Survey (DHS) 2000, it is apparent thatmany children enter standard 1 either short orunderweight for their age—57 percent of chil-dren 4–5 years of age are stunted and analarming 28 percent of children are severelystunted. Stunting and micronutrient malnutri-tion are associated with reduced capacity tolearn, delayed school enrollment, decreasedschool attendance, and dropout—especiallyduring the hungry period from November toApril. Families keep children out of school dur-ing this period so children can earn money tobuy food or look for food. In addition, hungerand fatigue are so severe that many children donot have sufficient energy to walk to school.
University Education
The expansion in primary education and theshortage of trained teachers is further con-strained by the limi0ted number of studentsenrolled in higher education. Malawi has closeto the lowest proportion of tertiary enrolled
students per 100,000 inhabitants in the entireSub-Saharan region. Public universities inMalawi enroll fewer than 4,000 students. Thefirst private university plans an initial intake of50 students but it is yet to open. Further, thereare significant inefficiencies at the universi-ties—some of these derive from the small scaleof operation. Both the student to lecturer ratio(7:1), as well as the student to support staffratio (about 9:1) are the lowest in SSA with theexception of Equatorial Guinea. Other clearinefficiencies stem from the large proportion ofbudget allocated to non-core functions, such asboarding and feeding. In fact, the current Edu-cation Act still limits total enrollment to avail-able bed space at the colleges although somecolleges are beginning to ignore this require-ment. A very minor portion of total enrollmentincludes non-residential students in parallelprograms that charge higher fees. Apart fromgender inequity, a more significant but not sur-prising inequity is the socio-economic back-ground of students. Students from the wealthi-est quintile consume more than half of thepublic expenditure at tertiary level; studentsfrom the poorest quintile have practically noaccess whatsoever.
Policy Issues and Choices
The development of the education system inMalawi will require major investments at alllevels and in all the critical areas. The imple-mentation of FPE without sufficient publicfunding has undermined the quality of the sys-tem beyond what could have been expected asa result of the focus on access. Malawi’s recur-rent expenditure on education has been rela-tively low compared to other countries thathave undertaken FPE policies, such as Kenyaand Uganda, but has been increasing the lastfew years. Given the limited prospects for eco-nomic growth, improvement of efficiency willbe the key for the overall sector development.A few policy issues derived from the study are
10 Cost, Financing and School Effectiveness of Education in Malawi
summarized in the Table 8 below. A more com-prehensive list of policy issues, their timing,cost, feasibility, political risk and probabilityfor successful implementation are listed inChapter 8.
Finally, in Chapter 8, this report analyzesthe fiscal implications of the required upgrad-ing of primary and secondary teachers neededto improve the pupil to qualified teacher ratio,on of the principal targets set in the govern-ment’s Policy and Investment Framework forEducation (PIF). This analysis is based on asimulation model developed in cooperationwith government; the model includes assump-tions on the gradual improvement in repetitionand dropout as a result of having more andbetter teachers. As can be seen in Chapter 8, ascenario for teacher training that will lead tothe accomplishment of the EFA and PIF goals afew years after the targets set in the PIF (thus,
a more realistic scenario), will require increas-ing spending on education from a share ofabout 21% of the discretionary budget to27%; and furthermore, require increasing theshare towards primary education from approx-imately 50 percent to 70 percent of total edu-cation spending. This result strongly implies aneed to focus now on improving efficiency inthe use of resources, and recalibrate currentpolicy targets to available resources. Thescarcity of resources must be taken intoaccount in the development of a comprehen-sive and sustainable teacher development strat-egy: the backbone for improving the educationsystem in Malawi.
Note1. From 2004, the Ministry of Education
and Human Resources.
Table 8: Possible areas of policy intervention—outcomes (objective)
Outcome (Objective) Policy Options/Interventions
Re-balanced education • Recalibrate PIF (EFA) goals to financial and human resources, especially system established teacher development
• Take a strategic long term view and establish % caps on public funding for secondaryand tertiary education
Accountability improved:Re-establish accounta- • Establish accountability at school level though social contracting between bility, and establish communities and schools and transparency systemsincentives for teachers • Ensure teachers accept strategies/public consensus buildingand headmasters to • Restructure teacher salary provisions/ Provide career development and rotation, perform their duties especially for rural assignments/ Empower headmasters (role in promotions and in
reprimanding teachers)• Improve supervision and inspection
Equitable expansion of • Lower repetition and dropout rates to shorten average of school completion enrollment improved (automatic promotion/cycles of learning standard 1–4)
• Target districts, areas or groups with inequitable access or survival, using incentives.e.g. Expand food for education of girls during the hungry season (November to April)
• Use teachers efficiently, re-deploy teachers; evaluate and adjust accordingly theteacher resource requirements under a streamlined curriculum at secondary level
• Improve incentives for private provision of education, particularly at secondary level
(continued on next page)
Executive Summary 11
Table 8 (continued)
Outcome (Objective) Policy Options/Interventions
Quality and internal • Redefine a coherent and sustainable teacher development model and strategy/efficiency improvement Strengthen in-service teacher training and other teacher professional support
• Lowering of PTR in standards 1–4 and redeployment of teachers as an integral part ofthe decentralization plans
• Curriculum Reform: Continue the Primary Curriculum and Assessment (PCAR) processand complete the proposed review of secondary curriculum;
• Improvements in the classroom conditions, other school facilities and learning materi-als through a direct support to school program (DSS) financed under the developmentbudget/Improve community involvement and through the DSS program lower indirectcost of education/opportunity costs
• Distribute iron supplements and support de-worming• Continue supervision of teachers, targeted provision of teaching and learning materi-
als at secondary level, incl. science & technology• Expand enrollment at teacher training colleges in balance with qualified teacher
needs, and at university level• Implement national policy on mother tongue instruction
Efficiency enhancement • Appropriate distribution of teachers according to enrollmentof public resource • Voluntary re-deployment of existing teachers with an incentive package or transfer of allocation and utilization pupils where feasible
• Budget and expenditure framework for all resources/common procedures using GoMsystems
• Adapt EMIS and funding formulae to meet enrollment changes at district level• Adjust cross sub-sector resource allocation for future balanced sector development
Strengthening • Improve data; EMIS, codification of all schools and teachers, merging of MoF and institutional MoEST salary and financial databasesarrangements and • Strengthen district-level capacity of local system management, including school capacity for service inspection, teacher development, monitoring and reportingdelivery • Strengthen management capacity at the school level, including the capacity of School
Management Committee at primary level
CHAPTER 1
Macroeconomic and Demographic Context
country’s economic and social devel-opment is dependent on the naturalresources and the human capitalavailable to that society. In Malawi,
the natural resource base is limited to an agri-culture sector heavily reliant on the export oftobacco and on prevailing tobacco prices. Thisreliance on one economic sector, allied to arecent decline in the terms of trade, makes thedevelopment of human resources—and the useof knowledge—both an obstacle and an oppor-tunity for Malawi if the country is to diversifyits economy and increase overall levels of pro-ductivity. However, without an investment ineducation and knowledge Malawi will havefew, if any, choices and the prospective foreconomic growth will remain bleak.
The level of investment in education is deter-mined largely by the strength and size of theeconomy (the macroeconomic conditions); bythe demographic characteristics of the popula-tion; by decisions about expenditure on educa-tion versus other sectors; and by the capacity ofthe education system to absorb existing andincreasing resources. As will be highlightedlater, while the absolute amount of resources isimperative for the development of a system, stillmore important is the ability of the governmentto efficiently use its existing internal and exter-
nal resources. Unfortunately, the wastage in theMalawi education system is substantial and, assuch, the opportunities to increase efficienciesare enormous. This is particularly the case inthe current situation where institutional struc-tures are weak and where accountability andincentives to perform are largely non-existent.While the first two determinants, demographicand macro-economic contexts, are often diffi-cult to influence in the short term, the improvedmanagement of the system and the efficient useof resources are within the control of schoolsand the Ministry of Education, Science andTechnology (MOEST).1
Other important aspects of educationrelate to the micro-economic conditions,including poverty and high opportunitycosts, and other important conditions affect-ing students and teachers, such as chronicmalnutrition, HIV/AIDS, social and culturalsettings—including language of instruction—and the religious contexts within which thesystem operates. These constraints and con-ditions set the framework within which aneducation system can develop, but the levelsof education, in turn, determine economicdevelopment, and the ensuing choices have adirect impact on poverty alleviation in thecountry.
12
A
Macroeconomic and Demographic Context 13
The Malawi government is faced with sometough but undeniable questions and chal-lenges. For example, how much should thegovernment invest in education? How muchshould it invest in the sub-sectors of education,when some adjustments to issues of quality,access and equity need to be addressed? Thepresent study will seek answers to questionsabout limited choices and will attempt todelineate a number of options and difficultchoices that need to be addressed across theprimary, secondary and higher education lev-els. The study also recognizes that without anintervention, the Malawian education systemwill continue its downward spiral. In this firstchapter, the focus is on general characteristicsof the macroeconomic, demographic and socialcontext in the country, and the overall capaci-ty of the system, including the impact ofHIV/AIDS.
Evolution in gross domestic product, per capita income and fiscal resources
Malawi is a small landlocked country situatedin southeastern Africa. Its land area is approx-imately 119,140 square kilometers and it has apopulation of about 10 million. In the 40 yearssince it became an independent country in1964, Malawi has stagnated at extremely lowlevels of per capita income. In recent years, theprevalence rate of the HIV/AIDS pandemic hasincreased to almost 20 percent and is responsi-ble for the deaths of thousands of Malawians,including teachers, civil servants and parents; itis also leaving numerous children orphaned.When the government introduced the Free Pri-mary Education Policy (FPE) in 1994, enroll-ment soared by approximately 1 million pupils(from 1.9 million to 2.9 million). However, thepolicy has been implemented in a largelyunplanned manner and without adequatefinancing. While it resulted in enormousprogress towards the goal of providing access
to primary education for all, it also forced thegovernment to recruit numerous teachers thathad no formal teacher training. In primary, theshare of untrained teachers in the total stock ofteachers rose from 20% to 50% upon theintroduction of FPE and has largely stayed thatway thereafter.
The combination of these factors—externalenvironment (macro-economic, famine, mal-nutrition, HIV/AIDS), declining per pupilspending (especially in secondary educationand teacher training2), and increasing numbersof untrained teachers, especially in primaryand secondary—has resulted in the educationsystem becoming unbalanced and with partic-ularly deleterious effects on quality. In manyways one can speak of a collapse in the educa-tion system. This has been further exacerbatedby a soaring debt burden and the collapse offiscal management and accountability follow-ing the introduction of multi-party electionsand FPE. Malawi is one of the poorest non-conflict countries in the world today as reflect-ed by its sobering human development indica-tors, as shown in Table 1.1.
Table 1.2, below, traces the evolution in thepopulation and economy. As shown (see alsoAnnex 1.1), in constant 1994 kwacha prices,GDP increased by 32 percent between 1991/92and 2001/02, i.e. an average annual growth of3.2 percent. Per capita income in current USdollars stood at US$177 in 2002. As the popu-lation grew by 21 percent over the last decade,per capita income rose slightly at an average ofroughly one percent per year.
Grants (including HIPC but excludingloans) as a share of GDP have been volatileover time but the overall trend over the pastdecade is one of a strong increase, from levelsof 3 percent of GDP to 6–8 percent of GDP (oras share of government revenue from levels of10–15 percent to levels of 25–35 percent). Thisindicates a strong and increasing dependencyon foreign assistance in the public sector.
Total public expenditures as a percentage ofGDP rose from about 25 to 35 percent during
14 Cost, Financing and School Effectiveness of Education in Malawi
the last decade; in real terms, the public expen-diture grew by 94% from 1991/92 to 2002/03.In general, both development and recurrentexpenditures as a share of GDP have increased.The higher level of public expenditure in2002/03 compared to 1991/92 is partlyfinanced through slightly higher government
revenues, partly through the above-mentionedincrease in grants, and partly through increas-ing the public deficit reaching as much as 7.7%by 2002/03.
In considering the prospects for educationaldevelopment, it is important to assess the out-look for economic growth and possible
Botswana Kenya Malawi Mauritius Mozambique S. Africa Tanzania Uganda Zambia ZimbabweGDP Per Capita (constant 1995 US$) 3951 328 157 4429 195 3985 193 355 392 656
GNI Per Capita, PPP (current US$) 7190 1010 600 9940 820 9180 530 1230 750 2590Growth of Per Capita GDP 3.2 0 3.5 4 .5 5.2 0 .7 1.6 4 .2 -0.6 0 1995-2000 (% p.a.)Life Expectancy at Birth 39 48 39 71 43 48 45 42 38 40
Percent Share of Income/Consumption of the Lowest 10% of Po pulation .. 1.80 2.50 .. 2.50 1.10 2.80 2.60 1.60 1.80
Percent Share of Income/Consumption of the Lowest 20% of Population .. 5.00 6.30 .. 6.50 2.90 6.80 6.60 4.20 4.00Survey Year .. 1994 1997/98 .. 1996/97 1993/94 1993 1992/93 1996 1990/91
Table 1.1: Social and economic indicators (latest year available)
Note: The Per Capita GDP growth in Malawi is distorted by the 14.9% increase in 1995 after an 11.6% decline in 1994 (which is not included in thecalculation). The picture from 1996–2000 for instance is of 1.7% annual growth, and from 1981–2000 of only 0.4% annual growth.Source: World Development Indicators.
Table 1.2: Evolution in population, GDP, and total government revenue and expenditures
Deficit, counting Grants as a deficit-determining item5 –3.0% –11.2% –5.3% –14.8% –4.9% –2.7% –6.9% –4.7% –5.7% –5.2% –7.5% –7.7%Deficit, counting Grants as a deficit-financing item6 –6.2% –13.4% –8.2% –24.2% –11.6% –7.0% –11.0% –11.1% –12.6% –14.0% –14.1% –14.5%
Sources: IMF “Selected Issues and Statistical Appendix. August 2002.”; WB SIMA database; and authors’ calculations. Government expenditure data are ‘actuals’with the exception of the most recent data for 2001/02 and 2002/03, which are estimates from IMF “First Review under the Poverty and Growth Facility and a Requestfor Waivers of Performance Criteria. August 2003.” Population data are from WB-HNP Stats. Inflation and exchange rate are from IMF as referenced in PER.
Macroeconomic and Demographic Context 15
increases in revenues. But the economy hasbeen struggling and its expected growth for thecoming years is not predicted to be much dif-ferent from the roughly 3 percent yearlygrowth experienced during the previousdecade.7 The estimated growth is anticipatedto exceed the population growth, but per capi-ta incomes, and consequently per capita gov-ernment revenues, are not expected to risemuch.
In summary, the economy cannot be expect-ed to generate much additional resources in theshort to medium term. The structure of theeconomy, with its high reliance on tobaccoexports, raises serious questions about thelong-term growth prospects for Malawi’s edu-cation system: What are the goals for educa-tion in Malawi? Can Malawi afford a furthermajor increase of its education system giventhe expected limited resources available?
The determining factors when estimating theimpact of economic growth on governmentrevenues (and on the potential of generatingadditional resources to invest in education),are the composition of the labor force and thecontribution of each economic sector to GDP,as shown in Table 1.3, below.
The estimated Malawi labor force in 2000was 4.5 million9 with a US$1.5 billion econo-my. The relative share of people working inagriculture is still high at more than 80 percentof the population. As Table 1.3 indicates,industry and services contribute to approxi-mately 60 percent of the measured GDP, butonly benefits about 16 percent of the work
force. In contrast, the majority of Malawians(84 percent), most of whom are subsistencefarmers, contribute only 40 percent to the GDP(or about $159 per worker against $1,307 perworker in services and industry).
This clearly constitutes a dilemma. Anexpansion in industry and services is likely tocontribute proportionally more to GDP andgrowth and fiscal revenue, but would only ben-efit a small segment of the population. In turn,while investment in agriculture has the poten-tial to increase, to some degree, productivityand outputs (and thus fiscal revenue), themajority of farmers hold less than 1 hectare ofland10 and, as such, are unlikely to either con-tribute or benefit much from any interventions.Furthermore, opportunities for these smallfarmers are limited in terms of excess produc-tion and productivity gains, and thus for anincreased tax base. In other words, the majori-ty of Malawians are caught in a poverty trapwith extremely limited assets (land) and highilliteracy rates.
In the long term, any per capita growth willhave to rely on increasing the land size of farm-ers and consequently gradually moving a highnumber of farmers out of agriculture. This, inessence, is Malawi’s dilemma: To increase pro-ductivity and provide new opportunities forthe majority of rural Malawians, the govern-ment will have to invest more in quality pri-mary education in the short term. From aneducational perspective, however, a parameterfor increasing economic growth is to supportthe industry and service sectors and the expan-
Table 1.3: Output and employment
Share of total labor force GDP 2000 (in million USD)8 GDP sector share of total (in thousands and %)
Sources: IMF Statistical appendix, July 2002. Uses 2000 GDP in constant 1994 factor cost Kwacha, and the average 1994 exchange rate of 8.74Kw/USDLabor force from 1998 population census, and includes formal and non-formal sector employees.
16 Cost, Financing and School Effectiveness of Education in Malawi
sion of these sectors to absorb increasing num-bers of workers. This, in turn, requires a larg-er proportion of high quality secondary andtertiary graduates, which necessitates furtherinvestments in post-primary education.
While Malawi’s favorable prospects forlong-term growth are strengthened by thecountry’s intention to improve education andto diversify the economy, government revenuesin the near and medium future will be generat-ed largely by the current formal sector (agri-cultural tobacco exports, industry and theservice sector). As a result, the fiscal burden islikely to be borne by a small fraction of thelabor force for the foreseeable future.
On the other hand, a growing labor forceand declining dependency ratio (see Table 1.4)will allow the fiscal burden to be shared by arelatively higher number of workers. The argu-ment here is that if there are fewer people out-side the labor force than actively participatingin it, the spending per beneficiary for publicsubsidies can be increased.
The dependency ratio has declined slightlyover the last decade, indicating an ease in thefiscal burden on workers. However, this slight-ly positive trend in Malawi is hiding a fright-ening reality: HIV/AIDS. While the decliningratio suggests an easing in the fiscal pressure,the reality is that the number of female-headedhouseholds (30 percent), and the number oforphans, has increased. While these groups donot directly claim resources from government,
they do increase opportunity costs as a resultof the weaker income bases in families, theneed of an economic structure to supportorphans, and because the characteristics ofHIV/AIDS contribute to a higher rate of illnessin families. These factors (indirect or directcosts) need to be addressed by government ifefforts to improve the human capital base areto be successful. Furthermore, the reduction inlife expectancy has a severe impact on workers’total number of active working years, theirproductivity and, consequently, their total netcontribution to the economy. The marginaloutput per worker as a result of HIV/AIDS isprobably inflated in the short run, as initially,output remains largely the same while workersdie.11 However, in the case of some countries,Uganda, for example, HIV/AIDS is likely tohave a negative effect on average productivityin the longer run—productivity gains thatwould normally be an alternative means ofincreasing the value-added in the formal sectorand, thereby, an increase in revenues. Thiseffect compounds the already depressed pro-ductivity levels in Malawi that result from thecurrent low levels of education.
Evolution in inter-sectoral allocationof public expenditure, in educationspending, and HIPC resourceavailability
Figure 1.1 indicates that prior to 1994, recur-rent spending on social (and community) serv-ices was lower than spending on public affairs,unallocated expenses and economic services.This situation changed abrubtly from 1994/95on when social services recurrent expenditureincreased and surpassed spending on generalpublic affairs and economic services. Here, alittle less than half of the increase in the pro-portion of spending to social services went tothe education sector (see Annex 1.2)—this wasmostly linked to the introduction of FPE and
Table 1.4: Evolution in the dependency ratio, 1990–2000
Source: HNP Stats, World BankNote: Dependency ratio is calculated as the population aged 0–14plus >65 over the working force population aged 15–64
Macroeconomic and Demographic Context 17
the resultant increase in expenditures neededto pay the additional teachers recruited.
Over time, the increase in the proportion ofsocial services expenditure has largely been atthe expense of the proportion of economicservices expenditure, more than at the expenseof the proportion on general administration
(general public service, defense, public orderand safety) and on unallocated services (debtservice, pensions and gratuities and others12).The proportions of general administration andunallocated services have been very volatileover time, but overall, no significant changeshave occurred during the past decade.
0.05.0
10.015.020.025.030.035.040.045.050.0
1990/911993/94
1994/951995/96
1996/971997/98
1998/991999/00
2000/012001/02
General Administration Social Services
Economic Services Unallocable Services
Figure 1.1: Recurrent expenditure by functional classification, in percentages of total
Source: Malawi Economic Report, various issuesNote: All percentages are based on ‘actuals’, except for 2001/02, which is based on the ‘estimate’.
0.00
10.00
20.00
30.00
40.00
50.00
60.00
1990/911993/94
1994/951995/96
1996/971997/98
1998/991999/00
2000/012001/02
General Administration Social Services
Economic Services Unallocable Services
Figure 1.2: Development expenditure by functional classification, in percentages of total
Source: Malawi Economic Report, various issuesNote: All percentages are based on ‘actuals’, except for 2001/02, which is based on the ‘estimate’.
18 Cost, Financing and School Effectiveness of Education in Malawi
Figure 1.2, below, shows breakdown by sec-tor of development expenditure and indicatesthat the shares of development expenditure areeven more volatile than recurrent expenditures.This derives from the nature of large invest-ment projects and those that tend to be one-offs typically dependent on donor support.Nevertheless, the share of total developmentbudget that went to the social and communityservices sector in the post-1994 period wasclearly higher than in the pre-1994 era. Theshare of development expenditure allocated toeducation also fluctuated greatly, with a peakin 1994/95, but thereafter stabilized at around10 to 15 percent.
As can be seen from Table 1.5, below, totaleducation expenditures (TEE) as a share of totalgovernment expenditures (TGE) rose initially(after the introduction of FPE) from 13 percentin 1993/94 to 18 percent two years later, butdeclined after 1998 to pre-FPE levels. However,in 2001/02, spending on education rose again to16% and is expected to have remained at thishigher level the past couple of years, eventhough official data are not yet available. Main-taining a high level of spending on the social sec-tors is a requirement under the HIPC initiative,as reviewed later in this Chapter.
The development expenditure on educationseems to have been very low in some years.However, one explanation could be that mosteducation development expenditures are offbudget and not included in public spendingdata. In 1999/00 and 2000/01, the share of
bilateral off-budget development spending wasestimated at 65 and 70 percent, respectively.External funding was recently estimated to bearound one third of total education spending.13
The evolution in education expenditures, asa share of GDP, shows a slightly negative trendin the nineties but started recovering in2000/01. This ratio, however, may actually behigher if off-budget development expenditurewere included.
Table 1.6 indicates that Malawi, by the endof the nineties, was somewhat below averageon education expenditure as a proportion ofdomestic revenue relative to other Africancountries. In particular, when compared toUganda—another country that is goingthrough an expansion in enrollment as a resultof a free primary education policy—the educa-tion spending in Malawi was at the lower end;spending on education has however recoveredin the last few years.
Malawi is eligible for assistance under theEnhanced HIPC Initiative. HIPC receipts andprojected receipts were initially estimated in aWorld Bank report (World Bank. 2000) atUS$91.4 million for the fiscal years2000/01–2002/03. An indicative allocation ofthe bulk of these resources by governmentshows that education would be allocated asubstantial proportion of this amount estimat-
Table 1.5: Trends in public spending on education, and comparison to total government spending, 1993/94–2001/02,in percentages
TEE in Total Government Expenditure (TGE) (%) 13 14 18 17 20 14 13 12 16
TEE (Recurrent) in TGE (R) (%) 13 10 16 19 21 14 16 12 16TEE (Development) in TGE (D) (%) 15 28 23 8 15 13 9 12 15TEE in GDP (%) 3.3 5.7 5.4 3.9 5.5 3.7 3.7 4.0 4.7TEE (Recur.) in GDP (%) 2.6 3.6 4.0 3.5 4.7 2.5 2.8 2.8 3.6TEE (Develop.) in GDP (%) 0.7 2.1 1.5 0.4 0.8 1.2 0.9 1.2 1.1
Sources: Malawi Economic Report, various issues
Macroeconomic and Demographic Context 19
ed at US$25.2 million over the full period.14
Of this amount, approximately two thirdswould be allocated to teaching materials whileanother third would be for teacher training. Asthe bulk of this assistance was provided afterthe last year for which actual expendituresdata are available (2000/01), it is not clearwhether these additional resources have mate-rialized and been allocated to the educationsector.
After 2002/03 it is possible to expect a fur-ther increase in the yearly debt relief, thusensuring additional resources for the educationsectors. This is estimated at approximately 10percent above the 2002/03 level that was esti-mated at US$44.2 million in total and atUS$12.8 million for education.15
The debt relief is contingent on the govern-ment’s commitment to pursuing a limited set of‘completion point triggers’ and actions recog-nized as important for poverty reduction andgrowth. In the education sector, the focus is onimproving the quality of education by: (i)increasing to at least 23 percent the share ofeducation sector (including universities andother subvented organizations) expenditure inthe discretionary recurrent budget; (ii) ensuringyearly enrollment of 6,000 students for teachertraining, and establishment of in-service train-ing for primary teachers; (iii) reallocating ofbudgetary resources from secondary schoolboarding (except for ‘special needs education’)to teaching and learning materials; and (iv)
pre-packaging donor-supplied primary text-books for each school with delivery directlyfrom the supplier to the schools.
The first of these ‘completion point triggers’also provides an additional means to examinethe current and expected resources made avail-able for the education sector; it will be possibleto verify how far the target of ‘at least 23 per-cent’ of education expenditure in the discre-tionary recurrent budget has been achieved.However, the picture for recent years for which‘actuals’ are available and the most recent‘revised estimates’ (i.e. for the most recentyears no ‘actuals’ are available) indicate a greatdeal of volatility and some discrepancies,depending on the data sources that are used(see Annex 1.3). This makes it difficult to drawany firm conclusions. However, the proportionof education sector expenditure in the discre-tionary recurrent budget appears on average tobe relatively close to the target of 23 percent.Depending on the data source, the average forthe past six years (mixture of ‘actual expendi-tures’ for the first four years and ‘estimatedexpenditures’ for the last two years) has been23.7 percent or 24.6 percent and, as such, iswithin the set target.
Notes1. From 2004, the Ministry of Education
and Human Resources.
Table 1.6: Comparative information on government recurrent spending on education as a percentage of governmentcurrent revenue, excluding grants, and as a percentage of GDP
Educ. recurrent exp. as % of gov. curr. rev excl grant 17.3 15 17.6 18.1 9.9 32.6 30.1 12.3 28.3 17.8
Educ. recurr. exp. as % of GDP 2.5 2.8 3.8 2 4.6 3.2 3.2 2.3 7.1 3.04
Source: Bruns, B. et al. 2002. For Malawi, authors’ calculations are used. * Refers to 33 African countries
20 Cost, Financing and School Effectiveness of Education in Malawi
2. In primary there was a huge dip in1994/95, upon the introduction of FPE; main-ly due to hiring large numbers of untrainedteachers, the unit cost started adjusting againand by 1997/98 it reached more or less pre-FPE levels again and has largely remained atthat level thereafter.
3. This is the 2000 value instead of 2000/01.4. This is the 2002 value instead of 2002/03. 5. Deficit as the difference between Revenue
plus Grants, and Expenditure.6. Deficit as the difference between Revenue
(excluding Grants), and Expenditure.7. IMF/World Bank CAS/PRGF projections.8. Industry includes mining & quarrying,
manufacturing, electricity & water, construc-tion. Services include distribution, transport &communications, financial & professionalservices, ownership of dwellings, private com-munity services, and government services.
9. Of course most of them work in the infor-mal economy.
10. Average land size in the EU is about 40hectare: despite high levels of productivity anduse of technology EU farmers are dependent onhigh levels of subsidies (about 20 percent ofincome).
11. Jill Armstrong, Uganda’s AIDS Crisis:Its Implications for Development, World BankDiscussion Paper 298 (Washington, D.C.:World Bank, 1995).
12. The travel budget as a share of GDP isone of the highest in Africa.
13. In 1999/00 recurrent and developmentspending together were 4,657 million kwacha,the on-budget donor spending was 516 millionkwacha and off-budget donor spending 1,065million kwacha. For 2000/01 these wererespectively 4,987, 492.9 and 1,295 millionkwacha.
15. However, the Reserve Bank (in “ReserveBank of Malawi: Foreign Exchange Budget,1997–2002” on 22. October 2003) publishedprojected total HIPC relief by calendar year(not fiscal year), where there is still a signifi-cant expected increase from 2003 to 2004.Projections for total HIPC debt relief by calen-dar year (not fiscal year), where there is still asignificant expected increase from 2003 to2004. Projections for total HIPC debt relief areas follows: 2001 US$27.4 million, 2002US$28.8 million, 2003 US$51.6 million, and2004 US$78.0 million.
CHAPTER 2
Enrollment Patterns
hapter 1 described Malawi’s educa-tion system in the context of macro-economic trends, government rev-enue and spending on education,
and issues related to demographic changes andthe impact of HIV/AIDS. This chapterdescribes the overall education system. In addi-tion to common indicators of coverage, such asgross enrollment ratios and entry rates,detailed information is presented on patternsof cohort survival, grade-specific enrollment,transition rates, completion rates, dropout andrepetition.
Structure of Malawi’s educationsystem
The formal education system in Malawi, as of2003, follows an 8–4–4 structure: 8 years ofprimary, 4 years of secondary and typically 4years of university level education1 (see Figure2.1). At the end of primary, pupils sit for thePrimary School Leaving Certificate Examina-tion (PSLCE), which determines their eligibili-ty for entry into secondary school. Public sec-ondary students attend either Community DaySecondary Schools (CDSSs) (previouslyMCDE), or Conventional Secondary Schools
(CSSs). After two years of secondary, pupils sitfor the national Junior Certificate of SecondaryEducation (JCE); after two more years, for theMalawi School Certificate Examination(MSCE). Tertiary education is provided by anarray of education institutions including pri-mary and secondary teacher training colleges,technical and vocational training schools, anduniversity colleges. For university entrance andfor the secondary teacher training college(Domasi), an MSCE certificate is required. Forprimary teacher training the policy is to takeMSCE graduates, but JCE passers can also beaccepted. Technical and vocational trainingcan start either after JCE or MSCE.
Primary education, preschool education andnon-formal education initiatives such as adultliteracy fall in the category of basic education,with the purpose to equip people with basicknowledge and skills to allow them to functionas competent and productive citizens in a freesociety. Primary and secondary education isadministered by the MOEST through its head-quarters, the six education divisions and 33district education offices. University level edu-cation is sub-vented by government, and uni-versity institutions are autonomous. The pri-vate sector participates in the provision of alllevels of education but this is most pronounced
21
C
22 Cost, Financing and School Effectiveness of Education in Malawi
at the secondary level where private sector con-tributions have been increasing substantially.
The current school calendar was introducedin 1997; the year is divided into three semes-ters, or terms, and commences in January andends in November. The end of each term is fol-lowed by a holiday of three to four weeks. Thelongest school holiday commences in Novem-ber when the schools close for almost twomonths.
Enrollment trends
Data on enrollment at the different levels ispresented in Table 2.1.2 The Malawi educationsystem is characterized by permitting only asmall share of primary school graduates accessto post-primary levels. This situation was fur-ther exacerbated by the introduction of FreePrimary Education, which led to an increase inprimary enrollment of about 50 percent; or a
Figure 2.1: Structure of Malawi’s education system
Source: Basic Education Statistics.
Table 2.1: Distribution of enrollment, by level of schooling, 2000
total of one million new students entering pri-mary. Less than 9 percent of the total studentpopulation is currently enrolled in post-pri-mary education, while 91 percent of totalenrollment is in primary education and of these65 percent (or 2.2 million) are enrolled inlower primary (Standards 1 to 4).
Pre-primary education
There is considerable evidence worldwide toindicate that attending nursery school helps achild prepare for primary school; it also pro-vides a foundation for lifelong learning. InMalawi, the Ministry of Gender, Youth, andCommunity Services organizes public EarlyChildhood Development (ECD). In 2002 therewere 1,618 childcare centers registered withthe Ministry, with 4,666 pre-school teachersresponsible for approximately 80,000 children,aged between 3 and 6 years.4 Annex 2.1includes background characteristics of childrenbetween the age of 6 and 14 who attendednursery schools, whether public or private.These data indicate that about one in ten chil-dren (9.4 percent) had attended nursery schoolfor an average of 1.7 years. Two factors areimportant predictors for nursery school enroll-ment: geographic location and income group.In urban areas, 39 percent of children attendednursery school compared with just 6 percent inrural areas. Furthermore, 27 percent of chil-dren from the highest wealth quintile attendednursery school—approximately 10 times morefrequently than children from the lowestincome group. This difference is compoundedby the fact that years of attendance are longerfor both urban and wealthy children. Youngerchildren are also more likely to have gone tonursery school than older children; only 5 per-cent of the 11–14 age group compared to 15percent of those aged 6–7 years had attendednursery school. This suggests that more par-ents than heretofore are sending their childrento nursery schools.
A troubling feature of the Malawi system isthe significant number of underage childrenenrolled in primary; for instance, in 2002, 28percent of 5 year-old children were alreadyattending primary school.5 To address this,according to the new primary school curricu-lum (2002), the government is consideringreducing the primary cycle from eight to sevenyears while introducing a pre-school year.However, such a change may draw awayresources from primary and secondary levelsalready struggling to be financially sustainable.Future investment needs to be based on a care-ful cost-benefit analysis, one that weighs gov-ernment investment in pre-school educationagainst improvements in the currently under-funded lower grades of primary.
Basic or primary education
Malawi has two types of primary schools: pub-lic and private. The latest school census for2001 established that there were 4,688 pub-licly funded primary schools with a totalenrollment of 3,143,427 (EMIS database2001). These include schools where the propri-etor is the central government, the Local Edu-cation Authority, or a religious agency thatreceives public funding. The total number ofprivate schools is difficult to determine becausegovernment only recently started to registerprivate schools. Currently, the number of gov-ernment registered private schools is 49 andthey enroll 18,500 pupils. The Private SchoolsAssociation of Malawi, PRISAM, estimatesthat there are about 40,000 pupils in 250schools. However, the Ed Data 2002 surveyindicates that enrollment in private primary ismuch higher; most likely around 5 percent oftotal primary enrollment—about 2 percent inprivate non-religious schools, and 3 percent inprivate religious schools.
Since the abolition of all primary school feesin 1994, access to primary has increased dra-matically allowing practically all children to
24 Cost, Financing and School Effectiveness of Education in Malawi
attend school. Figure 2.2, below, illustratesthat more than 95 percent of children attendprimary school at some point in their lives.
One way to measure the increase in enroll-ment is to consider the changes in the grossenrollment rate (GER) over time. Table 2.2illustrates that the GER for primary hasincreased substantially over the past ten years—from 88 percent prior to the introduction ofFPE (in 1991/92) to roughly 120 percent at theend of the decade — an indication of the suc-cess of the FPE in improving coverage.
Enrollment by age in primary
When FPE was introduced about 10 years ago,many of the children that enrolled for the firsttime were over-age. It was anticipated that thissituation would level out in subsequent years
and that gradually a higher number of childrenwould enroll within an age appropriate cohort— in other words, that the GER would con-verge towards the Net Enrollment Ratio(NER). However, as Figure 2.2 shows, timelyenrollment remains an issue: at age 7 onlyabout 70 to 80 percent of children have start-ed school. Late or early entry is common par-ticularly in rural areas where children’s agesare difficult to determine in the absence of doc-umentation. The problem of early entry iscommon when the school is perceived as pro-viding free childcare or when younger childrenjoin their older siblings. Late entry is commonwhen children have to walk far to get toschool, and is then compounded through repe-tition of grades. The persistently high numberof over- and under-age children points to bothdemand and supply side issues. On one hand,
Source: Basic Education Statistics and UN Population data used for EFA-FTI.* Taken from Basic education statistics.** From DRAFT Basic Education Statistics 2001.
Figure 2.2: Proportion of children who ever enrolled in primary, by age
Source: Authors’ calculation using data from the DHS 2000 survey and IHS 1998.
Enrollment Patterns 25
the opportunity cost associated with having achild in school affects enrollment and atten-dance. On the other hand, the inadequatelearning environment leads to low outcomesand high repetition rates.
The various sources of data on enrollmentprovide conflicting information about theextent of over- and under-age children in pri-mary (Figure 2.3 and Annex 2.3). The house-hold survey data indicate that the number ofover-age children is much higher than recordedby the official school census statistics records.According to the household survey, close to 30percent of 5 year-olds are already enrolled(representing close to 100,000 children)whereas school census data puts this estimateat 15 percent.
In addition to needing more reliable statis-tics, the more significant challenge is how toreduce the age disparity of primary school chil-dren. The existing wide age range makes teach-ing and learning even more difficult in an envi-ronment that already has many additionalfactors undermining the quality of education.To address the problem of over-age children,the most important measure by far is toimprove the quality of education in order toreduce repetition rates so children attain satis-
factory learning outcomes and simultaneouslyprogress more rapidly through primaryschool.6
Disparities in enrollment data andsources
The analysis in Annex 2.2 indicates that theGER in primary has, in recent years, fluctuat-ed between roughly 110 and 133 percent.7 Inlight of the strengths and weaknesses of eachdata source, for the purpose of the ensuing cal-culations, the gross enrollment ratio is estimat-ed to be about 120 percent.
If the GER for lower versus upper primary,as shown in Figure 2.4, is examined it providesa more accurate picture of the pressures on thelower standards as a result of repetition andearly/late entry. The gross enrollment ratio is ashigh as 170 percent in the first four grades butshrinks to a mere 70 percent in the last fourgrades. The high GER in lower primary con-firms that a high proportion of children repeatstandards 1 to 4.
Figure 2.5, below, indicates the evolution inenrollment by standard during the nineties.The sharp rise in Standard 1 enrollmentbetween 1993/94 and 1994/95, and the more
aaaagggg eeee"DHS 2000" 2000 Min Educ enrollm and NSO smoothed est. based on orig. pop. census 2000 Min Educ enrollm and Unesco pop
Figure 2.3: Enrollment rate by age, different sources, 2000
Source: Authors’ calculation using data from the DHS 2000 survey, from EMIS 2000, and from the National Statistics Office and UNESCO forpopulation estimates.
26 Cost, Financing and School Effectiveness of Education in Malawi
moderate but still significant rise in enrollmentin other standards, is attributable to the decla-ration of FPE. In fact, in 1991/92 when fees forStandard 1 pupils were abolished, enrollmentgrew by 19 percent over the previous year, andin 1994/95, when the policy was extended toall primary school pupils, enrollment grew by51 percent compared to the previous year.
The much lower enrollment increases in thehigher standards during subsequent years sug-gest that many children that enrolled in1994/95 did not progress to the next level. Thedecline in Standard 1 enrollment after the peakof 1994/95 is attributable to the fact that, in
subsequent years, new entrants were primarilychildren of normal entry age (age 6).
Pattern of student flow through thesystem, survival, repetition rates andefficiency
The gross enrollment ratio is a useful measureof the capacity of the education system in termsof the number of places available. However, inMalawi, grade repetition and drop out are com-mon, and consequently the gross enrollmentratio is a poor measure of actual coverage.8
This next section investigates the efficiency of
0 5 0 100 150 200
stand 5-8
stand 1-4
primary
Figure 2.4: Gross enrollment rates by level of schooling, 2000
Source: Basic Education Statistics, and UN population.Note: For primary the corresponding population is children 6 to 13, with population 6 to 9 for Std. 1-4 calculations and 10-13 for Std. 5-8calculations.
Source: Basic Education Statistics, various years.
Enrollment Patterns 27
the education system, by examining pupiladmission, survival and transition rates.
Comparing Data Sources to calculate EntryRate, Population and Repetition. The ‘CohortRate of Entry’ (or gross admission rate) is cal-culated by dividing new standard 1 entrants(or non-repeaters) by the total population ofschool entry age. In 1987 this indicator was0.87 (87 percent) but in 1998 it had increaseddramatically to 2.29 (229 percent) when usingthe standard school census and populationcensus statistics. It is obvious that under nor-mal circumstances the ‘cohort rate of entry’should not be more than 1, as there should notbe more new children enrolling into primary asthere are children of the corresponding agegroup. As analyzed in Annex 2.4, a non-stan-dard use of the repetition rate concept, togeth-er with a probable undercount of the popula-tion in the 1998 census explains part of thediscrepancy.
It is thus likely that the school census statis-tics underestimate the level of repetition(Annex 2.4). The household surveys availablefor 2000 and 2003 provide an alternativemethod to assess the extent of repetition. Fur-thermore, if the high-end population estimates,like those from UN-EFA, are used, the incon-sistency is further reduced. Using the bestavailable data, the cohort rate of entry comes
out to 1.39 for 2000. For the purposes of thisstudy, and to enable government to derivehelpful conclusions and identify possible policyinterventions, the repetition rate from thehousehold surveys is used in the following—unless otherwise indicated.9 Likewise the studywill use the UN-EFA population estimate.
Repetition and Dropout Rates. A strikingcharacteristic of the primary education systemis the widespread prevalence of repetition anddropout. However, discrepancies in data makeit difficult to establish the current levels of rep-etition and dropout. Table 2.3 summarizes rep-etition and dropout rates by grade from threedifferent data sources, and shows averages forlower/upper primary and for primary as awhole. The average repetition rate from thetwo household surveys (25.8 and 28.4 percent)is almost twice as high as the recorded repeti-tion rate of 15.5 percent from the school cen-sus with the largest differences noted in Stan-dard 1 and Standard 8. According to all thesources, the repetition rate generally declinesas children progress through the grades, withthe exception of standard 8 where repetition isvery high. In general, boys are more likely torepeat than girls, particularly in Standard 8.10
This trend may be due to parents’ greater con-cern to see their sons, versus daughters,progress into secondary school.
Table 2.3: Repetition and dropout rates, EMIS 2000 and DHS 2000
Sources: Basic Education Statistics 1999, 2000. The repetition rate is calculated here as the repeaters in grade x in 2000 divided by the totalenrollment in grade x in 1999. The dropout rate here is calculated as the dropouts from grade x in 2000 divided by the total enrollment in grade xin 1999.For DHS 2000 and Ed Data 2002 the results stem from the final reports of the studies. Repetition rates are calculated as the percentage ofstudents in a given standard who are repeating that standard. Dropout rates are calculated as the percentage of students, in a given standard, inthe previous school year (irrespective of whether or not they finished the previous year or left during that year) who did not attend school at anypoint during the school year.*Authors’ calculations using dataset.
28 Cost, Financing and School Effectiveness of Education in Malawi
The dropout rates reported by the differentsources vary considerably, from estimatesaround 4–5% per grade to as much as 10–11%per grade. Two data sources imply thatdropout is more prevalent in the higher gradesthan lower grades, while another source showsthe reverse pattern. Annex 2.6 shows in furtherdetail the causes for children dropping outfrom school.
The Monitoring Learning Achievement(MLA, 1999) study revealed that out of 11African countries, Malawi has the highest rep-etition rate in the first four grades of primary(see Annex 2.5). Further, the difference, rela-tive to other countries, is quite significant, par-ticularly for the first three grades. Not only isthe percentage of children passing from onegrade to the next by far the lowest in Malawi,substantial numbers of children repeat morethan once—a phenomenon rare in most otherSSA countries. The more recent household sur-vey in 2002 recorded a higher dropout ratethan the 2000 household survey. Here, also,dropout rates are much higher in the ruralareas relative to urban areas.11
In summary, primary school is characterizedby extremely high levels of repetition anddropout, irrespective of the source of informa-tion. The challenge in Malawi is to improve on
the present unsatisfactory Primary CompletionRates (PCR). On the positive side there is afirm basis for moving forward since at themoment 95 percent, or more, of all childrenenroll: as such, further improvements will onlybe achieved when a resolute effort to reducerepetition and dropout rates is implemented.
Survival Rates. Figure 2.6 shows an estima-tion of the survival rate by grade in primaryand secondary school and indicates a steepdownward trend throughout primary and amuch flatter trend for secondary (see alsoAnnex 2.7). These data imply that dropoutcould be even higher than the 5–10% indicat-ed in Table 2.3. For example, according to Fig-ure 2.6, in the academic year 1999–2000, forevery 100 non-repeating students that enteredStandard 1 only about 70 were still in schoolby Standard 4, corresponding to an annualdropout rate of more than 11%; by standard 8only a quarter of the potential student popula-tion had persevered, implying that on averageas much as 18% of the class had dropped outeach year. These high dropout rates, however,are not consistent with the Primary Comple-tion Rates presented in the following, and cantherefore be regarded as higher end estimates.
Annex 2.7 also suggests a real deteriorationin survival rates between the time just before
Source: Basic Education Stats 2000 for enrollment, DHS2000 for repetition, UN-EFA population.
Enrollment Patterns 29
the introduction of FPE until today. Resultsfrom the quasi-time series survival estimatesindicate that a student’s chances of “survival”throughout primary went down, possibly asmuch as 20 percentage points. However, due tothe greater intake into primary during the sameperiod, the number of children finishing pri-mary has gone up in absolute terms, as reflect-ed in the improved completion rates discussedin the following.
Completion rates
The Primary Completion Rate (PCR) is themain indicator for Education for All (EFA) andfor the Millennium Development Goal for edu-cation. Both share the goal of achieving by year2015 a completion rate of 100% for six gradesof primary. However, as primary school inMalawi has eight grades, and as there is noexam after standard 6, the corresponding indi-cator is the PCR based on the primary schoolleaving exam at the end of standard 8. Figure2.7 shows the PCR for each year between 1992and 2000.12 It increased by about 15 percent-age points: from 20–25 percent to 35–40 per-cent between 1992 and 2000 and this repre-sents a significant and important improvementin the completion rate (a PCR of 35–40% cor-
responds to average dropout around 10% ofthe student body each year).
Despite the clear positive trend, however, itis not likely that Malawi will reach a PCR of100% by 2015. As such, it may prove moreprudent for the government to develop its owntargets and goals, ones based on a credible andsustainable plan that will enforce and acceler-ate the positive trend in improving the PCR.
Annex 2.9 contains proxy completion ratecalculations in which the non-repeaters at acertain grade level are divided by the popula-tion of the corresponding age group. Com-pared to the other data sources analyzed, theseestimates however seem to be in the higherend, possibly underestimating real dropout: the‘proxy completion rate’ for Standard 4 showsthe remarkable increase in completion rates ofapproximately 45 percentage points over theperiod in question—it reached about 90 per-cent in 2000. For the Standard 6 ‘proxy com-pletion rate’ (which would coincide with theEFA/MDG minimal objective) there has beenan approximate 25–30 percentage pointincrease—it reached 60 to 70 percent in 2000.For Standard 8, the ‘proxy completion rate’ isapproximately 10 percentage points higherthan the real PCR, and has not improved con-siderably since 1995.
0.0
10.0
20.0
30.0
40.0
50.0
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Figure 2.7: Primary school completion rate over time, two population estimates
Source: Basic Education Stats for PLSCE passers, NSO population.Highest level is standard NSO population.Lowest level is using NSO population plus 15%. (UN-EFA population is not available this far back).
30 Cost, Financing and School Effectiveness of Education in Malawi
Being already very close to all children start-ing school, the challenge now is to improve thePCR by reducing the number of dropouts. Acomparison of the primary school completionrates with those of other countries in the regionindicates that Malawi’s PCR is lower thanmost. While it is still at about average for 33sampled African countries, this is not a greatconsolation (see Annex 2.9).
Primary School Leaving Certificate(PSLCE)
At the end of the 8-year primary cycle, pupils sitpublic examinations, which lead to the PrimarySchool Leaving Certificate (PSLCE). The PSLCEis a pre-requisite to enroll in the secondary sub-sector and it is used to select pupils for this levelby ranking them and deciding what type of sec-ondary school they qualify to attend. The passrates in the PSLCE are quite high as can be seenfrom Table 2.4. Performance between studentsin rural and urban areas is quite similar (rural79 percent; urban 77 percent, in 2000); so stu-dents who survive primary in rural areas do notappear to be at a disadvantage in their exami-nation performance.
Junior primary schools and distance to schools
The existence of Junior Primary schools—schools that provide less than the full eightgrades of education—may be a supply-side con-
straint for pupils restricting their access tocomplete the whole cycle of primary education.
To estimate the full extent of the juniorschool phenomenon, it is necessary to distin-guish between two categories of schools. First,there are the recently established schools thatmay eventually offer the full complement ofstandards, and second those schools that havebeen established for a prolonged period buthave not expanded to cater for all standards.Regardless, children attending these schoolsare more at risk of being ‘pushed out’ beforecompleting the primary standards.13 Annex2.10 indicates that approximately 27 percentof all new Standard 1 entrants (650,829pupils) enroll in schools that do not cater forall standards. Approximately two-thirds attendschools that were recently established and, assuch, may include additional grades in thefuture or are already acknowledged as ‘feederschools’. Overall, the extent of the problem oflong established school offering less than sixgrades appears to be affecting only about 4percent of pupils but the key issue is the prox-imity of the ‘complete’ school.
Distance to school is one explanatory factorto indicate why some children do not enter pri-mary or why a significant proportion of stu-dents start attending for the first time at ageshigher than the official entry age. Annex 2.10provides data on distance and walking times toschools in both rural and urban areas. A totalof 64 percent of children in urban areas livewithin 15 minutes of the nearest school; for
Table 2.4: PSLCE results and transition to different types of secondary schools
YEAR 1994–95 1995–96 1997 1998 1999 2000 2001 2002
Source: Exam data is taken from MANEB. Enrollments are from EMIS.Transition rate is calculated as form 1 enrollment in year x / number of PSLCE passes in year x–1.* Based upon estimated enrollment numbers for 2000.**This may be underestimated because a significant number of private schools are not registered with the government and are not included inthe statistics.
Enrollment Patterns 31
rural children the figure is 33 percent—indeed,more than one-third of rural children arerequired to walk more than half an hour. How-ever, the extent of the problem of access tocomplete schools requires further investiga-tion, particularly as the use of feeder, or juniorschools, may be a transient functional mecha-nism that caters for the limited number of chil-dren progressing to higher levels and, as such,may make good economic sense if it entailsmore efficient teacher utilization.
Special education provisions
Government policy on the education of chil-dren with special needs emphasizes the impor-tance of mainstream integration. Here, a keyissue is to raise community awareness of theimportance of facilitating the enrollment ofthese children into regular schools. Currently,there are a number of primary schools thatoffer boarding facilities to children with severehandicaps; the government supports thesethrough maintenance grants. There are cur-rently 28,711 pupils attending normal primaryschools who are defined as having differenttypes of disabilities (Table 2.5).
Transition rates from primary intosecondary school
Access to secondary education in Malawi islimited. However, transition rates for thosewho pass the PSLCE have increased dramati-cally; the average transition rate to secondaryeducation was about 75 percent of PSLCEpassers in 2000 (see Table 2.4, above). Thisincrease has been greatly facilitated by theintroduction of CDSSs, which now enroll the
majority of graduating primary students. In2000, the estimated Form 1 enrollment atCDSSs was 58,101 out of a total secondaryenrollment of 81,443.
It is important to note that the combinationof high transition rates and the introduction ofthe CDSSs resulted in a significant intake intosecondary education. Similarly to the impact ofthe 1994 FPE policy, this expansion wasunplanned and lacked essential funding. As aresult, quality has been seriously undermined.
Secondary education
Secondary education is divided into two sec-tions: junior secondary comprising Forms 1and 2 and senior secondary, comprising Forms3 and 4. At the end of junior secondary, stu-dents sit public examinations. Successful can-didates are awarded a Junior Certificate ofEducation (JCE) which is the basis for enroll-ment into senior secondary education. In Form4 students take the Malawi School Certificateof Education (MSCE) and the results deter-mine access to various tertiary institutions,such as university education, and teacher train-ing14 institutions.
There are several types of SecondarySchools: CSSs, which include GovernmentDay and Boarding Schools, as well as GrantAided Schools; CDSSs; Private Schools; andMalawi College of Distance Education(MCDE). Annex 2.11 includes a description ofeach. The CDSS schools only officially cameinto existence in 1998 when nearly all Dis-tance Education Centers (DEC)15 were con-verted into CDSSs. Most of the teachers atthese centers, however, were primary school
Table 2.5: Students with disabilities integrated in primary schools
32 Cost, Financing and School Effectiveness of Education in Malawi
teachers and were ill-prepared to teach sec-ondary students.
As a result of the above weaknesses, a largenumber of students enrolled in poorly runDECs whereas only a small elite group wasable to access the well funded CSS schools. In1996–1997, DANIDA agreed to assist in theupgrading of all DECs to standard secondaryschool status, under the title CDSS. However,when DANIDA withdrew from the educationsector, the government lacked the necessaryfiscal resources to proceed with the plan: ineffect the change from DECs to CDSSsoccurred in name only. As a result, while aCDSS is expected to provide an equivalentstandard of education as the better endowedCSS, the reality is that they are extremelyunder-funded and the quality, as measured byexamination pass rates, for example, is muchlower. The majority of secondary students areenrolled in CDSSs, and therefore this issueconstitutes one of the major challenges facingthe government.
Enrollment in secondary schools
Enrollment in secondary education increaseddramatically during the last decade; it almostquadrupled from less than 70,000 students in1991/92 to almost 275,000 in 2000 (seeTable 2.6). The GER increased from 10 per-cent in 1993/94 to 27 percent in 200016 (theGER is 30 percent in Forms 1–2 and 23 per-cent in Forms 3–417). The NER is estimatedat about 7–9 percent. The difference betweenGER and NER highlights the problem of
over-aged students enrolled in secondaryeducation. In fact, two thirds of all studentsare outside the official age range (14–17years) for secondary.
Enrollment growth in absolute terms hasbeen concentrated in the MCDEs and CDSSs;they registered an increment of well over100,000 between 1993/94 and 2000. Figure2.8 shows the distribution of enrollment bytype of school between 1993/94 and 2000 andhighlights how the CDSSs have come to repre-sent the lion’s share of secondary enrollment,up from approximately 40 percent in 1994/95to 70 percent in 1999/00.
The Private Schools Association of Malawi(PRISAM) is aware of the existence of a totalof 300 private secondary schools in the coun-try as a whole but, of these, only 171 are offi-cially registered. Furthermore, PRISAM con-cedes that there surely are a significantnumber of private schools not even known tothem. As such, private school enrollment sta-tistics are not reliable. Overall, PRISAM esti-mates that there are close to 90,000 pupilsenrolled in the 300 private secondaryschools—this figure is significantly higherthan MoEST estimates.19 Either way, it isclear that private schools form a significantportion of overall secondary education provi-sion. In fact, according to the Policy Invest-ment Framework (PIF), particularly for sec-ondary schools, the private schools areconsidered crucial in expanding supply of sec-ondary education in order to meet demandfrom a growing number of primary schoolgraduates.20
Table 2.6: Absolute enrollment and gross enrollment ratios in secondary18
1991/92 1993/94 1995/96 1998 2000No. of Students No. of Students No. of Students No. of Students No. of Students
Secondary repetition rates are low inMalawi, although repetition does exist inboth private and public schools. Interesting-ly, stated government policy does not permitrepetition in publicly funded schools. How-ever, repetition does occur and the averagerepetition rate in all schools, based on theDHS 2000 data, was estimated as 3.7 per-cent. In Form 1, the incidence was less thanone percent but it was much higher (19.7percent) in Form 4 due to repetition by stu-dents who have failed or are not ready totake their MSCE exam (average pass ratesare generally low).21 Some students may alsorepeat in order to improve MSCE grades andthereby improve their chance of enteringhigher education.
When students fail the JCE or MSCE, insome instances they change to a differentschool; for example, they may change from aCSS to a CDSS or a private school. This prac-tice runs counter to official policy and so thephenomenon is not captured in EMIS statis-tics. It may be advisable to adjust the EMISmeasurements to reflect the prevailing reali-ties of Malawian secondary education, name-ly that repetition does exist and has thepotential to increase unless the quality isimproved.
Survival/completion in secondary andtransition to tertiary
As previously noted, survival rates indicate theshare of students who enrolled at the beginningof primary, who survive to the end of second-ary (see also Figure 2.6 and Annex 2.8). Thesurvival rate in secondary, as a percent of newentrants, in Form 1 is 58 percent.22 This num-ber reflects survival through to Form 4; it doesnot, however, take into consideration thenumerous students who fail the MSCE examand are forced to leave the system without anyformal proof of having completed the full sec-ondary cycle.
Table 2.7 shows that MSCE pass ratesdeclined dramatically between 1993/94 and1999: down from 48 percent to 14 percent,which affected all types of schools. They sub-sequently increased in 2002 to reach 30 per-cent. This poor outcome is attributed—at leastpartly—to the increasing numbers of studentsattending the low-achieving CDSSs. There is asignificant difference between the pass rates atthe CDSS schools and at the CSS schools (GovBoarding, Gov Day, Grant Aided), as can beseen in Figure 2.9.
The meager learning outcomes achieved byCDSS students probably reflects two factors.Firstly, the best primary school graduates tendto enroll in the better-resourced CSSs, thereby
0
50,000
100,000
150,000
200,000
93/94 95/96 1998 2000
Gov+grant aided
CDSS +night school
private
Figure 2.8: Enrollment in secondary education by type of school
Source: Basic Education Statistics.
34 Cost, Financing and School Effectiveness of Education in Malawi
leaving the CDSSs with weaker students whowill require more concentrated and skilledinstruction to achieve MSCE passing level. Sec-ondly, there is very significant under-funding ofCDSSs relative to other public schools, includ-ing the caliber and qualifications of teachers(see also Chapter 4, Figure 4.4), the availabili-ty of teaching and learning materials, andavailable operational budget.
JCE pass rates present a mixed picture. First-ly, the pass rate is substantially higher than theMSCE pass rate. Further, the JCE pass rate hasremained consistently high even when theMSCE pass rate dropped to its lowest level(between 1997 and 1999). Indeed, it is quitesurprising that the JCE pass rate went up by 12
percentage points between 1993/94 and1995/96 at a time when the MSCE pass rate,for the same cohort of students two years later,dropped from 33 percent to 16 percent. Finally,in some years JCE pass rates have not been con-sistently better at CSSs than at CDSSs, contra-dicting the trend for the MSCE pass rate. Thislack of consistency suggests that the JCE fails toprovide students with realistic feedback onwhere they stand midway through secondary.23
A number of explanations have been offeredto explain the low MSCE pass rates. The FinalReport from the Presidential Commission ofInquiry into the MSCE results (2000) pointedto: (i) insufficient capacity at MANEB to han-dle the increased number of candidates from
Table 2.7: MSCE pass rates prior years
Year 1993–94 1994–95 1995–96 1997 1998 1999 2000 2000* 2002
Source: Pass taken from Basic Education Statistics and MANEB and includes external candidates.* Only internal candidates; Average for both the CSS and private schools together** Gov. boarding 46%, Gov. day 48%, Grant Aided 59%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
CommunityDay
Private NightSchool
GovBoarding
Gov Day GrantAided
Total
Figure 2.9: MSCE pass rates by type of school, 2002
Source: Pass rates from MANEB and include external candidates.Note: pass rate for night schools is quite high. However, this may be a reflection that in night schools a lot of the students in Form 4 do notenroll to participate in the MSCE exam in the first place, so that those who do enroll are probably the ones better prepared for it. In othertypes of schools a much higher percentage of those in form 4 participate in the exam.
Enrollment Patterns 35
CDSSs and private secondary schools; (ii) theproblematic examination process with its secu-rity weaknesses; (iii) the need to prepare stu-dents better for exams by a) improving theirattitude toward education and b) ensuringappropriate levels of discipline are not misin-terpreted because of increased democracy andhuman rights awareness; (iv) low teachermorale; (v) lack of teaching and learning mate-rials and poor infrastructure; (vi) lack ofschool inspection systems; and (vii) an outdat-ed curriculum, overly focused on academicskills and preparation for ‘white collar’ jobsbut too little concerned with creative skills andpreparation for vocational employment.
Despite an increase in Form 4 enrollment,the absolute number of students who passedMSCE declined between 19993/94 and 1999.This trend is particularly worrisome becauseof an increasing need for secondary schoolgraduates to enroll in teacher education inorder to improve the education system as awhole. In 1998, the supply of MSCE gradu-ates was close to the need for teacher educa-tion entrants (due to increased teacher traininglevels as a result of the MIITEP training pro-gram), and the spaces at first year of universi-ty. The need for both primary and secondaryeducation trained teachers will remain high
for the next 10–15 years, so the completionand pass rates at secondary level need toimprove to provide enough candidates forboth university education and teacher train-ing. Although there has been a significantincrease in the MSCE graduates since 2000, itis too early to determine if this will be main-tained.
Teacher training
In general, the teacher training system is notproducing sufficient numbers of new teachersfor primary and secondary schools. When FreePrimary Education was introduced it was nec-essary to recruit large numbers of untrainedteachers24; now, ten years later, there is still ahigh proportion of untrained teachers in thesystem adversely affecting quality and learningoutcomes. Similarly, as a result of the transferof the DECs into full-fledged secondaryschools (CDSSs), the government has had tohire untrained teachers—mostly primaryteachers—to teach in the CDSSs and this hasresulted in an additional drain on the pool ofqualified primary teachers while simultaneous-ly increasing the number of under trained sec-ondary teachers in the system.25
Source: Basic Education Statistics and MANEB database. * Data from DRAFT Basic Education Statistics 2001** Based upon estimated enrollment, not actually counted since many schools failed to provide data. + Between 1996 and 1998 the numberschanged dramatically due to the introduction of the MIITEP training program, with in total over this period 5 cohorts being trained, with a total ofa little over 10,000 students having enrolled. ++ Between 1999 and 2001 MIITEP enrolled only one cohort each year due to resource constraints.In 2002 and 2003 however two cohorts each of 3000 to 3500 students enrolled, and from 2004 on this is expected to increase to two cohorts of4,250 each, or 8,500 students in total. If the number of MSCE passers remain at the level of 2002 then in 2004 the transition rate to TeacherEducation will be 57%. Note: No data on new entrants to first year of university is available after 1999. However, with the total enrollment inuniversity at 3955 in 1999, 3977 in 2000 and 3654 in 2001, it is unlikely that the number of new entrants to university has changed substantially overthe past years. Therefore, the transition rate to university will have changed only as a result of the increasing number of MSCE passers. As such,it is likely to have declined.
36 Cost, Financing and School Effectiveness of Education in Malawi
Primary teacher training
In the period following the introduction of FPE,enrollment in primary rose from 1.8 million (in1992/93) to 2.9 million (in 1994/95). As aresult, demand for additional primary teachersincreased inexorably. At the time, however,annual output from the six existing teachertraining colleges was limited to approximately2,700 teachers. Consequently, MOEST recruit-ed 18,000 school leavers, and the ensuing chal-lenge of providing some training for theseuntrained recruits resulted in the birth of theMalawi Integrated In-Service Teacher Educa-tion Program (MIITEP).26 It is anticipated thatthis high volume program of teacher education,combining face to face instruction and distanceeducation, will need to continue for at leastanother five to ten years in order to train theunqualified teachers currently in the system,increase the teacher stock to cater for primaryenrollment increases, and replace teachers lostdue to retirement, death or job change (attri-tion). The annual attrition rate, currently esti-mated at approximately 6 percent (3 percentdeath related, 3 percent retirement and dropoutrelated), results in the loss of 3,000 teachers peryear—there are currently approximately50,000 teachers in the system.
There are six publicly funded primaryTeacher-Training Colleges (TTCs) in Malawi.Two of these colleges belong to churches andreceive a block grant. The total enrollmentcapacity is approximately 3,000 and this hasremained largely static during most of thenineties. The restricted output of teachersexplains the rationale for introducing the highvolume MIITEP crash program.
Table 2.9 shows that the MIITEP cohortsgraduated during the years 1997 to 2000 at anaverage rate of slightly over 2,500 per year,and from 2001 to 2003 only one cohort grad-uated each year because of funding shortfalls.This completely negated the rationale ofMIITEP since it trained the same number ofteachers as pre-MIITEP. In addition, it resultedin teachers receiving significantly less formaltraining, left TTCs empty for substantial peri-ods of the year—while tutors continued toreceive their salaries.
The intake from 2002 onward has been 2cohorts per year and so from 2004 on approx-imately 4,800 graduates can be expected tograduate.27 It is further anticipated that thetotal training capacity of the combined TTCswill shortly expand from 3,000 to 4,250 teach-ers through GTZ funding and that total outputwill increase to 6,800 students per year by2006.
Secondary teacher training
Secondary teacher training is provided atDomasi College of Education, at the Universi-ty of Malawi (Unima), at Mzuzu Universityand at the private institution, the African BibleCollege. Interestingly, the recommended PIFgoal for a secondary PTR of 40:1 is currentlybeing achieved. However, the PqTR is 120:1(EMIS 2001). As previously mentioned, themajority of the unqualified secondary teachersare trained primary teachers, teaching at theCDSSs. Total output from the combined train-ing institutions remains low; it is currently esti-mated at approximately 350 to 400 teachersper year.28 Domasi College also has a parallel
Table 2.9: Primary teacher training graduates over time
Year 1991/92 1993/94 1995/96 1997 to 2000 2001 2002 2003* 2004* 2005* 2006*
Number of 10379 1923 2706 2000 4800 4800 6800Graduates 1866 2666 2528 (cohorts (cohort (cohort (cohort (cohorts (cohorts (cohorts
1 to 5) 6) 7) 8) 9 & 10) 11 & 12) 13 & 14)
Source: Basic Education Statistics till 1995/96, DTED thereafter. * These are expected numbers.
Enrollment Patterns 37
teacher training system in place, the SecondarySchool Teacher Education Project (SSTEP) pro-gram. It upgrades trained primary teacherswho are already teaching at CDSSs.29
Technical and vocational training
The technical and vocational training sector inMalawi has been characterized by limitedcapacity, a supply driven approach, minimalinvolvement of the private sector, a narrowfocus on the formal sector, fragmentation ofproviders and training schemes and a diversityof assessment/certification systems. Variouspublic and parastatal institutions—mainlyunder the control of the Ministry of Labour &Vocational Training, the Ministry of Educa-tion, the Ministry of Commerce and the Min-istry of Gender, Youth, & Community Ser-vices—provide training in conjunction with anumber of private providers, for example, reli-gious mission training centers, social institu-tions and local and international NGOs.30 In1999 an independent secretariat called Techni-cal, Entrepreneurial, Vocational Education andTraining Authority (TEVETA) was established.The main aim of TEVETA is to link public sec-tor initiatives more closely with the private sec-tor. More details about Technical and Voca-tional Training programs can be found also inAnnex 2.12.
Traditional public technical and vocationaltraining in Malawi consist mainly of two types:an apprenticeship training system; or full-timeinstitutional training. The training programs
only enrolled 1,500 students up to 2000, andbetween 2000–2003 a total of 1,723 males and883 females graduated. The typical duration ofa formal program is four years.
Private training providers are active in avariety of areas, particularly in commercial butalso in technical fields, and the training pro-grams consist of short and long-term, full-timeand part-time courses. Trainees pay full fees socourses are primarily attended by the moreaffluent school leavers or by employees in theformal sector whose fees may be covered infull, or partially, by the employers. The PRSPestimated a training capacity of 18,000 placeswithin the private training providers.
There are other non-formal training institu-tions; churches and welfare organizationsmanage many of these and they invariably tar-get school leavers. These institutions are fre-quently located in rural regions where studentshave few opportunities to enter further formaltraining. The traditional apprenticeship train-ing, referred to as ‘master-craft training’, ispossibly the most important sub-system interms of the numbers of trainee places theyprovide. The courses are completely self-organ-ized through on-the-job training and financingarrangements, and course duration varies fromtrade to trade and from employer to employer.
Notes1. University level education provides certifi-
cate, diploma, degree and Master’s level cours-es of 2 to 7 years duration.
Table 2.10: Secondary education teacher graduates, Unima and Domasi
Source: Basic Education Statistics for Unima. Document “Domasi—Capacity Building August 14, 2002” for Domasi. Note: Domasi had nograduates in 1998 because of the switch from a 2 year system to a 3 year system. Therefore the number of yearly graduates reduced starting1999, since the enrollment capacity remained the same. The program was modified because there was “a lack of adequate content knowledgeon behalf of the graduates … therefore lacking confidence.” There was also a switch from enrolling primary school teachers with at least 2years teaching experience to enrolling MSCE graduates with good grades but no teaching experience.
38 Cost, Financing and School Effectiveness of Education in Malawi
2. At the end of 2003 the latest availableschool statistics was the draft version of the2001 Basic Education Statistics. However, dueto difficulties with the data collection for sec-ondary and uncertainties with the subsequentestimation of enrollment in secondary, it wasdecided to use the 2000 enrollment in mostcases.
3. For secondary enrollment, the number isthe estimated enrollment (as found in BasicEducation Statistics 2000) and is again calcu-lated by imputing average enrollment numbers(averages calculated per type of school) for theschools that did not provide statistics—only 77percent of registered secondary schools provid-ed the required statistics.
4. Source: Economic Report, 2002. ThisMinistry also provides assistance to communi-ty childcare programs and approximately118,000 children participate in these pro-grams.
5. Noted in both the DHS 2000 and Ed Data2002 surveys.
6. The significant variance between the ageestimates of children in school from theschool census and household surveys alsomake the Net Enrollment Ratio (NER) anunreliable indicator if based solely on theschool census. The household surveys indicatean NER of 81 percent in 2002 (Ed Data), upfrom 78 percent in 2000 (DHS). When com-paring this to the GER level found (115% byEd Data), it indicates that for every 81 pupilsage 6–13 in primary, there are 34 pupils whoare either younger than age 6 or older thanage 13.
7. By using enrollment numbers from theschool census and the 1998 population censusdata, the GER is 132.6 percent and significant-ly higher than the results from any of the otherpossible sources. For instance, using householdsurveys over the last five years (IHS 1998, DHS2000, EdData 2002) gives a GER between 107percent and 120 percent.
8. First, the ratio is inflated where repetitionis common. Second, due to dropout enrollmentlevels tend to be higher in the lower grades andtherefore the ratio, by averaging enrollmentacross all grades, over-emphasizes enrollmentin the higher grades. Third, the same ratio candescribe two very different situations; one ofhigh initial entry and high dropout, and anoth-er of lower initial entry and lower dropout.
9. School census data are used for analysesof trends over time, because these are availablefor a longer period than the household surveys.
10. DHS 2000: Boys 40.2%; Girls 35.9%.Ed Data 2002: Boys 22.1%; Girls14.2%.
11. DHS 2000 registered an averagedropout rate for rural areas of 5 percent versus2 percent for urban areas while Ed Data 2002reported 9 percent rural versus 3 percenturban. While dropout in lower primary amonggirls and boys is approximately the same(3.6% girls, 3.9% boys), the picture is quitedifferent for upper primary (9.2% girls, 6.8%boys)—this suggests that the pressure in muchgreater on girls to drop out.
12. The PCR is calculated as the number ofchildren successfully completing a cycleexpressed as a percentage of the number ofchildren of the corresponding age cohort. Forthe entire Malawi primary cycle, this is bestcalculated by the PSLCE passers divided by thepopulation aged 13 years.
13. A school is considered ‘long established’if the year of establishment was before “2000minus number of available grades minus 5”; orif the year of establishment was not given inthe dataset (here 291 schools did not have ayear of establishment).
14. In reality, a number of primary schoolteacher training entrants enroll with only theJCE as their highest level of qualification eventhough official government policy insists theMSCE is a prerequisite.
15. The DECs originally existed to providesecondary education using distance education
Enrollment Patterns 39
modalities, i.e. with learners’ reading materi-als printed by the MCDE center and with asmall number of teachers at these centers guid-ing learners and occasionally grading theirwork.
16. The household surveys recorded similarlevels; the IHS 1998 finding reported GER atapproximately 27% and the NER at 7%, whilethe Ed Data 2002 found respectively 27% and9%.
17. For GER calculations the correspondingpopulation is 14–17 (Form 1–2 with age14–15, Form 3–4 with age 16–17).
18. In 2000 only 77% of the schoolsresponded to the data gathering questionnaireand many publicly funded schools did not pro-vide any data. As such, the actually countedtotal enrollment was only 164,459. The num-ber used, here, is the one Basic Education Sta-tistics 2000 estimates as the enrollment byimputing enrollment numbers for the missingschools based upon the average enrollment forthat type of school.
19. MoEST only includes registered schools.20. The rationale for establishing PRISAM
in 2000 was “to promote and improve privateeducation services in Malawi and safeguardthe interests of all those concerned with theprovision.” The key objectives are: (i)improve the quality of education service inprivate schools (e.g. assist in teacher training,conduct inspections, etc.); (ii) act as a coordi-nating body for the efficient and effectiveoperation of private schools; (iii) control andregulate the establishment and operations ofprivate schools (e.g. facilitate registration ofschools with MoEST and the Malawi Nation-al Examination Board to ensure minimumstandards are adhered to); (iv) assist inacquiring donor and government finance (e.g.‘soft’ loans for infrastructure improvements);(v) safeguard private schools against counter-productive government legislation and regula-tions.
21. It is 3.1% in Form 2 and 1.5% in Form3. However, Form 2 ends with a formal exam-ination to decide who progresses to Form 3.
22. Based on school census enrollment, DHS2000 repetition, UN-EFA population. Usingschool census enrollment and repetition, andNSO population, survival is 67%, but that fig-ure disregards the practice of secondary repeti-tion. However, if only DHS 2000 data is usedthe figure is 54%.
23. Many Malawians anecdotally refer tothe JCE as the “Joker Certificate”. This indi-cates the decreasing value of the qualificationand its inability to provide the level of skills themarket demands. However, its existence raisesan additional question: if conducting thisexamination is expensive and disruptive to thesystem as a whole, is there any merit in contin-uing with it?
24. Teacher:pupil ratio increased from 1:84in 1991/92 and 1:78 in 1992/93 to 1:108 in1994/95. Source: Basic Education Statistics,various years.
25. MoEST increasingly prefers the term‘under trained’ since the majority are trainedprimary teachers.
26. MIITEP is a 2-year course, which com-bines college and field based support andallows multiple cohorts of 3,000 to 3,500 perannum use the facilities of the six colleges.Theoretically up to three cohorts could gradu-ate from the program each year but, to date, ithas not succeeded in generating this volume fora myriad of reasons.
27. Based on an estimated pass rate of 80percent.
28. Domasi supplies roughly 150, Chancel-lor College, 100–150, Mzuzu University 20(but expected to increase to 100) and theAfrican Bible College 15). The Polytechnic andthe Banda Agriculture Faculty at Unima do notspecifically train teachers about 20 and 15graduates respectively join the teaching forceeach year from these two institutions.
40 Cost, Financing and School Effectiveness of Education in Malawi
29. It is a distance learning program of threeyears duration and presently three cohorts of300 are enrolled. There are also plans to con-tinue with some additional form of distancelearning program at Domasi in the future butonce the current untrained backlog at CDSSs iseliminated. The stated objective of the SSTEP
program is to enroll approximately 300 MSCEgraduates each year to train as secondaryteachers.
30. See Promotion of non-formal TechnicalEntrepreneurial Vocational Education Trainingcomponents in Malawi.by TEVETA (no refer-ence year).
CHAPTER 3
Education Expenditures and Financing
he preceding chapters raised concernsabout the efficiency and effectivenessof the education system. This chapterupdates and supplements the data
and analyses that have been presented in priorreports on education financing in Malawi. Themain ones referred to are: (i) the educationchapter of the Public Expenditure Review of theGovernment of Malawi (MOFEP 2001); and (ii)the Policy and Investment Framework for theEducation Sector (MOE 2000). The chapterbegins with a brief review of the budgetary sys-tem and reporting concepts and then providesan analysis of the trends in budgetary expendi-tures on education and broad sub-sectoral allo-cations. This is followed by a detailed analysisof the components of recurrent expenditures,the trends in unit costs and decomposition ofthe structure of unit costs. The economic com-position of developmental expenditures and thevolume and composition of external donorfinancing, both through and outside the budget,are presented next, together with a discussion ofthe implications of these trends for the sustain-ability of investments in the sector. Finally,household level expenditures at the primarylevel are discussed.
Education in Malawi is financed by the gov-ernment, external donors and households and,
as such, a complete picture of educationfinancing requires data from all three sources.At the moment, data from the three sources iseither incomplete or not up to date. Accuratedata on budgetary expenditures are availablebut there is a delay of two or three years. Alarge part of the financing provided by externaldonors is off budget and hence not readilyavailable. Details of household educationexpenditures are available but only for the pri-mary level for the year 2001. Therefore, theanalysis of education financing and expendi-tures has to be pieced together from differentsources of variable quality and some issues pre-sented in this chapter might require furtherinvestigation.
The budgetary system in Malawi
The government budget captures public expen-ditures for the education sector under therecurrent budget and the development budget.The recurrent budget comprises expendituresthat are financed by tax revenues, non-tax rev-enues and grants, while the development budg-et comprises spending under multilateral loansand government’s local contribution. Expendi-tures under the development budget are most-
41
T
42 Cost, Financing and School Effectiveness of Education in Malawi
ly capital expenditures but some recurrentexpenditure are also included in external proj-ects, which may need to be subsumed in theregular recurrent budget after the project peri-od (for instance, salaries of project administra-tive staff or the cost of textbooks). Therefore,unit recurrent costs based on the recurrentbudget may result in an underestimate of thetrue costs of maintaining the education system.
More importantly, the development budgetdoes not capture grants from bilateral donors.In 2000/01, these off-budget grants accountedfor about 70 percent of total developmentexpenditures. A detailed breakdown of theseexpenditures, by economic categories, is notreadily available.
The data on budgetary expenditures mustalso be interpreted with caution because of thedifferences between approved, revised budgetsand actual expenditures that spans over a 2–3year period for the same fiscal year. Budgetaryinstability, associated with high rates of infla-tion and depreciation of the Malawi Kwacha,together with limited budget managementcapacity, contribute to substantial discrepan-cies between these estimates.
Finally, aggregate annual expenditures donot indicate the real difficulties of providingstable financing for effective service deliveryand financing of critical inputs during theschool year. Budgetary instability in allocationsand in actual releases to the Ministry is partlyassociated with periodic natural shocks(droughts, floods), which reduce agriculturalproduction and hence revenues, while raisingdemands for expenditure for relief.1
External agencies contribute about 90 per-cent of the resources for the developmentbudget (about 95 percent of total on- and off-budget development expenditure) and aboutone third of the education budget as a whole.While budgetary instability has been a chronicfeature, the suspension of foreign grant moneyand loans (in 1992 and 20002) have furtheradded to the volatility of expenditures in thesector.
The budget provides public resources to theMOEST, which oversees primary and second-ary education, as well as non-universityteacher training colleges.3 The subventedorganizations receive funds directly from theMinistry of Finance (MOF).4
Overall budgetary expenditure trendsin the education sector
As stated in Chapter 1, real recurrent expendi-tures in the education sector have risen gradu-ally between 1993/94 and 2001/02, while realannual development expenditures approxi-mately halved over the same period, perhapsdue to more off-budget development expendi-ture. Total real educational expenditures, asshown in Figure 3.1 below, have remainedlargely at the same level.
However, there have been considerableannual fluctuations in real recurrent expendi-tures. From 2001/02, recurrent expenditureshave increased significantly, and though offi-cial figures are not available yet, it is expectedthat the higher level of recurrent spending oneducation has been maintained the last coupleof years. The share of MOEST in total recur-rent education expenditures has been in therange of 72–80 percent. As can be seen fromFigure 3.2, the growth in real recurrent expen-ditures has been mostly attributable to theexpenditures of MOEST; those of subventedorganizations have shown very modest growth.
The real growth in recurrent expendituresfor MOEST has largely been driven by theincrease in personal emoluments as a result ofthe increase in the number of teachers after theintroduction of FPE. The increase in realexpenditure on non-salary expenditures hadbeen modest up to 1999–2000 (and thereafteronly unreliable estimates are available). Expen-ditures on other inputs required to improveeducation quality have not kept pace.As shownin Figure 3.4 below, recurrent expenditures bysubvented organizations (mainly universities
and colleges) have, on average, increased overthe past five years, despite a decline during twoyears. In the preceding period, between1993/94 and 1996/97, their funding haddeclined steadily. Not surprisingly, the overallgrowth over the last decade has been compar-atively lower for the subvented institutions(universities) than for basic education sector.As will be discussed in more depth in chapter7, real expenditures on tertiary institutionshave driven this growth. The actual (real)
expenditures on other subvented organizationshave remained very low in absolute terms.
Development expenditures of the MOEST,as shown in Figure 3.5 below, comprising theoverwhelming share of the developmentbudget for education, have declined sharplybetween 1993/94 and 1999/2000—mainly asa result of the decline in external funding.Development expenditures for subventedorganizations have stagnated at very lowlevels.
Education Expenditures and Financing 43
0
100
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1993
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1997
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-00
2000
-01
2001
/02
2002
/03
Mill
ions
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Development
Total
Figure 3.1: Real recurrent and development expenditures, 1993-2003 (millions of kwacha)
Source: Authors’ calculations, using PER and GOMM budget data.
0
100
200
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1993
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Mill
ions
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Figure 3.2: Real recurrent expenditures: MOEST and subvented organizations
Source: Authors’ calculations, using PER and GOPM budget data.
44 Cost, Financing and School Effectiveness of Education in Malawi
Sub-sectoral allocations
Allocations for primary education have com-prised the largest share of recurrent expendi-tures on education, and, until the last fewyears, the overwhelming share of developmentexpenditures (See Annex 3.2). The share allo-cated to primary education of total recurrentexpenditures rose from 50 percent in 1993/94to approximately 60 percent in 1995/96. Allo-
cations to secondary education, which fluctu-ated around 10 percent between 1993/94 and1998/99, have increased to about 15 percent.
Three other features of the sub-sectoral allo-cations of recurrent expenditures need to behighlighted. First, the allocation for tertiaryeducation is substantially higher than that forsecondary education, although the latter servesa much larger number of students (about 70times more students). Second, the overall sub-
050
100150200250300350400450
1993-94
1994-95
1995-96
1996-97
1997-98
1998-99*
1999-00
2000-01
MOESTrecurrentMOESTSalaryNon-salary
Figure 3.3: MOEST recurrent expenditures in real terms
Source: Authors’ calculations, using PER and GOPM budget data.
020406080
100120140
1993
-94
1994
-95
1995
-96
1996
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-99*
1999
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/02
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Mill
ions
Subvented recurrent Tertiary Subvented other
Figure 3.4: Real recurrent expenditures of subvented organizations
Source: Authors’ calculations, using PER and GOPM budget data.
Education Expenditures and Financing 45
sectoral share for secondary disguises the verylow share for CDSSs compared to the relative-ly high share for CSSs—as mentioned in theprevious chapter. The result is a severe under-funding of general secondary education. Third,the share for teacher education is 3 percent orless, raising the question of whether allocationsto teacher education are consistent with thegovernment priority of improving the qualityof teachers. This is particularly relevantbecause it has been claimed that budget short-falls were the main reason for recruiting onlyone cohort of teachers to the TTCs each yearbetween 1999 and 2001, when MIITEP wasoriginally intended to facilitate at least twocohorts per year.
The analysis of development expenditure isstrongly influenced by the separation of on-budget and off-budget spending since the shareof off budget is substantially larger—althoughit is difficult to obtain complete information onthis. However, a review of the on-budget devel-opment expenditure by sub-sector indicatesthat allocations, within the developmental on-budget expenditures, were concentrated up to1998/99 on primary education. In recent years,however, the level has dramatically shiftedtowards secondary education. As will be
shown later, changes in on-budget spending area result of complementarities with the sub-sec-toral off-budget spending by external agencies’spending, as well as a result of changing prior-ities over time (both for the donors and thegovernment).
Composition of recurrent expenditures
The breakdown, or functional composition ofrecurrent expenditures, indicates what theseexpenditures financed. The share of expendi-tures allocated to personal emoluments is high-est in primary by a wide margin, fluctuatingbetween 86–91 percent between 1993/94 and1999/00. This high share of emoluments hasfueled the growth in overall MOEST salaryexpenditures. In the other sub-sectors, theshare of emoluments is surprisingly low; it isgenerally less than 50 percent of total recurrentexpenditures. The share of non-personnelexpenditure has been rising in all sub-sectorsother than primary.
While overall non-personnel expenditures(ORT) have risen only modestly in real terms,the sub-sectoral trends in these expendituresrequire further analysis. First, in primary edu-
0
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ions
MOEST Development Subvented - develpment
Figure 3.5: Real development expenditures
Source: Authors’ calculations, using PER and GOPM budget data.
46 Cost, Financing and School Effectiveness of Education in Malawi
cation the share of ORT seems too low, andwithin this category, the share of expendituresfor teaching and learning (T&L) materials hasbeen 5 percent or less.5 The scarce non-salaryexpenditures also cover items such as funeralcosts and the travel of civil servants. In somereported cases, the entire ORT has been usedto cover funeral costs that arise fromHIV/AIDS related deaths. Second, in all theother sub-sectors, the share of ORT is relative-ly high and constitutes a rising share of totalrecurrent expenditures. A detailed breakdownof these expenditures shows that, historically,the largest share accrues to either boarding6 oran ambiguous “others” category. The share forteaching and learning materials rangedbetween 5–7 percent in most sub-sectors,except in tertiary education where it reached11 percent. The “others” category includesmainly travel allowances (the government hasone of the highest travel budgets as a share ofGDP in the world).7
Trends in unit public expenditures
Following the enormous increase in enroll-ment after 1994, real unit expendituresdeclined in primary education due to theinsufficient number of teachers and the subse-quent rise in PTR. With the hiring of manyuntrained teachers, this situation was rapidlyaltered and since 1997/98 real recurrent
spending per pupil has more or less returnedto pre-FPE levels.8
In secondary education as a whole, per pupilexpenditure has decreased dramatically. Thesub-sector has seen enormous increases inenrollment at CDSSs, but with little additionalresources allocated. Spending per pupil hasalso declined slightly for CSSs as enrollmenthas increased. Additionally, in recent yearsthere has been a gradual shift from boarding today schooling, and cost sharing was intro-duced at the remaining boarding schools.Overall real spending per pupil in 1999/00 wasless than half of what it was in 1993/94. ForTTCs the drastic fall in real unit cost is at leastpartially a result of a change in the delivery sys-tem from the traditional pre-service system tothe MIITEP program.9 As such, this is anexample of improving resource efficiency.
At university level, the real unit cost hasincreased over the same period. A comparisonof the averages for the past three years(98/99–00/01) versus that of the first threeyears (93/94–95/96) shows per pupil spendinghas increased more than 20 percent. The over-all trend of rising real unit costs at the tertiarylevel is in marked contrast to the trends inother sub-sectors and will be discussed in moredetail later in the study.
The per pupil spending as a multiple of theunit cost of a primary student in Table 3.3,reflects the vast disparities in the level of serv-ice provision and funding. For instance, each
Table 3.1: Share of personal emoluments in recurrent expenditures
Source: Authors’ calculations, using PER and GOPM budget data.Notes: Secondary Education is very difficult to estimate because of the duality of the CSS system versus the MCDE/CDSS system. The P.E.calculations, here, exclude the expenditure for MCDE (since it was easily separated). However, from the time nearly all of MCDE was transferredinto CDSSs in 1997/98) the expenditure on CDSSs has been captured directly within the standard secondary education expenditure and this is theexpenditure reflected here. However, to further complicate matters, it may be that salaries for at least some of the teachers at CDSSs – sincethey are trained primary and not secondary school teachers – are captured under primary expenditure and not under secondary expenditure.
Education Expenditures and Financing 47
year students in CSSs receive about 10 timesthe public aid that primary students do. Includ-ing the CDSSs, however, this ratio is closer to5, indicating the low level of resource provi-sion in CDSSs. The discrepancy in the level offunding of CDSSs and CSSs needs to beaddressed if the quality is to improve. Thesewide differentials in quality representinequitable use of resources—especially as ahigher proportion of the poorer studentsattend CDSSs.
On a per student basis, secondary and terti-ary education are undoubtedly always moreexpensive than primary. However, the ratiosfound in Malawi for CSS, and especially foruniversities, are well beyond any rational basisin terms of quality norms, as can also be seenfrom comparative data in Annex 3.3. At thetertiary level, a student receives 300 timesmore resources than those allocated to a pri-mary student (2000/01).10
Another measurement is the unit cost, orspending per pupil, as a share of annual percapita income of Malawi, as shown in Table
3.3, below. At the primary level, the annualcurrent public expenditure on each studentrepresents a mere 5 percent of annual per capi-ta income, which would undoubtedly need tobe raised if quality is to improve. Averageexpenditure per secondary student is about 21percent of per capita income11 and a universi-ty student receives about 10 to 15 times the percapita income.
Annex 3.3 shows the ratios in comparisonto other developing countries and indicatesthat while Anglophone countries have higherratios than other regions, none approach thedisparity in per pupil expenditures apparent inMalawi. In Malawi the absolute level of perpupil expenditures is actually low at all levelsexcept for tertiary (see Annex 3.4). At the pri-mary level the annual recurrent expenditurewas only US$14 in 1999/2000, compared toUS$3712 in Sub-Saharan African countries. Bycontrast, the annual expenditure on tertiaryeducation has been largely within theUS$2,500–3,000 per student range and witheven higher levels during peak years.
Table 3.2: Per pupil annual recurrent expenditure (in 1993/94 kwacha)
Sources: PER for data until 1998/99. For 1999/00 primarily from Basic Education Statistics. For 2000/01 from ‘Consolidated annual appropriationaccounts’.
Table 3.3: Unit costs for a year of education, by level of education, 2000/01
Recur. Expend. Unit cost As multiple As prop of 2000/01 (MK ‘000) Public enroll in MK of GDP/cap spending in prim
Source: Authors’ calculations, using 2000/01 actual expenditure data.
48 Cost, Financing and School Effectiveness of Education in Malawi
Decomposition of public unit costs in 2000/01
Expenditure per student is a measure of thepublic resources that, on average, a countrydevotes annually to each student’s education.To understand when an increase or decrease isan improvement in efficiency, it is important tounderstand the composition, or breakdown, ofthe unit cost. In particular, the variations in therelative price of the main inputs (e.g. teachers’salaries) and the quantity of inputs devoted toeducation (teachers and non-teaching staff perpupil or learning materials per pupil) affect theper student expenditures.13
In Table 3.4, the factors explaining the sig-nificant difference between primary and uni-versity unit costs are: (i) the very lowpupil–teacher ratio at tertiary level; (ii) a simi-larly low pupil–other staff ratio; and (iii) a highlevel of spending on “other recurrent” costs.The differential in average teacher salariesacross the sub-sectors is not a significant con-tributing factor in explaining the differentialsin unit costs. The primary student equivalentof tertiary education non-salary expendituresin 2000/01 was 347 times that of non-salaryspending in primary education. In contrast, theratio of average teacher salary to the averageuniversity salary was only 4 times. Thepupil–teacher ratio at the university level isalmost one-tenth of that in the primary sub-sectors. The differential in the ratio of pupils toother staff between the two sub-sectors is enor-
mous. Spending on teaching and learningmaterials and other expenses per pupil isapproximately 50 and 540 times higher,respectively, at the tertiary level than at theprimary level.
At the primary level, unit public recurrentcosts represented only 4 percent of per capitaincome. Average teachers’ salaries are about4.5 times per capita GDP, slightly higher thanthe 3.5–3.8 multiples of per capita GDP inmany other Sub-Saharan countries. Most ofthese other Sub-Saharan countries, however,have higher GDPs per capita, so the currentsalary level for primary teachers’ may well beappropriate for Malawi14 The low public unitcost results from the very high pupil–teacherratios—relative to international standards—and from the negligible spending on recurrentitems such as teaching and learning materials.
In summary, the differences in teachers’remuneration across sub-sectors do notaccount for the huge disparities in unit costs.The high differentials are more directly linkedto the differences in organization of servicedelivery and spending on non-salary expendi-tures. In secondary education, an increase inpublic spending on CDSSs has to be consid-ered. At the tertiary level, the fixed costs of thesystem, relative to the limited total studentpopulation, need to be addressed. While somerestructuring of PTRs to eliminate gross ineffi-ciencies (for example, courses with lowdemand) is required, the overall issue is to raisethe scale of operation. A strategic question for
Table 3.4: Decomposition of public unit costs, 2000/01
Secondary- Teacher Primary conventional education University
Pupil–Teacher ratio 66 23 41 7Teacher average salary (USD) 872 1522 2511 3843Pupils per Other staff 1943 65 38 6Per pupil spending on T&L materials (USD) 1.9 6.0 0.0 93.8Per pupil spending on Other (USD) 2.7 29.2 682.1 1439.5Memo: Teachers’ salary as a multiple
of per capita income 5.95 10.39 17.15 24.71
Source: Authors’ calculations using 2000/01 actual expenditures.
Education Expenditures and Financing 49
Malawi is how to reorient higher educationand expand access, thereby reducing unit cost,while keeping total recurrent public cost fromrising significantly. As will be shown in Chap-ter 7, there should be scope for increasing thenumber of university graduates without over-supplying the job market. A recent tracer studyindicated that university graduates quickly findformal employment jobs, thus suggesting thatdemand still outruns supply.
Trends in sub-sectoral emoluments
This section examines possible reasons for thedecline, or stagnation, of real unit recurrentcosts in primary, secondary and teacher train-ing—interestingly, these costs have tended torise for tertiary education. The focus is onemoluments, or salary expenditures. Non-salary expenditures, or ORT expenditures, areclassified under the broad and somewhatambiguous category of “other”. Presentaccounting systems and the lack of consistencyin data entry make further analysis of this cat-egory difficult. However, as ORT expendituresconstitute more than 50 percent of total recur-rent expenditure at post-primary levels, theearlier analysis of the impact of ORT spendingis a better predictor to explain differencesbetween the sectors. Here, too, further analysisof these expenditures would be beneficial andpossibly contribute to improved resource uti-lization.
In recent years, total real emoluments haveincreased in only the primary sub-sector; in allother sub-sectors real emoluments haveremained largely unchanged. To estimate aver-
age emoluments per staff, data on the numberof staff are required. In the secondary sector itis difficult to estimate staff numbers due tolack of transparency in the data on staff levels,particularly at the CDSSs. A lot of teachersteaching at CDSSs are primary school teacherswho are often still registered, and paid, as ifthey were teaching in primary schools. Obvi-ously this distorts staff numbers at both pri-mary and secondary levels. There has not beensufficient clarity by the central administrationtoward the divisions and lower levels on howexactly to handle this consistently.
Table 3.5 indicates that per person staffemoluments in the primary and tertiary sectorsdeclined in real terms during the nineties. Inthe primary sector, average salary expenseswere 20 percent lower in 1999/00 relative to1993/94. This decline in real average emolu-ments does not necessarily indicate that theteachers’ salary levels have declined; it is due inpart to the hiring of a large number ofuntrained teachers but at lower salary levels.As such, when these teachers receive trainingand achieve the same salary scales as theirtrained counterparts, average emoluments perteacher are expected to rise (discussed furtherin Chapter 8).
In the tertiary sector the decline in averagereal emoluments per staff has been even moresignificant: between 1993/94 and 1999/00 itfell by approximately 50 percent. As before,these figures do not imply that the salary levelof existing tertiary level teachers have neces-sarily declined; rather they indicate that therehas been an increase in the number of staff atlower salary levels, including both teachingand non-teaching staff.
Table 3.5: Average emoluments per staff (in 1993/94 kwacha)
Source: PER and authors’ calculations. Note: In Primary nearly all staff are teachers, whereas in tertiary this is not the case.
50 Cost, Financing and School Effectiveness of Education in Malawi
Table 3.6 shows that it is mainly the growthin teacher numbers at both the primary andtertiary level that has contributed to theabsolute growth in personnel costs; it is notdue to an increase in salary levels. In the caseof the primary sector, there was an addition of20,000 teachers between 1993/94 and1999/2000, but since enrollment has increasedrapidly due to FPE, the PTR declined onlyfrom 68 to 61. In the tertiary sector, there wasa similar percentage increase in the teachingstaff (75 percent) but since enrollments actual-ly declined over the period, the PTR went from12:1 to 6:1. This trend in the tertiary sectorindicates a decline in efficiency.
Development expenditures
Composition
On-budget development expenditures consistprimarily of investment, or capital, expendi-tures. Between 1993/94 and 1999/00, con-struction or civil works has typically absorbedapproximately 60 percent of all developmentspending; furniture another 5 percent; rehabil-itation about 4 percent, pedagogical materialsaccounted for 9 percent (but varied between 1to 25 percent), training allocations requiredabout 6 percent (but varied between 3 to 11percent), and ‘other’ absorbed 19 percent.15
Overall, the share of development expendituresin the total education budget is approximately25–30 percent annually.
Donor financing and extra budgetarygrants
Donors play a critical role in the education sec-tor. They contribute in the region of 80–90 per-cent of funds in the development budget. Theyalso contribute extra-budgetary grants thatamount to approximately double of the devel-opment budget for 1999/00 and 2000/01 (seeAnnex 3.5). In total, roughly 95 percent oftotal sector development expenditures arefinanced externally while the remaining 5 per-cent of domestic financing comprises govern-ment’s counterpart funding. As such, donorprojects and programs determine the nature ofeducational sector development and influencecosts, efficiency and future recurrent expendi-ture requirements.
Since data on extra-budgetary grants arenot regularly compiled, or universal in theircoverage, it is not possible to say whethertotal, or sub-sectoral allocations, are in linewith policy priorities. However, the partialdata available do clearly indicate that sub-sectoral allocations for off-budget grantassistance still strongly favor primary educa-tion, in contrast to the high share of second-ary in the development budget. Therefore,the estimate is that about 40 percent of totaldevelopmental expenditures (including off-budget) go to primary, compared with 35percent to secondary. This is considerablydifferent to the distribution by sub-sector, asdiscussed earlier, of total expenditures foreducation.
Table 3.6: Growth of teaching staff and pupil–teacher ratios
Although precise estimates of extra-budget-ary donor financing cannot be derived, someindication of the magnitude in specific areascan be gauged from the following data: totalannual average donor expenditure (both on-and off-budget) was approximately US$37 mil-lion at the end of the nineties. Projected expen-ditures by the main donors during the period2001–2007 are given in Annex 3.6.
Government is reliant on a wide range ofdonors and organizations, and this makes sec-tor planning, increased efficiency and equitableallocation of resources difficult. First, donorfinancing of education has been, and remains,volatile. Second, external financing is the pri-mary determinant of the level and compositionof non-salary operating expenditures (such astextbooks and teaching-learning materials) andthese would normally be financed under thepublic recurrent budget. The volatility andunpredictability of these funds not only affectsplanning but also impinges on measures toimprove quality. Third, since much of the exter-nal financing is off-budget, the recurrent costimplications of these projects are not explicitlytaken into account during the design phase andthis, in turn, affects the sustainability of projectinterventions if, and when, external assistanceceases. Fourth, although donor coordination isamicable it remains minimal and there is a needfor greater coordination and coherence toensure that overall sub-sectoral goals will beachieved in a cost-effective manner. Two exam-ples of the problems arising from extra-budget-ary funding and uncoordinated donor financingare highlighted in Annex 3.7.
Household financing
Despite low household incomes, Malawianhouseholds continue to bear a considerableshare of both the recurrent and capital costs ofprimary education. At the higher levels of edu-cation, household contributions are likely to begreater in absolute terms but lower in relative
terms. This is because access to the upper lev-els of education is highly inequitable and large-ly benefits the higher income quintiles. In thefollowing section the characteristics of house-hold spending at the primary level areexplored.
As much as 83% of parents of primarypupils in public school paid for one or moretypes of school supplies during the year 2001.The majority of families reported paying fortextbooks and uniforms and approximatelyhalf reported contributing to the school devel-opment fund, which finances maintenance.Surprisingly, the average household expendi-ture for public primary school was almost ashigh (80%) as the per pupil public expendi-ture. As Table 3.7 shows, the household expen-ditures for primary education are also regres-sive with the lowest quintile paying more inabsolute terms than the richer income groups(with the exception of the wealthiest quintile);hence they were paying disproportionatelymore as a percentage of their total householdexpenditures. Equally striking is the rapid risein annual expenses within each standard: rela-tive to Standard 1, students in Standard 3 incur50 percent more expenses, students in Stan-dard 4 spend 2.4 times more and Standard 6pupils spend 4.7 times more than Standard 1pupils.16
This high level of household expenditure forprimary school is a possible explanatory factorof student dropout in primary. A comparisonof household and public expenditures in Stan-dard 1 is particularly instructive. The extraor-dinarily high PTR of about 100 to 1 effective-ly means that per pupil public expenditure isabout 40–50 percent below the average for theprimary cycle. At this grade level, householdexpenditures actually exceed public expendi-tures. This finding is inconsistent with the prin-ciple of pro-poor spending which ideallyshould ensure that the largest subsidies benefitthe poorest groups.
A comparison of household monetary con-tributions for primary schools shows that both
52 Cost, Financing and School Effectiveness of Education in Malawi
the poorer and the rural Malawian householdcontribute a larger share of their incomes thanin some of the neighboring countries (Annex3.8). For example, in Malawi, the poorestquintile of households contributes 5–6 percentof its income for education and the richestquintile contributes only 1 percent whereas incountries like Uganda, Zambia and Kenya thepoorest only contribute half the above amount.
These direct monetary contributions shouldbe added to the indirect, or non-monetary/in-kind contributions (such as materials andlabor) made by the poorer households—espe-cially in the rural areas. Within the last year, 72percent of rural households, in comparison to25 percent of urban households, contributedlabor to primary schools. In addition, 20 per-cent of rural households also contributedmaterials relative to only 6 percent in urbanareas. Again, the poorest sector carried thelargest burden with 77 percent of the poorerhouseholds contributing labor versus 40 per-cent for the highest quintile.
The current high levels of poverty, the sus-ceptibility of agricultural and rural incomes toclimatic shocks and poor terms of trade, andthe relatively high dependence on householdfinancing all result in greater instability. Thisparticularly impacts the financing of criticalteaching and learning materials, school repairsand construction costs. Instability in thefinancing of the education system impacts neg-atively on quality and on children’s progressthrough the system. It also compounds thelater problem of inefficiency in public resourceuse through high repetition and excessivedropout rates.
Notes1. A particular issue at present (2003) is the
cash budget system, introduced in 1996 as ashort-term stabilization measure to restore fis-cal balance. This has resulted in unplanned andexogenous cuts in discretionary spending.Monthly expenditure allocations to line min-
Table 3.7: Annual household expenditures on primary education, 2001
Mean annual per pupil hh expenditure Kwacha US$ As % of per pupil public exp
Public schools 761 10.1 80Private schools 3600 48.0
Mean annual per pupil hh expenditure—public schools
Source: Ed Data of 2002.Note: Exchange Rate 72.1 Kwacha to 1 USD.
Education Expenditures and Financing 53
istries depend on actual cash revenues and for-eign loan inflows during the month—after tak-ing into account non-discretionary expenditureon interest payments. Because of delays in therelease of funds by external agencies (as havebeen the case over the past years in the absenceof an IMF program) there are often cash man-agement problems and delays in releases toimplementing Ministries.
2. After about a two-year delay a new IMFPRGF program was approved in October2003.
3. The principal subvented organizations arethe tertiary institutions, notably University ofMalawi and Mzuzu University. Other subvent-ed organizations comprise the Malawi Nation-al Examination Board (MANEB), MalawiInstitute of Education (MIE), Malawi Nation-al Library Services (MNLS) and MalawiNational Commission for UNESCO
4. The normal budgetary process is that theMinistry of Education, Science and Technologyand educational subvented organizations pres-ent forward estimates to the Ministry ofFinance (MoF), which then approves the budg-et based on estimates of the total resourceenvelope. Revised estimates of expenditure arepresented at the end of the fiscal year, but actu-al expenditures are only available a couple ofyears later, after it has been reviewed by theauditor general. Hence, data for the mostrecent years are usually approved or revisedestimates, which may be above or below theactual expenditures. While revised estimatestend to be higher than the approved amounts,actual expenditures usually lie (but not always)in-between the forward estimate and therevised estimate.
5. It is important also to mention that after1998/99 with the new cost center basedaccounting structure it has become almostimpossible to calculate breakdowns to moredetail than simply P.E. versus ORT for all ofthe education levels. This is partially due to thefact that the more elaborate budgeting toolsare not always used consistently among the dif-
ferent divisions (cost centers). The last clearORT breakdown in T&L and other categoriestherefore also dates from 1998/99.
6. It is stated GOM policy to increase costsharing with students on items such as board-ing and feeding at secondary level and particu-larly at university level. In practice, no drasticchanges have occurred at the university level,mostly because it is the Education Act thatforesees boarding provision at tertiary level,thereby contributing to the very high publicunit cost at this level and at the same time pro-hibiting real chances to significantly increaseenrollment. At secondary level, however,boarding expenditure should have diminisheddrastically in the last year or so, as one of theHIPC triggers is to shift the burden of board-ing to the households and free up much need-ed resources, for the CDSSs, for example. Theactual expenditure for the most recent yearshould therefore begin to reflect this change.
7. The question is whether such a highexpenditure is justified. One possible explana-tion is that these expenditures are partly ameans to supplement staff emoluments. How-ever, without a more detailed breakdown ofthis category; one that would require piecingtogether this type of expenditure from the bot-tom up (since it is not immediately available inMOEST statistics, it is not possible to explainthe increases in expenditure. The currentaccounting system should theoretically allowdetailed analysis, but the low level of consis-tency in the use of the different categories byinadequately trained staff at the divisions andheadquarters, have rather achieved the oppo-site in making even basic analysis more diffi-cult. Therefore this kind of exercise is alsobeyond the scope of the present study.
8. While average PTRs were maintained,despite increased enrollment, this hides the factthat PTRs are very different between urbanand rural areas and between lower and highergrades. Also hidden is the fact that the rapidexpansion of the primary enrollment resultedin the employment of many unqualified teach-
54 Cost, Financing and School Effectiveness of Education in Malawi
ers, so that the PqTR increased dramatically.These issues are addressed in more detail else-where in the study.
9. Although it is clear that the unit cost forteacher training has been significantly reduced,the exact extent is difficult to establish becausein recent years the MIITEP program (with the-oretically 2 cohorts per year graduating where-as in the pre-service system half of one cohortwould graduate per year) has not been runningup to its maximum capacity. As such, there arequite wide fluctuations in number of graduatesand in the ensuing unit cost by year.
10. This disparity may be explained by sub-stantial inefficiencies at the tertiary level.
11. These ratios would need further adjust-ment because the expenditure figures excludeadministration at the division level. Adminis-tration disproportionately benefits the conven-tional secondary schools.
12. Bruns et al. 2002. This study finds thatthe non-weighted average of non-teachersalary recurrent spending in 33 African coun-tries is US$9 and represents 24.1% of the totalrecurrent spending. Thus the average totalrecurrent spending would be 9*100/24.1, orUS$37.4
13. In analyzing the breakdown of unit costin general the following key components wereconsidered: (i) average teacher salary, (ii)pupil-teacher ratio, (iii) average other staffsalary, (iv) pupil-other staff ratio, (v) perpupil spending on teaching-learning materi-als, (vi) per pupil spending on other operatingexpenses (including for example pedagogicalsupport and travel); and (vii) per pupil spend-ing on social welfare and boarding. InMalawi, however, the data for the last twocomponents are not disaggregated and so thelast two items covering travel, grants andboarding will constitute “other recurrentexpenditures”.
14. Bruns et all. 2002.15. Clearly, some expenditures in the
development budget could be classified asrecurrent expenditures, but they are includedin the former because they are financed bydonors and form part of the public invest-ment plan—these include project staff salaryexpenditures, textbooks and rehabilitation ofschools.
16. However, since these data include someprivate school children, they should be inter-preted with caution.
CHAPTER 4
Internal Efficiency and ManagementEffectiveness in Resource Utilization
his chapter further explores efficien-cy and management issues in thedelivery of education. In a countrylike Malawi, where resources are
scarce, it is a priority to ensure that availableresources are used optimally if the desiredobjectives are to be achieved. As such, thechapter examines the relationship betweeninputs into the education system and studentoutcomes as measured by the level of gradeattainment. It will also identify resourcewastage resulting from the high repetition andpupil dropout rates and inequities in the allo-cation of teachers.
The efficiency analysis will reflect differentperspectives and include analysis at the nation-al, division, district and school levels. The dis-cussion will examine how effectively inputs aretranslated into pupils who complete the coursecycle, or pass the final exam, and examine ifthe same amount of inputs could produce addi-tional graduates. The issue of learning out-comes will be explored in Chapter 5.
Efficiency in student flow in primaryand secondary education
Index of efficiency and schooling yearsto produce a graduate
The sudden expansion in the system in 1994allowed most children to gain access to educa-tion. This expansion, however, was notmatched with the additional trained teachersor the essential teaching and learning materialsneeded to assure quality. As a result, the lowerstandards are characterized by large class sizestaught by mostly untrained teachers teachingin bleak environments, often under a tree.1
This has contributed to high repetition anddropout rates and has resulted in the wastageof a significant share of the resources allocatedto the education sector.
The magnitude of the waste and inefficiencyis reflected in Table 4.1. It shows that with thecurrent level of repetition and dropout in thesystem, the government pays for 20 school
55
T
56 Cost, Financing and School Effectiveness of Education in Malawi
years in order to get one child to graduate fromprimary instead of the normal 8 school years.This is also reflected in the so-called ‘index ofefficiency’, which for Malawi is 39.7 percent.This figure indicates that 60.3 percent of thepublic resources are used either on childrenwho drop out before finishing primary,2 or onrepetition years (both of those who eventuallyfinish and those who do not3 and are also lostto the system). In comparison, similar data forMozambique4 indicate that 30 percent areused either on children who dropout or on rep-etition years, which is only half the level ofMalawi. Paradoxically, this wastage may bedue to insufficient spending on primary educa-tion (e.g. qualified teacher, appropriate PTR,sufficient T&L materials, adequate infrastruc-ture, etc.), as reflected by the low unit cost forprimary school in Malawi. Put another way,quality education probably requires a certainunit cost per child per year.
The table also shows that if the current levelof repetition is maintained, and assuming no
student drops out, the index of efficiencywould be as high as 81%; thus wastage lessthan 20%. In the same way, assuming no stu-dent needs to repeat and the current dropoutrates are maintained, then half (50 percent) ofthe resources would be wasted. Clearly, highdropout rates have the greatest adverse affecton the efficiency of the system and, as such,any planned policy interventions would main-ly need to target a reduction in dropout rates.However, since repetition and dropout are pos-itively correlated, reductions in repetition willhave a positive effect on dropout rates (seeAnnex 4.1 for a more detailed discussion).
Internal efficiency in secondary is signifi-cantly better than in primary but, nevertheless,inefficiencies still exist. At the secondary level,a little less than one-quarter of public resourcesare wasted due to repetition and dropout: itrequires 5.2 school years instead of 4 to pro-duce a graduate. Also, inefficiencies resultingfrom repetition alone are low, consumingabout 5 percent of the public resources. Ineffi-ciencies are substantially higher as a result ofdropout only and consume close to one fifth ofthe available public resources.7 This positivepicture probably results from the rigorousselection process. However, as will be madeclear, there are significant differences betweenthe various types of secondary schools.
At first glance, repetition may appear to notmake a difference from government’s perspec-tive since the cost of one teacher is the same,whether s(he) teaches ten or a hundred pupils.However, if a genuine effort is made to deployteachers to roughly achieve the prescribed 60:1PTR, then the total number of teachers required(and thus their cost) is much higher if there aremore repeaters. Alternatively, if teachers are notdeployed based upon numbers of children in aclass due to repetition, then repetition obvious-ly will have an impact on pedagogical practicesand student learning due to overcrowding. Thiscreates a vicious circle: students repeat partiallyas a result of very high PTRs, and the PTRsremain high because of the repetition. To lower
Table 4.1: Index of efficiency in the different cycles ofstudy, 1999/00
Primary Secondary
Total Total
Index of overall efficiency5
Percent 39.7 76.8Numbers of years necessary to
have 1 graduate from primary 20.1 5.2Index of efficiency if the system would not have dropouts, i.e. the only source of inefficiency are repeatersPercent 80 95Numbers of years necessary
to complete 10.0 4.2Index of efficiency without repeaters, i.e. the only source of inefficiency are DropoutsPercent 50 81Numbers of years necessary
to complete 16.06 4.9
Source: School Survey Data in Basic Education Stats 1999 and 2000,and repetition rates from DHS2000 final report for primary and fromDHS2000 dataset with authors’ calculations for secondary.
Internal Efficiency and Management Effectiveness in Resource Utilization 57
the PTRs to the recommended PIF levels, andwithout reducing the repetition rate, moreteachers would be required than without any,or with limited, repetition. For instance, if it isassumed that in primary there is a total enroll-ment of 3 million pupils and a repetition rate of25 percent and MK 1000 (about US$10) isspent on a child annually then total spending ofMK750 million extra is required to achieve thesame PTR as in a scenario without repetition.In other words, a reduction of one percentagepoint in the repetition rate will generate savingsequivalent MK30 million (about US$300,000)per year.
Teacher deployment
The quality of an education system is generallyassociated with the supply of teachers in theschools, particularly qualified teachers. Sinceteachers’ salaries in primary school constitutethe lion’s share of expenses—both as a share ofunit cost and total public expenditures—teacherdeployment is closely associated with unit costper pupil or school, and therefore with the equi-table distribution of funding. It is important,therefore, to explore how teachers are allocatedat the division, district and school level.
The distribution of teachers is generallybased on the targeted PTR, one that is deemed
effective for teaching and learning. A furtherimportant aspect is the qualifications andexperience of teachers: unequal deployment, orthe deployment of untrained and inexperiencedteachers, can lead to poor student outcomes,which in turn contribute to both higherdropout and repetition rates and to lower sur-vival rates.
An important aspect of teacher distributionis associated with the formulation of clear cri-teria for providing schools of similar enroll-ment size with a comparable number of teach-ers.8 The task, therefore, is to document towhat extent current teacher allocations inMalawi are consistent with this principle.9
As such, the following analysis examines theextent that this principle holds true by formal-ly estimating the average relationship betweenthe number of teachers and the number ofpupils at the school level by using a regressionanalysis. The result indicates the degree thatschools deviate from the average relation-ship.10 This technique is applied for the coun-try as a whole, but separate data on the differ-ent divisions/districts and urban/rural areas areprovided.
Primary school level
Figure 4.1 visualizes the regression results forall public primary schools in Malawi. It clear-
0
10
20
30
40
50
0 500 1000 1500 2000 2500
Number of pupils
Num
ber o
f tea
cher
s
Figure 4.1: Teachers allocation in publicly funded primary schools
Source: Authors’ calculations, using EMIS 200011
58 Cost, Financing and School Effectiveness of Education in Malawi
ly indicates that not all schools are on thestraight line (each dot represents a school);rather there is a significant spread that corre-sponds to an R-square value of 66 percent, orto 34 percent ‘randomness’—this means thatthis part of the variation in teacher deploymentis not explained simply by difference in thenumber of pupils in the schools but by otherfactors.12 For instance, schools with 1000pupils can have anywhere between 5 and 40teachers and, similarly, schools with 40 teach-ers have enrollments varying between 500 and3800. There are a number of schools that areextremely far removed from the norm, whereimmediate action is most urgent.13
Figure 4.2 puts this 34 percent ‘randomness’in perspective by comparing Malawi to a num-ber of African countries based on this indica-tor. The average for the sample of countries is25 percent; as such, Malawi is clearly amongthe countries with a more arbitrary teacherdeployment system. This indicator also indi-cates that there are significant opportunitiesfor immediate improvements.
To further identify where management prob-lems might exist, it is possible to assess theextent to which the degree of randomness is a
result of variance, either between the divisions(i.e. some divisions over endowed in compari-son to others), or somewhere at a lower level inthe system. For this, a set of dummy variablesfor the different divisions in the regressionmodel is used. By doing this, differencesbetween the new ‘randomness in teacherdeployment’ (33.6 percent=100–66.4) and theone noted earlier (34.1 percent), provides anindication of the variability that is explainedby differences in allocations to different divi-sions (see Table 4.2). Since this difference isquite small, it is possible to state that teacherdeployment between divisions is equitablesince none appears strongly favored, or disfa-vored. This suggests that allocation of teachersby the Ministry Headquarters to divisions isfairly equitable, but that allocations withindivision and districts may not be. Table 4.2also shows the average school size and theaverage number of teachers in each division.The national average school size is 671 pupils,with slightly less than 11 teachers.14
To further analyze the degree of inconsisten-cy in allocating teachers within the divisions, aregression was run for various subsets ofschools across each of the six divisions. In
0
10
20
30
40
50
60Sao Tome
GuineaMoza
mbiqueNiger
NamibiaGuinea-B
issau
ChadSenegal
Mauritania
ZambiaRwandaGabon
Burkina Fa
soMadagasc
arEthiopia
MalawiUganda
BeninCameroon
MaliTogo
Countries
% R
ando
mne
ss
Côte d'Ivoire
Figure 4.2: Comparison of degree of randomness in teachers allocation to individual primary schools for selectedSub-Saharan African countries
Source: Mingat, 2003.
Internal Efficiency and Management Effectiveness in Resource Utilization 59
Table 4.3, below, the column ‘Degree of ran-domness’ indicates the variability establishedby the regression for each of the division sub-sets. The degree of inconsistency differs sub-stantially from one division to another.
It is also possible to simulate what would bethe average number of teachers in schools of agiven size in each of the divisions. In Table 4.3,column one provides the results of these simu-lations for schools of 671 pupils, which is theaverage size of the primary schools in Malawi.The average number of teachers in an averagesize school ranges from 9.4 teachers (SouthEastern division) to 11.9 teachers (Northerndivision).
The difference between both sets of ran-domness values in Table 4.3, above, providesan indication of the consistency of teacherdeployment in each division across their
respective districts. In those divisions that lacka main urban area (Central East and ShireHighlands) it is clear that no district appears tobe strongly favored, or disadvantaged. Howev-er, divisions with a clear urban center present aradically different picture. The current teacherhuman resource management system signifi-cantly favors urban areas in districts where thedivision has a major urban center.
Further analysis for the subset of schools ineach district provides additional informationon teacher deployment to individual schoolswithin individual districts. The results of thisanalysis (see Annex 4.2) point to a wide varia-tion in teacher deployment among the districts,and indicate a need to evaluate teacher deploy-ment at the district level.
Large differences in PTRs exist betweenurban and rural districts (see Annex 4.2). The
Table 4.2: The relationship between the number of teachers and pupils in public or subvented primary schools,1999/00
Pupils TeachersDivisions Total / Avg. per school Total / Avg. per school Coefficient
Regression values between brackets are not significant at the 5% level.
Table 4.3: Regression results with and without using district dummy variables within each of the division subsets
Number of teachers Degree of randomness Percent difference in average school Degree of with dummy variables between degree of
Division (671 pupils) randomness for districts randomness
Central East 10.6 49.4 49.2 0.4%Central West (with Lilongwe) 10.9 39.5 29.7 24.8%Northern (with Mzuzu) 11.9 30.7 24.8 19.2%South East (with Zomba) 9.4 36.1 30.7 15.0%South West (with Blantyre) 11.1 17.3 13.8 20.2%Shire Highlands 9.8 41.6 40.2 3.4%
Source: Authors’ calculations using EMIS 2000 data.
60 Cost, Financing and School Effectiveness of Education in Malawi
average PTR in 2000 was 1:63, a figure closeto the PIF objective of 1:60. However, in allurban centers, the PTR falls below this target.On the other hand, the ratios in rural districts,such as Mangochi (82:1), Phalombe, Chik-wawa, Machinga (75:1), Lilongwe Rural-East,Dedza (72:1) and Ntcheu, Thyolo, Mulanje(71:1) are far removed from the policy target.
A review of the deployment of qualifiedteachers clarifies the situation even more. Theaverage pupil-to-qualified teacher ratio (PqTR)is enormously high at 123:1. The geographicdiscrepancies are clear: urban areas maintain a60:1 ratio of qualified teachers, but rural areasare severely deprived of sufficient qualifiedteachers (PqTR is close to 200:1 for LilongweRural East, Mangochi, and Phalombe). Ifexpressed as a percentage of qualified teachers(of the total teaching staff) urban areas have arelatively high proportion of qualified teachers:it is 70 percent in Mzuzu; 87 percent inZomba; 70 percent in Blantyre, and 58 percentin Lilongwe. The percent of qualified teachers
varies in the rural districts, ranging from 39percent to 53 percent. In addition, the propor-tion of female teachers in urban centers (73–87percent) is much higher than in rural areas(19–48 percent).
Table 4.4 illustrates that schools in urban dis-tricts are appreciably larger (about 3 times) thanin rural districts. The urban institutions alsohave larger class size than their rural counter-parts, even though they have much lower PTRs.This results from the dubious practice of urbanschools employing almost two teachers for eachstream of pupils—this practice is inappropriate-ly referred to as ‘team teaching’. In effect, itinvariably results in one teacher being presentwith all the entire group of children whilehis/her colleague is involved in some other activ-ity, or is absent altogether.16 So although urbanareas have a liberal supply of teachers and arewell below the target PTR, these deploymentpractices result in classes being even larger, onaverage, than in rural areas.
There are also notable differences in thePTRs by grade,17 ranging from extremely highlevels in the lowest grades to quite low levels inthe highest grades (Table 4.5). One possibleexplanation for this may be that following theintroduction of FPE, the redeployment ofteachers from the higher standards to the lowerstandards has been limited, even though it is inthese lower grades that the new influx of chil-dren has occurred. The higher grades havelower PTRs because a high percentage of thechildren drop out before reaching the highergrades. Another contributing factor is the con-tinuing use of ‘specialized’ teachers for thehigher standards; they frequently teach onlycertain subjects and consequently these indi-viduals having abundant ‘free time’.
Table 4.4: Efficiency ratios by rural and urban districts,1999
Efficiency Ratio Urban Rural Total
Pupils per teacher 45 66 63Pupils per qualified teacher 66 129 118Pupils per stream 86 70 72Pupils per stream (std 1–2) 100 93 n.a.Pupils per stream (std 3–7) 82 60 n.a.Pupils per stream (std 8) 74 44 n.a.Pupils per school 1,865 606 646Pupils per classroom 144 92 96
Teachers per stream 1.94 1.06 1.13Teachers per school 42 9 10Teachers per classroom 3.24 1.40 1.51
Source: PER (MOFEP 2001)
Table 4.5: Pupil teacher ratios, standard 1 — 8, 2000
Std 1 Std 2 Std 3 Std 4 Std 5 Std 6 Std 7 Std 8
100 76 64 52 45 39 33 28
Source: EMIS 2000
Internal Efficiency and Management Effectiveness in Resource Utilization 61
Deployment process in primary
The current deployment process (discussed indepth in Annex 4.3) is clearly flawed. A moreequitable distribution of teachers requiresimmediate consideration but this will necessar-ily take time because of the difficulties associ-ated with redeploying teachers who are in —for them — comfortable positions, but whichare not equitable nor efficient for the educationsystem as a whole. However, the large numbersof teachers that need to be recruited into thesystem over the next few years provides a win-dow of opportunity to bring about some of therequired changes.
A more effective budget mechanism candeter unplanned teacher movement. However,to encourage teachers to move to areas whereshortages are endemic, such a budget systemneeds to be complemented by incentives, andby insurances for teachers to not be ‘stuck’their whole careers in undesirable locations.
Possible incentives might include a combina-tion of the following: more speedy promotionopportunities for teachers working in lessdesired areas; higher rates of leave accumula-tion; larger and more regular annual incre-ments; hardship allowances that reflect the dif-ficulties of the place of employment; freehousing and utilities; higher transportallowances to facilitate more frequent travel tocenters; etc. At the same time extreme cautionis required to establish mechanisms wherebythe additional benefits are only given to theteacher as long as (s)he serves in a hardshiparea. In other words, a hardship bonus shouldnot follow the teacher once (s)he relocates to anon-hardship posting. Another option wouldbe to require new graduates to serve a numberof years in a rural area, as some sort of reim-bursement for the training received.
The myriad of inconsistencies in teacherdeployment practices in many Malawianschools make it clear that the establishment ofan equitable policy on teacher utilization willnot, in itself, provide a magical panacea to
remediate the present anomalies. However, therecently established decentralization policyprovides a great opportunity to improve thesituation, by giving districts greater freedom tohire and pay teachers, and by supplying themwith financial resources based upon a neutralformula using the number of pupils with someadjustment criteria for poverty level or popula-tion density. As a result, rural districts shouldbe able to advertise open posts as soon as ateacher leaves.
Secondary schools
Figure 4.3 shows the distribution of teachers inpublic secondary schools18. In these schools,average size is 233 pupils while the averagenumber of teachers is 8.9. The teacher deploy-ment is even more unequal than in primary, asthe R-square in the regression analysis explain-ing the number of teachers in a school by thenumber of students is only 41%, leaving asmuch as 59% of the variation unexplained.There are also some secondary schools withextreme differences to the norm, which mayneed immediate action to adjust the number ofteachers.
When examining the PTRs and PqTRs at thesecondary level, it is clear there are strong dif-ferences between rural and urban areas. Forexample, in 199919 the PTR and PqTR inurban areas were respectively 28:1 and 59:1whereas these indicators for rural areas were36:1 and 131:1.
In the publicly funded secondary school cat-egory, three main types of schools are found.The CDSSs are acknowledged to be perform-ing under difficult circumstances, relative toCSSs and grant aided schools. For an averagesize secondary school (approximately 233), aCDSS has roughly 4 teachers less, while grantaided schools have about 1.8 teachers morethan government day and boarding schools.21
Teachers’ qualifications are equally impor-tant in determining pupil performance. Thevast majority of CDSSs are staffed with trained
62 Cost, Financing and School Effectiveness of Education in Malawi
primary teachers who are generally lacking inknowledge of subject content, but they are alsooften uncomfortable teaching at secondarylevel. Figure 4.4 clearly illustrates the radicaldifference between the various types of second-ary schools.
Notes1. In general, the higher standards in
Malawi are allocated classrooms whendemand does not match supply.
2. Pupils may of course have received somebenefit from their time at school. However, the
assumption here is that the goal is to producechildren with at least primary education com-pletion. Another more valid argument mightbe that completing 8 grades is more than isrequired to achieve full literacy—and it can beseen a self-standing achievement of the educa-tion system. However, typically 5–6 years ofquality education are perceived necessary toreach this level and more than half of thedropouts do not achieve either.
3. Note: because repetition rates are used instandard 8, the effect of having to pass the pri-mary leaving exam to graduate from primary istaken into consideration.
0
5
10
15
20
25
30
0 100 200 300 400 500 600 700 800
Number of pupils
Num
ber o
f tea
cher
s
Figure 4.3: Teacher allocation in all CSS, CDSS, and grant-aided secondary schools
Source: Authors’ calculations using EMIS 2000.20
0%
20%
40%
60%
80%
100%
1999 2000 2001
CSS (including grant aided) %unqual Priv %unqual CDSS %unqual night %unqua
Figure 4.4: Percentage of qualified teachers in different types of secondary schools
Source: Basic Education Statistics, 1999-2001
Internal Efficiency and Management Effectiveness in Resource Utilization 63
4. Mozambique: Cost and Financing of Edu-cation, World Bank, July 2003.
5. Calculated with the Quasi-time-seriesestimate for the survival rate, using years1998/99 and 1999/00.
6. This means that even if there was no rep-etition, on average 16 years of schooling arerequired to produce 1 primary school graduatebecause for each child that completes primary,there are 2 who completed 4 grades only andthen dropped out.
7. This includes those pupils who sitthrough the 4 forms, but who never pass theMSCE exam. Even though they finished thesame number of grades as MSCE passers, theiremployment opportunities and especiallyexpected salary levels are substantially lower(Kadzamira E.C. 2003).
8. An exception to this rule might be in thecase of very small schools in remote areaswhere the student catchment area does nothave enough children to achieve the PTR poli-cy aim—even when incorporating multigradeteaching.
9. For example, an average PTR of 60:1—asprescribed in PIF for primary schools—can beachieved in an equitable manner and with thesame PTR nearly everywhere throughout thesystem. However, it may also result from verydifferent PTRs, with some far above and oth-ers far below the average.
10. Schools for which the number of teach-ers exceed the expected value based on the sizeof their enrollment are over-endowed, andvice-versa
11. Subset of 4384 schools with valid com-binations of teachers and pupils, and not beingprivate schools, are used out of a total of 4647schools in EMIS 2000.
12. It is appropriate to use the [100%—Rsquare], to obtain an aggregate quantitativeindicator of the degree of inconsistency or ran-domness in teacher deployment. If the value ofR square is 0, it implies the absence of any sta-tistical relationship between the two variables(i.e. complete inconsistency in teachers’ alloca-
tion). If instead, R square is 100%, it indicatesthat there is a perfect consistency and that thenumber of teachers in any school is exactlywhat would be anticipated on the basis of thenumber of students enrolled. This can be pre-sented by a straight line graph, as shown in fig-ure 4.1. In the case of primary schools inMalawi, a school of 500 pupils would alwayshave 8 teachers and a school with 1000 pupilswould always have 16 teachers.
13. Some examples of these are: (i) 20schools have a PTR of less than 40, with someless than 10, while on the other end of thespectrum, there are 10 schools with a PTR ofmore than 80—it actually goes as high as aPTR of 200; (ii) 15 very large schools havingmore than 4,000 pupils, up to a maximum of8,600 pupils; (iii) schools with more than 100teachers, combined with a low PTR of 25 or37; etc. However, these schools do not repre-sent the average teacher deployment situationin the country and so, to clarify the situation,schools with more than 60 teachers and/ormore than 2,500 pupils are not included in Fig-ure 4.1.
14. The fact that the Northern region has onaverage fewer teachers per school than ShireHighlands, does not automatically mean theyare under endowed with teachers since theyalso have the smallest average schools. Theseaverage school sizes and average numbers ofteachers in each school, of themselves, do notgive an indication on the equity of teacherdeployment!
15. Based on 4383 out of a total of 4647listed schools with valid data.
16. The practice is also frequently accompa-nied by subject specialization.
17. If teachers are registered as teaching inmore than 1 grade, then they are added to thegroup of teachers for each category.
18. It is important to note that in secondaryschools a significant number of students attendprivate schools—official statistics indicateapproximately 10%. However, there are also anumber of non-registered private schools for
64 Cost, Financing and School Effectiveness of Education in Malawi
which no statistics are available so, here, thepercentage might be higher. However, since thegovernment has no direct influence on teacherdeployment practices, these are not included inthis analysis. The grant-aided schools, howev-er, are included because their teachers are fullyfunded by government.
19. MOFEP, 2001.20. 593 schools with valid data were used
and this represents 138152 students. However,in the Basic Educ. Stats the total ESTIMATEDenrollment is 274949, i.e. including thoseschools that did not provide data and the pri-vate schools that are not included here. Thesample does include 31 schools that do notprovide data on student numbers but havebetween 1 and 20 teachers.
21. When running a regression thatincludes dummy variables for the type of sec-ondary school, the degree of randomnessdecreases from 59 percent to 52 percent(100–48.2)—or by about 12.2 percent. Thisindicates that a part of the variability isexplained by the over-endowment of certaintypes of schools versus others (see Table 4.7).The coefficients show that in comparison tothe reference government day and boardingschool, the grant aided schools fair favorably,whereas the CDSSs have fewer teachers for agiven number of students.
22. For 2001, the Draft Basic Education Sta-tistics is used.
arlier chapters examined aspects of theMalawian education sub-sectors andcritiqued the degrees of efficiency withwhich they succeed in progressing stu-
dents through the system. However, it is alsonecessary to review how effectively studentslearn. This section provides this informationand is based, mainly, on EMIS data, nationalexamination data and internationally compa-rable standardized surveys of levels of achieve-ment in basic skills in primary standards(Monitoring Learning Achievement (MLA)and Southern African Consortium for Moni-toring Educational Quality (SACMEQ). Thesection uses a cross-country perspective todetail student achievement levels and discussesthe correlation between schooling characteris-tics and learning outcomes. The chapterincludes a discussion of malnutrition, whichhas been consistently documented as a factoraffecting children’s attendance and ability tolearn effectively.
Level of learning
The many challenges facing the primary educa-tion system in Malawi combine to produce aless than conducive learning environment for
its pupils. For example, SACMEQ1 examinedlevels of English literacy achievement in Stan-dard 6 (or its equivalent grades) in severalcountries in the region.2 In Malawi, less thanone percent of all measured pupils reached the‘desirable’ mastery level in literacy, while 21.6percent reached the ‘minimum’ mastery level.
The results show further that the most sig-nificant differences are between children inlarge towns and the rest of the country, andacross socio-economic levels (see Annex 5.1).Some small differences also exist between (i)the wealthiest children versus children of allother socio-economic categories and (ii) chil-dren from rural areas/small towns versus thosefrom urban areas.3 There is also a small gendergap—the girls performed less well than theboys. Poor rural girls not only constitute thegroup most at risk of dropping out beforeachieving primary completion (see equity chap-ter), but they are also least likely to achieve sat-isfactory learning outcomes if they do manageto stay in school.
Compared with the SACMEQ test scores ofsix other countries from Eastern and SouthernAfrica, Malawi had the lowest percentage ofpupils meeting the minimum and desirablemastery levels of reading literacy (see Figure5.1).
CHAPTER 5
School Effectiveness, Malnutrition and Learning Outcomes
65
E
66 Cost, Financing and School Effectiveness of Education in Malawi
A separate UNESCO study, MonitoringLearning Achievement (MLA, 1999), meas-ured fourth-graders’ scores in life skills, litera-cy and numeracy and compared a number ofcountries (See Table 5.1).
Table 5.1 reveals that Malawi’s overall per-formance is roughly comparable to the othercountries surveyed, although it has the lowestliteracy rate. In numeracy, Malawi also rankedat the lower end. Interestingly, Malawi’s per-formance in Life Skills is superior to all thecountries in the study and this may proveimportant in trying to implement strategies to
improve health and reduce the prevalence ofHIV/AIDS.
The level of English used in the literacy andnumeracy tests may have contributed toMalawi’s low scores. In contrast, the Life Skillstest uses more simple English statements andalso includes drawings. Another contributingfactor could be that the Life Skills test assessesmore general knowledge that children acquireoutside school, while the numeracy and litera-cy tests measure skills specifically achievablethrough effective teaching in schools. Finally,the above results add fuel to the current debate
64.8
56.4
46.1
25.9 25.821.623.4
37
26.7
5.27.6
2.30.6
52.8
0
10
20
30
40
50
60
70
Kenya
Zimbabwe
Mauritius
Zanzibar
Namibia
Zambia
Malawi
Scor
es % Minimum
Desirable
Figure 5.1: SACMEQ test score, Southern and Eastern Africa
School Effectiveness, Malnutrition and Learning Outcomes 67
on the important role of local language in ini-tial learning achievement and suggests that fullimplementation of the existing national lan-guage policy4 is likely to contribute toimproved learning outcomes.
The MLA study also provides disaggregateddata by gender, urban/rural, and type of school(public/private). The average test score for allareas (literacy, numeracy, Life Skills) shows aless than significant 3.3 percentage point dif-ference in favor of boys. Differences betweenurban and rural students are also modest; thereis a 2.2 percentage point difference in favor ofurban schools and this is one of the lowest forthe countries sampled. However, the differ-ences between private schools and publicschools are more pronounced with 6.2 per-centage points in favor of private schools (8percentage points for literacy alone).5 This dif-ference is approximately in the mid-range, rel-ative to other countries.
The learning environment in primaryschools
In addition to looking at test scores, it is alsonecessary to understand characteristics of thelearning environment. This section highlights anumber of issues that are considered germaneto the learning process.6
School and home environment
Children in Standard 6 were greatly over-aged,a finding that confirms issues raised in the pre-vious analysis on primary enrollment. Theaverage age was slightly over 15 years whereas
the expected age range would be 11 to 12years; there were also wide age ranges whichwould make effective instruction difficult.
The Standard 6 classroom environmentswere generally exceedingly bleak. The mostbasic piece of equipment, such as a usablechalkboard, was missing in 14 percent of theclassrooms. Only 35 percent of pupils had adesk to sit at and a mere 29 percent of pupilshad writing places; less than half of the class-rooms had a teacher’s chair and table; only halfof the classes had an English dictionary; butother essential learning materials, such asmaps, were even more infrequent. In addition,a mere 24 percent of Standard 6 pupils were inclassrooms that contained library books whileonly 26 percent of schools had a school library.
Textbooks were also in short supply. Overone-third of Standard 6 pupils did not have anEnglish textbook. Overall, EMIS 2001 findsthe following pupil to textbook ratio for threemajor subjects (Table 5.2).
The situation should have changed drastical-ly since then, as CIDA provided a total of 11million textbooks distributed to all primaryschools between the end of 2001 and June2002. Unfortunately, no EMIS statistics after2001 were available at the time of this report.Going forward, the government will need toensure regular textbook provision as part ofthe primary education sector budget, orthrough long-term donor commitment.
About one-quarter of teachers reportednever having met the parents/guardians of apupil during an academic year, varying some-what across divisions. Sixty-three percent ofparents/guardians noted the existence of a PTAat the school their children were attending,
Table 5.2: Students per textbook in primary, by standard
68 Cost, Financing and School Effectiveness of Education in Malawi
while 96 percent of respondents said that therewas a school committee.7 Eighty percent ofparents who stated that there was a schoolcommittee indicated that it was doing a goodjob; 11 percent said it was not; and 8 percenteither had no opinion or did not answer thequestion. Ninety-five percent of respondentsindicated their belief that schools should teachmore practical skills than done at present.
The Ed Data survey revealed that onlyslightly more than half of the children sur-veyed, aged 6–14 years, live with both of theirbiological parents. Twenty-two percent livedwith their mother (but not with their father), 2percent lived with their father (but not withtheir mother), and 22 percent lived with nei-ther of their natural parents, although not allof these were orphans. In brief, around one infive children have lost one or both parents.
Other factors influencing schooleffectiveness
Table 5.3 summarizes time children spend onschool-related activities in an average schoolday.8 This time includes time spent traveling toand from school; time spent in classes and
after-class study sessions; and time spent onextracurricular activities.
It is apparent that the time spent on schoolactivities increases through the standards.Children in Standards 1 and 2 spend 5 hoursper day on school activities; those in standards3 and 4 spend 6 hours; and those in Standards5 through 7 spend 7 hours on school-relatedactivities. Only 2 percent of primary schoolpupils spend more than 8 hours on school-related activities. There is virtually no differ-ence in the time spent on schooling by sex, byurban-rural residence, by region, or relative towealth.
While the percentage of pupils doing home-work outside of school increases through thestandards, the amount of time spent per weekon homework outside school varies little; itranges from approximately 2 hours in thelower standards to 3 hours in the higher stan-dards. Most striking are the differences bywealth, with 38 percent of pupils in the highestquintile and 24 percent of pupils in the lowestquintile doing homework outside of schoolhours.
On average, pupils who were absent fromschool missed a total of 17 days during the
Table 5.3: Time spent on school and homework in primary by grade
Average number of hours on school-related activities 4.8 5.0 5.8 5.9 6.7 6.9 7.1 (7.1)
Percentage who do not have homework during the week 92 84 66 52 33 28 15 (5)
Average hours spent on homework per week outside school 1.7 1.9 1.6 2.2 2.4 2.8 3.0 (3.2)
Source: Ed Data 2002. Note: For Std. 8 these results are based on a sample of less than 50 pupils and, as such, are less reliable.
Table 5.4: Number of school days missed by primary school children during the 2001 school year
Lowest Highest Urban Rural Public Private quintile quintile Total
Days absent 12 17 17 12 19 12 16.7
Source: Ed Data 2002. Note: only asked to pupils who were absent at least one day during the year. However these represent 97 percent of total.
School Effectiveness, Malnutrition and Learning Outcomes 69
year. Pupils in rural areas were slightly morelikely than those in urban areas to have missedschool at least once, and they missed moredays of school (17 rural versus 12 urban daysmissed). Children from households in the high-est quintile missed fewer days than those fromhouseholds in the lowest quintile (12 days ver-sus 19 days). The SACMEQ study shows thatone quarter of the Standard 6 pupils wereabsent on the day of testing.
In the Ed Data study, the reasons given byparents for the absenteeism of their childrenduring the previous school year were: illness—86 percent, funeral—61 percent,9 did not wantto go—39 percent, school clothes dirty—34percent, too hungry—28 percent (29 percentrural, 18 percent urban), any type of work—12.5 percent, no money for fees—10 percent.
Teacher absenteeism in Malawi is reportedas chronic. The main reasons suggested for thishigh level of teacher absenteeism was atten-dance at the funerals of colleagues or beingbusy on errands, such as collecting salaries orexamination correction payments. In someschools, teacher time-on-task was as low as1–2 hours each day. Anecdotal evidence sug-gests that absenteeism is high also among dis-trict, division and Ministry staff. In summary,it is apparent that there is a breakdown in insti-tutional accountability and that this is linkedto the failure to provide appropriate incentivesto perform assigned duties.
Teacher Mobility. While teacher absenteeismcontributes significantly to interruptions in theteaching and learning processes, a related diffi-culty is causing additional disruptions, namely,the degree of teacher mobility. For example, astudy in 2000 by the Improving EducationalQuality (IEQ) Project (in partnership with theMalawi Institute of Education)10 indicated thatmany teachers do not remain with the samestandard for a reasonable length of time. Forexample, by October of the school yearapproximately 50 percent of the 188 teacherssurveyed were no longer teaching the class theyhad commenced with in February of the same
year. This disturbing trend is at variance withthe continuity children need if they are toacquire basic literacy and numeracy skills.
Curriculum
The nature, scope and relevance of the schoolcurriculum also significantly impacts schooleffectiveness. In the following section, the pri-mary and secondary curricula are brieflyreviewed.
Primary Curriculum. Recently, a PrimaryCurriculum and Assessment Reform (PCAR)document has been drafted and is expected tobe presented to Cabinet for formal approvalshortly. This revised curriculum will: (i)address the ‘crowded’ subject range; (ii) high-light child-centered, more effective teachingstrategies; (iii) increase awareness ofHIV/AIDS; (iv) promote heightened genderconsciousness; and (v) provide an increased,and necessary, emphasis on ‘mother’ tongueinstruction.11 The draft curriculum advocatesthree groupings for the entire primary stan-dards: Infant, Middle Primary and Upper Pri-mary, and suggests organizing core subjectsaround these groupings. The curriculumreform also intends to develop resource mate-rials to support teaching within each group.Finally, an Assessment and Training Module,already available, will assist teachers to imple-ment the recommended continuous assessmentpractices.
A detailed plan for the introduction andevaluation of the new primary curriculum isnow required. This plan should: (i) indicate thelikely training required for existing TTC tutorsand for practicing teachers; (ii) outline themanner in which newly qualified teachers willbe aligned with the new curriculum; (iii) reviewdeployment practices to ensure they are consis-tent with local language instructional require-ments; and (iv) agree community and teachersensitization programs to clarify the impor-tance of local language to achieve positivelearning outcomes.
70 Cost, Financing and School Effectiveness of Education in Malawi
Secondary Curriculum. A revised secondarycurriculum was introduced to Forms 1 and 2 in2000, and to Forms 3 and 4 in 2002. This revi-sion reduced the excessive number of subjectsto seven core subjects and approximately 14possible elective subjects. This ‘new’ curricu-lum, however, has been challenged, principallyby the universities. It is now necessary forMOEST to: (i) facilitate a review of the exist-ing document; (ii) decide on subsequentteacher in-service efforts; and (iii) to indicateplans for revising teacher training in the con-text of previous, and intended, changes to thedocument.
Teacher education programs have not beenfully responsive to changes in secondary schoolcurricula. Therefore, the National Strategy forTeacher Education (2002) advocates the needto review both curricula concurrently.
Impact on pupils and teachers ofHIV/AIDS
The HIV prevalence rate is estimated to bearound 20 percent in Malawi with severe con-sequences for the education system. Numerousstudies on the impact of HIV/AIDS have beenprepared and one study “The Impact ofHIV/AIDS on Primary and Secondary School-ing in Malawi: Developing a ComprehensiveStrategic Response”12 as described in Annex5.2, summarizes the results and impact onteachers over a 10-year period; both the directeffect from HIV/AIDS illness and loss of life,and its indirect negative impact on repetitionand dropout rates. Evidence from theHIV/AIDS pandemic in Uganda and Zambiasuggests that the population growth willdiminish due to many adults dying at an earlyage, but that the growth of school age popula-tion will decline only slightly. In those coun-tries, it is anticipated that the attrition rate dueto death from AIDS may increase as much as 3percentage points to around 8 percent in total.In order to make up for this higher attrition,government will need to train approximately
50% more teachers every year than in a situa-tion without death from AIDS. Assuming thatthis evidence is applicable to Malawi, this hasimportant implications for the development ofthe pre- and in-service teacher training sys-tems, and for the costs of teacher training. Inaddition, keeping the increasing number ofchildren who are orphaned in school mayrequire additional investment and supportstructure. Furthermore, the higher level ofteacher and student absenteeism because of ill-nesses and increasing opportunity costs willundoubtedly adversely affect teaching andlearning conditions for all students, and thereis evidence showing that absenteeism fromHIV/AIDS is a greater problem to the educa-tion system than the cost of additional teachertraining.
Prevalence and consequences ofmalnutrition affecting educationattendance and outcomes
Malawi has one of the highest levels of stunt-ing in children for all countries in eastern andsouthern SSA. The problem is associated withperiodic food shortages combined with poorchild caring practices and has led to almosthalf of the children under 3 years of age beingstunted (see Table 5.5). These high rates havepersisted in the last decade—even during timeswhen food supply has been adequate. Stuntingand micronutrient malnutrition are associatedwith delayed school enrollment; decreasedschool attendance,13 especially during thehunger period from November to April; andreduced capacity for adults to work andschool-age children to learn satisfactorily. Therecent food crisis has been extreme, and onethat affected most of the population. It is evi-dent that Malawi remains chronically foodinsecure because of food shortages in someareas and seasonal food shortages in most ofthe country. In this situation, young childrenare particularly at risk because they have thehighest nutritional requirements of any age
School Effectiveness, Malnutrition and Learning Outcomes 71
group and are dependent on others for theirfood and health care.
While rates of malnutrition in young chil-dren have been documented, less is knownabout the national prevalence of malnutritionin school-age children. From the Demographicand Health Survey (DHS) 2000, it is apparentthat many children are entering Standard 1either short or underweight for their age: 57.4percent of children 4–5 years of age are stunt-ed and an alarming 28 percent are severelystunted. These high levels of malnutritionreflect cumulative nutritional insult and a direnutritional situation, most of which occursbefore 3 years of age.14
National figures on malnutrition in adoles-cence (usually defined as ages 10–19 years) arelimited. In one study,15 prevalence of malnutri-tion was high in 10–14 year-olds. The 2000household survey shows that 17 percent ofwomen 15–19 years of age have low bodymass index (BMI<18.5); this is 2–3 times high-er than any other age group of reproductiveage women (20–49 years of age). However, onthe positive side, there is some possibility ofcatch-up growth in children who are stuntedduring early childhood.
In Malawi, the beginning of the school year(January) occurs during the hunger season,which has a profoundly negative effect on
enrollment, school attendance and dropoutrates. Families keep children out of school dur-ing this period so children can earn money tobuy food or look for food. In addition, hungerand fatigue are so severe that many children donot have enough energy to walk to school.
Anemia, caused by iron deficiency, is preva-lent throughout the country, as is Vitamin Adeficiency (VAD). AIDS is also a cause of mal-nutrition, anemia and other micronutrient defi-ciencies. Because diet is poor (both in quantityand quality), it is likely that school children areaffected by these deficiencies, and also defi-cient in a number of other micronutrients thataffect health and capacity to learn.
Malnutrition and increasing educationopportunity costs. From the above, it is clearthat the overall nutritional status of children inMalawi has an adverse effect on learning andraises opportunity costs during crisis periods.The nutritional status of school age children isa combination of the quality and quantity oftheir current food intake and also of their
Table 5.5: Percent of children 0–3 years of age withstunting in the Eastern and Southern Africa region
Source: National data from countries with available recentinformation for this age group. Note: Stunting means <–2 S.D. below the NCHS standard for heightfor age.
Box 5.1 The Impact of Stunting andUndernutrition on Education and Devel-opment:
In young children, malnutrition is associ-ated with half of all child deaths (Pelletier,1994), i.e. half of children who currentlydie from a childhood illness would not ifthey were well nourished. Stunted childrenare less likely to enroll in school at theappropriate age than children withoutstunting and have lower test scores inschool, particularly in mathematics(Drake, et. al., 2002). Physiologically,stunted individuals have less capacity towork than taller individuals. As a result oftheir reduced ability to work and impairedcognitive function, short individuals havelower earning potential than their tallercounterparts.
72 Cost, Financing and School Effectiveness of Education in Malawi
intake before they enter school, particularlybefore the age of two years. Lack of food,either seasonally or year round, and poor childfeeding practices are the major causes of mal-nutrition in the country. As such, ensuringgood nutrition and health in very young chil-dren is an investment in school children. Fur-thermore, programs that promote good healthand nutrition in school children are also need-ed and essential to maximize children’s abilityto learn while they are in school.
Lack of food has devastating effects on theenergy intakes of school children. According toone study, in non-crisis years energy intakes inschool children were only 74 percent of therecommended amounts (from Latham, et al.,1995), and presumably in crisis years thiswould decrease further. Morning hunger is a
recurrent problem in school children becausechildren are normally not fed breakfast andoften walk long distances to school and thisresults in their being unable to benefit from aday of learning. A 1995 report stated that“throughout Malawi’s three regions, teachersreported that between 50–90 percent of chil-dren come to school hungry” (Latham, et al.,1995).
During periods of food shortage, attendanceat primary school dropped dramatically (tozero in some schools) because children werekept home to look for food or they were tooweak to attend. A report for UNICEF (Gal-lagher, et al., 2002) indicates that attendancerates dropped off seriously between Novemberand April — the months prior to harvest, oftenreferred to as the hunger period. In Malawi,
Box 5.2: The Impact of Anemia, of Iodine Deficiency, and of Selected MicronutrientDeficiencies on Education and Development:
Iron deficiency anemia (IDA) in children (particularly <2 years) has irreversible negative con-sequences on learning in older children, even when IDA is corrected later in life (Booth andAukett, 1997). Lower test scores are associated with anemia (Drake, et al., 2002). A recentstudy found that U.S. children with IDA had poorer math scores than children without IDA(Halterman, 2001). Giving iron supplements to young children increases growth (Drake, et.al., 2002) and may decrease levels of stunting which also affects school enrollment and otherindicators for coverage and quality of education. In Malawi, Shrestha (1994 as reported byLatham, et al., 1995) found that by giving iron supplements to children 6–8 years of age inNtcheu District, eye-hand coordination improved and IQ increased by 7 points. Vitamin Adeficiency increases mortality in young children, is a leading cause of blindness in young chil-dren worldwide and affects iron metabolism, increasing iron deficiency anemia. Zinc is anoth-er micronutrient, which is important for the growth of children under 5 years of age and pre-pubertal children (Brown, et al., 2002). Zinc deficient children who receive zincsupplementation have decreased severity of diarrheal disease and pneumonia (Bhutta, et al.,1999). Children living in iodine-deficient areas have lower IQs and poorer cognitive and motorfunction than children living in non-iodine deficient areas. Most of the damage to IQ occursbefore birth but several studies show that improvement can occur in abstract reasoning andverbal fluency when urinary iodine status improves (Drake, et al., 2002). The Shretha study(1994 as reported by Latham, et al., 1995) found that children 6–8 years of age performed bet-ter on tests for stamina and certain physiological tests when they received iodine supplements.Improvement in mental development translated to a 21-point increase in IQ. When iron wasalso given, IQ increased by 26 points.
School Effectiveness, Malnutrition and Learning Outcomes 73
the academic year begins in January, which hasa negative impact on student enrollment anddropout. While this drop in attendance is achronic annual problem, in 1999 the problempersisted during most of the school year.16
During the most recent food crisis, schoolmeals were the only food some children werereceiving and these helped stave off starvationin families that were without grain reserves ormoney to purchase food. There is also someanecdotal information to suggest that duringthis period, younger children (<6 years of age)were enrolling in school to obtain at least onemeal per day.
However, access to education is differentfrom a demand for education. As such, foodcan prove to be either a barrier or an incentiveto attend school. Meanwhile, Malawian par-ents are faced with the stark reality of increas-ing opportunity costs at a time when the per-ceived benefits from education are, at best,minimal.
Correlation between schoolingcharacteristics and learning outcomes
To appreciate further those characteristics thatinfluence learning, this section investigates theelasticity between education outcomes andinput variables—in other words, the extentthat learning outcomes improve with changesin inputs. The strength of this relationship willalso provide insight into the overall manage-ment of the system; the expectation is thatchanges in the typical policy-related inputsshould have a direct impact on learning out-comes. This analysis is especially importantbecause of an emerging paradigm shift frominputs to outcomes.
The review measures changes in outcomesby examining changes in retention throughoutprimary and by investigating changes in thepass rates in the national PSLCE. Such ananalysis only provides a partial picture of theeducation system, and it does not capture the
totality of student learning. Using the EMIS2000 dataset, a regression analysis is per-formed to examine the correlation between thementioned outcome changes and changes inschooling input characteristics—for examplethe percentage of qualified teachers, unit costs,repetition rate, PTR, proportion of femaleteachers, etc.
Table 5.6, below, summarizes the results offour regression models based on retention andpass rates of individual schools. The first threemodels use retention throughout primary as ameasure of student achievement; the last oneuses the pass rate in the PSLCE.17 The first twomodels measure the variability in retentionrates from Standard 1 to 818 based upon vari-ability in the input variables. The models differin that they use slightly different input vari-ables. Retention is calculated with a simplifiedformula: in each school the non-repeating stu-dents in Standard 8 are divided by the non-repeating students in Standard 1. This processprovides an average retention of 31 percent.The third model measures the variability inretention rates from Standards 1 to 4,19 andthe average retention measured in this manneris 49 percent.
It is important to note that the EMIS schoolcensus only reports school-related variables.The most important finding is that these select-ed variables only clarify a very minor part of thedifferences in retention and pass rates amongschools. In other words, there are factors whichare not included in the regression model that aremuch more powerful contributors to the differ-ences in the selected outcome variables. For theregressions on retention in Standards 1 to 8,only about 10 percent of the differences can beexplained by the differences among schools inrespect to the selected input variables(urban/rural, proprietor, repetition rate, doubleshifting, proportion female teachers, text booksper student, unit cost). In the same way theregression for retention in Standard 1 to 4 canexplain only 5 percent of the differences in theretention among different schools. In the case of
74 Cost, Financing and School Effectiveness of Education in Malawi
the regression using pass rates, it can onlyexplain about 2 percent of the differences in thePSLCE pass rates among schools.
In the regressions on retention in Standard 1to 8, the significant variables27 are the PTR,the percentage of unqualified teachers and theunit cost. In regression (2) the interpretationfor the PTR variable is that if a school with anational average of 70 pupils per teacher couldreduce this number to 60, retention wouldimprove by nearly 1.5 percentage points. Simi-larly, for unqualified teachers, if a school withthe national average of 52 percent unqualifiedteachers could lower this by 10 percentagepoints, then retention would improve byapproximately 1.7 percentage points.
In regression (1) the interpretation for theunit cost is that if a school has a unit cost ofabout 100 MK more (as a result of a lowerPTR and/or more qualified, thus better paidteachers) than the national average of about1,115 MK, then retention is likely to be higherby about 0.8 percentage points.28
In a well-managed education system, a sig-nificant relation is expected between inputsand outcomes. In Malawi, however, there isvery little relation shown when using these tra-ditional school-based variables. What these
analyses have demonstrated—and confirmedthrough similar analyses in other countries—isthat absolute resources (unit costs), the PTR,and the qualification of teachers are predictorsfor improvement in learning outcomes. Obvi-ously the weak correlation between the vari-ables means that there are important non-explained (by this model) factors to thelearning process in schools, like for instancethe limited time-on-task or the high teacherand student absenteeism. In summary, thisreview suggests that more efficient manage-ment of the system, greater accountability andimprovements in the existing incentives areessential precursors for a successful interven-tion in Malawi’s education system. Additional-ly, factors external to the system, like forinstance malnutrition, can also have an impor-tant effect, and addressing such should be partof an overall strategy to improve children’slearning opportunities.
Notes1. In Malawi the SACMEQ study only
included the English literacy test, not themathematics test, as it did in many of the otherparticipating countries.
Table 5.6: Correlates of school variables with retention and exam pass rates
(1) Retention (2) Retention 1 to 8 Model 1 to 8 Model (3) Retention
Variable with unit cost without unit cost 1 to 4 (4) Pass rate
Source: Authors’ calculations using EMIS 2000. Note: Values in brackets are not statistically significant at the 5% level.
School Effectiveness, Malnutrition and Learning Outcomes 75
2. In the case of Malawi, approximately onethird of the pupil data were missing—therewere only 1983 valid responses out of plannedsample of 3100. Several reasons were suggest-ed for this; the major ones were a lack of trans-port for data collectors and pupil absenteeismon the day of testing. In most other countriesthe response rate was 90 percent or more. Thismeans that the Malawi results have to be treat-ed with caution but the gaps are unlikely toinvalidate the general finding of the study.
3. A degree of caution is required wheninterpreting these results because many of thepupils who live in towns and from the highersocio-economic levels are also the ones whomay regularly come in contact with Englishoutside school, which may have an effect ontheir performance on English reading tests.
4. The draft Malawian language policy wasreaffirmed in 1996 and stated that in the lowerstandards, local languages be used as the medi-um of instruction. But for a number of reasons,the policy is not fully implemented—theseinclude: ambivalent attitudes about the valueof this policy, lack of the required teaching andlearning materials, language mismatchingbetween various region and teacher postingdecisions, time tabling difficulties, confusionsabout the distinction between teaching a lan-guage and developing literacy, etc. As such,many pupils frequently fail to acquire basic lit-eracy skills because they are forced to learn ina language other than their L1 (MLA, 1999).
5. The number of private schools sampled istoo small to allow for reliable generalizations.
6. The main sources are the 2002 householdsurvey and the 1998 SACMEQ study.
7. PTAs are voluntary organizations run byparents and teachers and focus on the welfareof students and teachers and the overall devel-opment of the school. The school committeesare the statutory representatives of the MOESTat the primary school level and are chargedwith overall development of the school.
8. The data is confined to children attendingday schools; boarding pupils are excluded.
9. Attending funerals or assisting familymembers with funeral-related responsibilities.
10. See “American Institutes for Research.2000.”
11. The reconfirmation of local languageinstruction for Standards 1 to 3 during a recentlanguage symposium was a positive develop-ment.
12. Esme Chipo Kadzamira, Dixie Maluwa-Banda, Augustine Kamlongera, Nicola Swain-son, September 2001, Center for EducationalResearch and Training (CERT), Malawi.
13. DHS—Ed Data 2002 found that 29% ofrural children and 18% of urban children wereabsent some time during the previous schoolyear because of being too hungry.
14. Studies in smaller areas of the countryconfirm high rates of malnutrition in allschool-age children. Surveys conducted bySave the Children/U.S. (SCF/US) in selectedschools of Mangochi district show high preva-lence of stunting (39 percent), underweight (38percent) and wasting (5 percent) in all schoolchildren (ages 6 years to over 14 years of age)(Save the Children. 2002). Stunting rates werehighest in the 10–14 year age group (42 per-cent). Higher rates of stunting in older agegroups have been corroborated by anothergroup, which found that 43 percent of 11-year-old school children were stunted and by a 5-country study (Partnership for Child Develop-ment, 1998). This 5-country study found thatstunting was higher in boys than girls—a find-ing also of the SCF/US study.
15. Save the Children. 2002. 16. In order to increase enrollment and
attendance at schools, WFP, in partnershipwith MOEST and UNICEF, is implementing apilot school-feeding program in selectedschools in the country. In 1999 Dedza East dis-trict was selected as the pilot area for theschool feeding program with the target of23,500 primary school students attending 24schools. The objectives of the program were to:improve child enrollment and attendance in allstandards; improve pupils’ capacity to concen-
76 Cost, Financing and School Effectiveness of Education in Malawi
trate and assimilate information by reducingshort-term hunger; increase attendance andenrollment and reduce dropout rates of girls inStandards 5–8. The program in turn increasedenrollment by 20 percent, stabilized classattendance patterns, reduced dropout rate ofgirls and boys in all standards, improved edu-cational results for both girls and boys (accord-ing to interviews with parents, teachers andstudents) and attained a more equitable ratioof boys and girls in Standard 5–8.
It should be noted that school feeding pro-grams elsewhere do not translate into betternutritional status of students because parents,knowing that their children receive a meal atschool, reduce the food they provide to chil-dren at home. However, committees wereencouraged to provide food more strategicallyin the day, when it would have the greatestimpact on attentiveness and learning andwould maximize its effect on educational out-comes. Students in Standards 1 and 2 attendschool from 7 to 11 am and receive Likuniphala at about 9 am, which helps reducehunger students experience at school and, intheory (there has been no evaluation on theprogram’s impact on learning) increases atten-tiveness, attention span and ability to learnduring the subsequent school hours. Because ofthe logistics of feeding all children at the sametime, older students, who have a longer schoolday, usually receive their meal later in the day.
17. It is important to remember that it is thevariability in the pass rates of schools that isanalyzed. Children reaching the level sitting thePSLCE are already a minority group within theschool system, irrespective of how the condi-tions of their school have been throughout theeight grades and irrespective of any other non-school related conditions experienced.
18. The Free Primary Education policy maydistort the results somewhat. However, for themost part the extra enrollment as a result ofFPE will be relatively proportional over the dif-ferent schools, so that the variance in retentionamong schools (which is being examined here)
is not effected. Only the absolute level of reten-tion might be underestimated.
19. The large influx as a result of the FreePrimary Education policy in 1994 may distortthe results somewhat. However, by the year2000 (for which data exists), a major part ofthose entering primary in 1994 have eitherdropped out or are presently in standard 4—this means that the standard 4 enrollment hasalready incorporated the effect of FPE.
20. Dummy variable for urban versus ruralschools. A positive value (if significant) meansthat urban schools perform better, given thatall other variables in the model are the same. Apotential reason why this variable is not signif-icant in 3 models, may be because the main dif-ferences between rural and urban areas may becaptured elsewhere in the model under thepupil: teacher ratio and pupil: qualified teacherratio—which are much higher in rural areas—or under the unit cost which is much lower inthe rural areas.
21. This is a dummy variable for centralgovernment schools. It reflects the difference inoutcomes between a school where the centralgovernment is the proprietor versus the refer-ence type of school which is one where LEA isthe proprietor, considering all else the sameabout the schools.
22. This is a dummy variable for centralgovernment schools. It reflects the difference inoutcomes between a school where a religiousentity is the proprietor versus the referencetype of school which is one where LEA is pro-prietor, considering all else the same about theschools.
23. Same as previous, but between privateschool and LEA school.
24. Interpretation is as follows: a 1 percent-age point decrease in repetition in the whole ofprimary (below its average of about 16% asmeasured by EMIS) corresponds to a 0.2 per-centage point increase in pass rate of the grade8 students who take the exam.
25. Dummy variable for schools with doubleshift system or schools with an overlapping
School Effectiveness, Malnutrition and Learning Outcomes 77
system of classes with a single shift and classeswith a double shift. The reference here are sin-gle shift schools. A positive value thereforemeans the result is better in schools with dou-ble shifting or overlapping.
26. Interpretation is as follows: a 10-per-centage point increase in the proportion ofwomen in the whole of primary (above itsaverage of about 24%) corresponds to a 0.5
percentage point increase in the retention inprimary.
27. Those that had a very high T-statistic asa measure of significance.
28. The unit cost is calculated using thenumber of teachers for a given number of stu-dents and their assumed income given theirgrade levels.
CHAPTER 6
Equity
he present chapter discusses educa-tion equity and focuses on differ-ences across gender, geographicallocation/region, household income
groups and consumption quintiles. The under-lying premise is that an equitable distributionof education resources plays an important rolein reducing poverty and in improving the dis-tribution of opportunities, of income andwealth and of participation in society. In addi-tion, improving educational access by thepoor, by the marginalized and by the mostvulnerable groups leads, eventually, to faireraccess to a number of public services. Further-more, equitable access to education con-tributes to the re-distribution of income andthis, in turn, benefits the poorest groups insociety. This is particularly true in the educa-tion sector. It constitutes the largest govern-ment expenditure item and it has the widestoutreach because almost all families inMalawi have children, or are guardians forchildren and, as such, have the potential tobenefit from public subsidies through educa-tion. This means the education sector is aneffective fiscal instrument for alleviatingpoverty and redistributing income. According-
ly, this section examines who benefits frompublic spending on education and other equi-ty issues.
The government has implemented a numberof initiatives, explicitly aimed at ensuring equi-table access to education. Here, FPE, in partic-ular, has improved the access of the poorer seg-ments of society to primary education. Atsecondary and tertiary levels, also, a number ofinitiatives have been initiated. For example, thegovernment has created extra secondary schoolplaces by changing Distance Education Centersinto Community Day Secondary Schools; it hasprovided scholarships to girls and orphans;and has established education institutions indisadvantaged areas. At tertiary level, a bur-sary scheme to support female students study-ing non-traditional courses, such as engineer-ing, is in place; there is also a loan scheme toassist needy students ‘whose parents orguardians fail to pay the obligatory fees’.1
Although these policy interventions are target-ed, in part, to improve inequities in the distri-bution of education opportunities, there is aneed to ascertain the extent of currentinequities and tighten policy interventions asrequired.
78
T
Equity 79
Enrollment patterns by gender andgeographic location
An overall perspective
Figure 6.1, shows that overall enrollment inthe Malawi education system, by gender,favored boys in 1999/2000. The percentage ofgirls enrolled was 48.5 percent for primaryeducation, 40 percent for secondary, 35 per-cent for primary teacher training, and 26 per-cent for higher education. However, in primaryeducation there are as many girls as boys infirst four grades while the share of girls dropsto 45% in Standards 5 through 8.. In publicformal Technical and Vocational Training,between 2000–2003, girls represented 34 per-cent of the graduates.
Since primary Teacher Training Colleges(TTC) traditionally enroll a significantly high-er number of male than female students, theshare of women in the stock of primary teach-ers is much less that of men. One crucialcaveat, here, is that trying to balance the num-ber of male and female teachers should takeinto account that most female teachers are cur-rently deployed to urban areas—in rural areasonly 22 percent of teachers are women, where-as in urban areas the figure is 75 percent.Accordingly, recruiting more female teachers
should be coupled with implementing policiesto deploy more female teachers to rural areas.
If the perspective over time is considered, itis clear that improvements have occurred insecondary; girls’ participation has grown from35 percent of total enrollment in 1992/93 to 40percent in 2000, and, in addition, femaleaccess to university level also increased slightlyfrom 23 percent in 1993/94 to 26 percent. Onthe other hand, in primary teacher education,there has been a negative trend with a declinefrom 41 percent in 1993/94 to 35 percent in2000.
Analyzing for regional differences, no signif-icant difference was found in gender specificenrollment between the six divisions.2 Annex6.1 presents the Relative Gender Gap (RGG)by district.3 To close the gap in gender specificenrollment, efforts need to be considered, suchas providing targeted feeding for girls in thetwo districts with the most significant gendergaps (Nsanje and Chikwawa).
Table 6.1 indicates that there are significantdifferences in primary enrollment betweenrural and urban areas, both for NER and GER.Furthermore, the NER and GER are quite dif-ferent by region, the Northern region havingthe highest enrollment and the South havingthe lowest. Differences are just as substantialbetween the richest and the poorest house-
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
Highereduc.
Prim.Teach.
Training
Secondary Standards5-8
Standard1-4
Primary
Boys Girls
Figure 6.1: Enrollment by gender and level of education, 2000
Source: Basic Education Statistics 2000. For secondary the estimated numbers are used.
80 Cost, Financing and School Effectiveness of Education in Malawi
holds: for children aged 6–13 years in the high-est income quintile, 91 percent attend primaryschool compared to 73 percent in the lowestquintile. The GER follows a similar pattern; itis 126 in the highest quintile and 106 in thelowest quintile.
There is no difference in the NER by gender(81 percent). However, the male GER exceedsthe female GER in both the North and theSouth, but there is no difference in the GER inthe Central region.5 Thus, the full difference inenrollment in primary by gender is a result ofthe higher number of over-age boys in the sys-tem. This is an indication that a reduction inrepetition will reduce the imbalance in theboys/girls enrollment. In general, the older girlsare more prone to drop out and more likely torepeat. As such, if repetition is not lowered sub-stantially in the lower standards, it will be nec-essary to target older girls to improve retention.
Inequities in the NER also arise as a result ofdifferences in parents’ education; studies sug-gest that the education of parents is a strongpredictor of whether a child is likely to enrollin school. This is especially true for the educa-tion of girls and their mothers. The NERamong children aged 6–13 years whose moth-ers never attended school is 71 percent, where-as the NER among children whose mothers
obtained some primary education is 87 per-cent, or 16 percentage points higher. Amongchildren whose mothers attended at least somesecondary school, NER is 97 percent, or 26percentage points higher than for childrenwhose mothers never went to school.
Another predictor of educational attainmentis household income level. As Table 6.2 shows,the GER for all income quintiles in Standards1–4 is above 100 percent and this reflects thelarge number of overage students, and possiblyreflects some underage students. The poorestincome quintiles have a higher GER than therichest for Standard 1 to 4 because children ofpoor parents repeat disproportionately moretimes in the lower grades. In upper primary,however, the picture is radically different: theGER for the richest quintile is about 100 per-cent whereas it is only 60 percent for the poor-est quintile. In other words, even though pri-mary education is free, certain factors impedethe poorest children from progressing fromStandards 5 to 8. The GER for boys versusgirls only shows a minor difference of 6 per-centage-points for lower primary (156 percentfor boys, 150 percent for girls), whereas inupper primary the GER for girls is much lowerthan for boys (86 percent for boys, 70 percentfor girls).
Table 6.1: Primary school enrollment ratios according to background characteristics, 2002
Residence Region Wealth index quintile4
Urban Rural North Central South Lowest 2nd 3rd 4th Highest Total
Source: Integrated Household Survey 1997/98. Notes: The GER for Std 1–4 is total enrollment in these grades divided by the Std 1–4 school agepopulation (6–9) and the GER for Std 5–8 is total enrollment divided by the population aged 10–13. Quintiles are constructed here by rankinghouseholds by their consumption per adult equivalent. This is different from the quintile calculation in Ed Data 2002. However, it is unlikely thiswill affect the trends discerned.
Equity 81
Table 6.3 shows that urban youth aged14–17 years are three times more likely thantheir peers in rural areas to attend secondaryschool (NER 21 percent versus 7 percent),while the GER differences among them areonly slightly smaller. Regional differences inthe secondary NER are considerable and fol-low a similar pattern to the primary cycle: 6percent of youths aged 14–17 years attend sec-ondary school in the Southern region, com-pared to 10 percent in the Central region and16 percent in the Northern region. There arethus significant regional inequities in the accessto secondary education.
While the gender gap in the NER for sec-ondary is minimal (8 percent of female and 10percent of male youths aged 14–17 yearsattend secondary school), there is a consider-able gender gap in the GER for secondaryschool. Male youths up to age 24 are far morelikely (33%) than female youths (20%) toattend secondary school. This difference is aresult of a significant gender gap in access tosecondary school in rural areas, where maleyouths, often over-age, are twice as likely asfemale youths to attend secondary school. Oneconclusion, here, is that rural girls haveextremely limited access to secondary school.
At the secondary level, differences in theNER as a factor of income level are far morestriking than those found at the primary level:only youth in the highest income quintileappear to have access to secondary schooling.While 23 percent of the wealthiest youth aged14–17 years attend secondary school, only 7
percent of the youth in the fourth quintile, and3 percent of those in the lowest quintile, attendsecondary school.7 This pattern suggests thatthe monetary costs of schooling at the second-ary level may present a substantial barrier bothto entry and to persistence in school beyondthe primary level. It is important to note thatpublic subsidies to secondary education tend tobenefit the wealthiest income groups. There-fore, public funding to secondary should notbe at the expense of primary.
Gender and geographical disparities inschooling profiles
The disparities in access to Standard 1—or the‘gross admission rate’ or ‘cohort entry rate’ bydivision (using the school census informationand UN-EFA population)—show that all divi-sions have rates of well over 1 (or over 100percent, meaning more new entrants in Stan-dard 1 than the population in the correspon-ding age groups). The figure ranges from ashigh as 2.55 for Central West to 1.41 in SouthEast and it indicates a clear relative difference.8
There are no divisions that show a significantdifference between boys and girls. Using therepetition rates in the 2000 household survey,the access rates of primary for boys and girlsare quite similar with values higher than 1(1.32 for boys, 1.27 for girls).
Figure 6.2, above, shows that survivalthrough primary is about 20 to 30 percentagepoints higher in urban areas than in rural, dueto higher dropout rates in rural areas in the
Table 6.3: Secondary school enrollment ratios, by gender, according to background characteristics, 2002
Residence Region Wealth index quintile6
Urban Rural North Central South Lowest 2nd 3rd 4th Highest Total
Source: Ed Data 2002. Results are for the de jure household population age 5–24.
82 Cost, Financing and School Effectiveness of Education in Malawi
first few grades. This indicates a need to focuson survival in early primary in rural areas; italso suggests that if rural children make ithalfway through primary, they are more or aslikely to complete their education as theirurban counterparts. In Chapter 4, it wasapparent that urban areas benefit proportion-ally more from teacher deployment arrange-ments, especially for the qualified teachers.Concurrently, the regressions on retention inprimary show that the proportion of qualifiedteachers and the PTR impact retention levels.Therefore, the difference in survival ratesbetween urban and rural areas are affected bythe difference in PTR and by the percentage ofqualified teachers.
Retention is slightly better for boys thanfor girls in upper primary (see Annex 6.2). Insecondary education the difference in the sur-
vival rate is slightly higher but it is still muchmore modest than the urban-rural differ-ences, even in the primary sub-sector. Thedifference in the survival of boys versus girlsis also quite similar in all divisions. Signifi-cant differences in survival exist betweendivisions themselves, as Table 6.4 below indi-cates.11 Here, the Northern Division clearlyhas a significantly better retention than allother divisions, whereas Central West has themost worrying situation. Although it may beargued that the Northern Division is privi-leged, compared to the other divisions, thedrop from 100 percent to below 50 percentby Standard 8 reflects inadequacies inherentin the entire education system. However, themagnitude of the intervention required for apositive change to occur would differ by divi-sion.
0102030405060
7080
90100
Grade1
2 3 4 5 6 7 8Urban Rural
Figure 6.2: Survival in primary, urban9 vs. rural (cross-sectional method)
Source: EMIS for enrollment and repetition,10 UN-EFA population (distributed between urban/rural according to proportion found in NSOpopulation estimates for 2000).
Table 6.4: Retention standards 1–8 and 1–4 by division and by gender, 2000
Northern 42.2 65.4 57 95Central East 24.0 53.0 63 132Central West 14.8 35.0 62 131South East 21.2 49.5 70 146South West 27.6 58 60 109Shire highlands 20.3 48.1 70 136
Source: EMIS 2000 enrollment and repetition12 and 2000 UN-EFA population (distributed over the divisions according to proportion found in NSOpopulation estimates for 2000)
Equity 83
One possible reason for the better perform-ance in the North is the longer tradition and thehigher esteem in which schooling is held—it wasthe region where many missionary schools werefounded and where education has, in general,been of a better quality. Another reason for thedisparity may be the lower PTR and the lowerPqTR vis-à-vis the other divisions. It is interest-ing to see that South West is the second best per-forming division in retention, and also has a bet-ter PTR and PqTR. However, the difference inthe retention rate between South West andNorthern is larger than would be expected fromthe difference in the PTR and PqTR.
Completion rates in primary andsecondary
The PCR by gender shows a sizable difference,with a bigger gap for Standard 8 completion in
comparison to Standard 4 completion (see Fig-ure 6.3 and Annex 6.3). Despite this discrep-ancy, the trend over time is positive and showsa narrowing of the gap.
Table 6.5, below, shows that the disparity inpass rates between girls and boys differ signif-icantly by type of school, especially for stu-dents enrolled in a CDSS.13 The differencesbetween boys and girls may have to do withthe selection policy at the beginning of sec-ondary, which allows girls to enter more easi-ly than boys with similar levels of achievementin the PSLCE test. Since the number of girlsentering secondary is still lower than the num-ber of boys, it is difficult to argue against thispolicy if gender equity is considered para-mount. It is, however, important to verifywhether other factors are contributing to theweaker performance of girls on the MSCEtest.
Standard 4
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
YYYY eeeeaaaarrrr
Boys
Girls
Standard 8
0.0%
20.0%
40.0%
60.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Perc
ent
Boys
Girls
Perc
ent
Figure 6.3: Proxy std. 4 and std. 8 completion rates by gender
Source: Basic Education Statistics for enrollment and repeaters, and NSO population.‘Proxy’ completion is calculated as the number of non-repeating students in Std. 4 and Std. 8 divided by the corresponding age cohort. Note:UN-EFA population is not available for the beginning of the nineties, nor are household surveys for repetition rates. However, since the goal isto look at relative differences in completion by gender, the potential shortcomings in population estimates and repetition rates are lessrelevant.
84 Cost, Financing and School Effectiveness of Education in Malawi
From the results of Table 6.5, it could behypothesized that the grant-aided schools mayoffer lessons relevant to schools trying toimprove their MSCE results. For example, per-haps the management styles of the grant-aidedinstitutions elicit better student performance inexaminations. However, it is also importantnot to overlook the fact that households whosend their children to grant-aided schools alsocontribute significantly more funds, comparedto government day and boarding schools. Inaddition, the selection process of potential can-didates may also be different.
Public expenditure breakdown byquintiles and gender at differenteducation levels
To improve the equitable distribution ofresources and pro-poor spending, it is impor-
tant to analyze the amount of public resourcesthat different income groups receive in eacheducation sub-sector. For example, if publiceducation spending is distributed equallyacross the population, then each of the fiveincome groups will receive an equal share of20 percent.14 Table 6.6, below, summarizeshow education spending is distributed by levelof education according to family wealth, com-paring situations in 1997/1998 and1990/1991.
It is apparent that the situation hasimproved: in 1990/1991, the poorest quintilereceived only 10 percent of public resourcesbut by 1997/98 this share had increased to 16percent and had been reduced for the richestquintiles (e.g. from 38 percent to 26 percent).Despite this progress, public spending remainsregressive, benefiting the children of the richesthouseholds most (26 percent versus 16 percentfor the poorest quintile).
Table 6.5: MSCE and JCE results, 2002
MSCE MSCE JCE JCE
Type of school % female pass % male pass % female pass % male pass
Community Day Total 10.2% 21.0% 48.4% 63.4%Government Boarding Total 28.8% 54.7% 56.3% 75.8%Government Day Total 37.9% 54.0% 60.8% 76.9%Grant Aided Total 53.3% 65.0% 74.4% 86.9%Night School Total 26.0% 50.3% 30.1% 64.3%Private Total 28.7% 39.2% 55.6% 65.2%Grand Total 23.9% 34.4% 52.8% 66.6%
Source: Authors’ calculations, using data from MANEB database.
Table 6.6: Incidence of public education expenditure by level and quintile
Poorest 20% 2nd 3rd 4th Richest 20%
1997/98All 16 19 19 20 26Primary 22 22 21 19 16Secondary 12 18 16 22 33University 0 13 24 11 531990/91All 10 13 16 24 38Primary 15 18 20 23 24Secondary 7 11 14 28 41Sources: 1997/98 data from Integrated Household Survey and MoE (1998); 1990/91 data is taken from Castro-Leal (1996), table 14 pp24 and tableA.8 pp42. Notes: Under ‘All’ for 1997/98 only primary, secondary and university public education spending is included. ‘All’ for 1990/01 includes thesame spending types but, in addition, it also includes other tertiary education (primary teacher education and technical training).
Equity 85
This is due to the fact that, in general, chil-dren from wealthier families tend to benefitmore from secondary and tertiary education—because very few, if any, poorer childrenprogress to higher grade levels. However, since1990/91 the situation has been improving as aresult of FPE and the expansion of secondaryschools. In 1997/98, the poorer primary pupilsbenefited more than the highest income groups:the two poorest income groups each received22 percent of public resources for primary edu-cation versus only 16 percent for the richestquintile. On the other hand, in 1997/98, chil-dren from the poorest quintile benefited almostnot at all from subsidies in tertiary education.
As indicated earlier, primary PTRs acrossstandards show substantial differencesbetween the lowest and highest standards.Since the largest public expenditure item inprimary is teacher salaries, a very high PTR inlower grades means that spending per child inlower primary is less than the spending perchild in upper primary. Further, since fewerchildren from the poorest households progressbeyond the lower grades, there is room forimprovement in pro-poor spending in primary.At a minimum, balancing the spending perchild in lower and upper primary (especiallyby lowering the PTR in lower primary andensuring, at least, the same percentage of qual-ified teachers at this level as for upper pri-mary15) could improve the situation further.
As discussed, the situation at the secondarylevel has improved since 1990/91; more chil-dren from poorer households are now access-ing this sub-sector. For example, the share forthe poorest quintile increased from 7 percentto 12 percent in 1997/98 while the share forthe richest quintile declined from 41 percent to33 percent. However, substantial inequitiesremain, with the children of the poorest 40percent households receiving less than 30 per-cent of the public expenditure, while those ofthe richest 20 percent receive one-third.
At university level, where access to university isby and large only open to children of wealthier
families, more than half of the public resourceswere consumed by children from the richest 20percent of the population in 1997/98. Those in the2nd to 4th quintile, on average, benefit fromabout 16 percent from government spending. Thesubsidization of university is particularly con-tentious — since full board is a major expenditureitem — at a time when hunger and chronic mal-nutrition is endemic for millions of Malawi’spoorest. As such, overall public funding at the uni-versity level needs to be further investigated todetermine possible funding and access increaseswhile simultaneously increasing pro-poor spend-ing and targeting the poorer qualified students atboth secondary and tertiary education.
Improvement in the distribution of resourcesrequires the allocation of public subsidies to thelevels with the highest proportion of poor chil-dren. Prime targets include primary, generally,but also upper primary and secondary CDSSs.Continued efforts are required to ensure gener-al cost recovery (or cost transparency) at sec-ondary, and especially at the university level,combined with scholarships schemes for thepoorest. However, this is a complex and diffi-cult area that requires further analysis.
Looking at differences for boys and girls byincome group (see Annex 6.4), it is clear thatthe most significant differences are found forthe secondary and university sub-sectors: theshare of spending apportioned to girls of rich-er families relative to girls of poorer families ismore disproportionate than for boys. Forinstance, at secondary level it is 36 percent forgirls for the richest quintile versus 9 percent forthe poorest quintile, while for boys it is 30 per-cent versus 13 percent. At university level, it is61 percent versus 0 percent for girls and 49percent versus 0 percent for boys. This is notsurprising since more boys progress to thehigher levels even among the poorest incomegroups. In primary, the situation is similar forboys and girls and with both groups publicspending is slightly pro-poor.
86 Cost, Financing and School Effectiveness of Education in Malawi
Notes1. In the academic year 2001/02, however,
over 4000 students benefited from the loanscheme and this number is more than the totaluniversity enrollment, according to Basic Edu-cation Statistics.
2. At secondary school level, all divisionswere close to the country average of 40 percentgirls—the Central East division was the moreequitable outlier with 43 percent girls and theShire Highlands was the less equitable outlierwith 36.5 percent girls.
3. The RGG is determined by dividing the dif-ference between the GER of boys and girls bythe GER of girls. The RGG, therefore, could behigh as a result of large differences between theGER of boys and girls, or as a result of a smalldifference but combined with a small GER ofgirls. When the RGG is examined against thetotal GER of each district or region, there is aninverse relationship. Higher RGGs are typicallyfound in regions with lower GER levels. Theimplication, obviously, is that increasing GERoverall, would lower the gender gap, and, assuch, a policy to increase retention and enroll-ment addresses gender inequities.
4. For an in-depth explanation of how thewealth index is constructed see page 30 in“Education Data for Decision-making. 2003”by NSO and ORC Macro.
5. South: Boys 114% vs. girls 102%; North:boys 134% vs. girls 123.5%; Central boys118% vs. girls 119%.
6. For an in-depth explanation of how thewealth index is constructed here, see page 30 in“Education Data for Decision-making. 2003”by NSO and ORC Macro.
7. A similar pattern exists among youth upto age 24, with a GER of 62 percent among thewealthiest youth, 23 percent among youth inthe fourth quintile, and 11 among the poorestyouth.
8. It might be that if the reality of CentralWest is much closer to 1 than the results show,the situation in South East is one of a cohortrate of entry of well below 1
9. For urban areas, only Mzuzu City, Blan-tyre City, Zomba Urban, Lilongwe City areincluded.
10. Since the main aim, here, is to show rel-ative differences, the perceived repetition rateinconsistency in EMIS probably effects bothurban and rural areas in a similar way.
11. Remark: Although an assessment ofinequity at secondary education level betweendistricts, divisions and regions might reveal anumber of disparities, such an exercise couldalso be misleading because some districts hostnational schools whilst others do not.Nonetheless, it would be plausible to isolatethe national boarding schools from the “day”in order to determine the magnitude of differ-ence between districts. Furthermore, the dis-trict analysis would offer an opportunity todetermine whether or not the inequity problemhas roots in the primary school sub-sector.
12. The repetition rates in the householdsurveys are not broken down by division andcannot be used in this context.
13. See Chapter 2, section ‘Survival / Com-pletion in Secondary and Transition to Ter-tiary’.
14. The two caveats here, are, that the quin-tiles are based upon 5 groups of the samenumber of households. But since poorer house-holds on average have more children, equalityof public expenditure at household level doesnot imply that each individual child achieves asmuch as subsequent children. Secondly, eventhough in most circumstances achieving equal-ity is going to be an enormous challenge, itcould be argued that for education to be anequalizing factor in society, public expenditureon it should be pro-poor rather than merelyequal among all quintiles.
15. There is a great deal of international evi-dence to suggest that allocating a society’s bestand most qualified primary teachers to the ini-tial grades is bneficial for the educationaldevelopment of the population.
CHAPTER 7
University Sector
n previous chapters a number of fea-tures of the Malawian education sys-tem were explored, particularly theprimary and secondary education
sub-sectors and teacher training strategies. Asmentioned in Chapter 1, education consti-tutes a system and, thus, in the present chap-ter, the higher education sub-sector will bediscussed; here the focus will be on access,equity, financing, efficiency, quality and rele-vance.
Malawi has one of the smallest higher edu-cation systems in Sub-Saharan Africa. Thecountry has two public universities, the Uni-versity of Malawi (UNIMA) and Mzuzu Uni-versity. UNIMA is by far the largest and theoldest university, and it embraces a number ofrelatively autonomous colleges: Bunda Col-lege of Agriculture, Chancellor College, theCollege of Medicine, Polytechnic andKamuzu College of Nursing. However, thedevelopment of the higher education sub-sec-tor has been constrained by a number of fac-tors. In particular, investment has been limit-ed because of the failure to develop a nationalstrategic plan for the education sector as awhole, one that reflects the role of higher edu-cation in relation to the education sector itselfand the overall social and economic goals of
the country. In 1998, the Malawi Institute forManagement (MIM) carried out an analysisof the university sector and concluded that:“Government has yet to develop a compre-hensive policy framework for the University’sdevelopment in terms of defining/determiningthe demand for University’s products andservices, broad parameters e.g. sectors of pri-ority focus, quantity and quality of the Uni-versity’s principal outputs (graduates andresearch) in line with economic require-ments”.
While the MIM Report made a number ofproposals and recommendations on the man-agement of the university sector, to date,implementation of these recommendationshas been limited. Apart from the establish-ment in 1998 of Mzuzu University—in a for-mer teacher training college—there has beenlittle expansion of higher education inMalawi. As such, the colleges have beenforced to function with the existing facilities,staffing and infrastructure arrangements.Lack of investment and maintenance has ledto the deterioration of the infrastructure andhas left some of the colleges in need of signif-icant rehabilitation. Paradoxically, in excessof 200 maintenance staff continue to beemployed at the universities.
87
I
88 Cost, Financing and School Effectiveness of Education in Malawi
Access and equity
Malawi’s comparatively small higher educa-tion system enrolls approximately 4,000 stu-dents, which constitutes roughly 0.3 percentof students of eligible age. The last officialdata from 2001 was 4,128. Growth in enroll-ment has been very slow over time. In1987/88, 2,330 students attended, in 1990/91it was 3,117 and in 1994/95 enrollmentreached 3,600. The only private university,Livingstonia, has yet to open but the projectedinitial intake will only be in the region of 56students.
Figure 7.1, confirms that Malawi has one ofthe lowest proportions of enrolled tertiary stu-dents per 100,000 inhabitants in the whole ofSub-Saharan Africa. This data is from 1996but enrollment has remained more or lessunchanged since the mid-nineties.
With a limited number of students attend-ing, it is interesting to disaggregate the areas ofenrollment. Figure 7.2, provides a breakdownof enrollment in UNIMA and Mzuzu Universi-ty across subject areas for 2001. Additionally,Annex 7.1 shows a detailed breakdown ofrecent enrollment trends and graduate outputby college and by subject area. Here, it isapparent that there is some alignment in rela-tion to areas of enrollment, the demands of thelabor market and the structure of the economy:about 40 percent (or about 1,600 students) areenrolled in agriculture, education or engineer-ing programs.
Despite this relative alignment to the needsof the labor market, the limited enrollment andskills mix means that the higher education sec-tor fails to provide a sufficient number of highlevel human resources and professionals toassist in the conversion and diversification of
0100200300400500600700800
Djibo
uti
Moz
ambiq
ueTa
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iaM
alawi
Chad
Ethio
piaBu
rkina
Faso
Eritr
eaGu
inea
Mali
Ugan
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asca
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oBe
ninTo
goM
aurit
ania
Mau
ritius
Botsw
ana
Swaz
iland
Zimba
bwe
Namibi
a
Figure 7.1: Enrollment in tertiary per 100,000 inhabitants, Sub-Saharan Africa
Source: USAID education statistics database. Results are generally for 1996 but it includes data from 1997 and 1995.
16% 15%
10%8%
7% 7% 6%5% 5% 4% 3% 2%
0%2%4%6%8%
10%12%14%16%18%
Education
Agric
ulture
Engineerin
g
Social S
ciences
S
ciences
Nursi
ng
H
umanities
Applied Studies
Commerce
Educatio
n and Media
Law
Medicine
Figure 7.2: University enrollment by subject area, 2001
Source: UNIMA and Mzuzu University.
University Sector 89
the economy. Several neighboring countrieshave focused on expanding tertiary programs ineducation, agricultural sciences, communica-tion, science and technology. These efforts havegenerated increasing productivity and diversifi-cation of production. In contrast, Malawi hasnot sufficiently focused on these subject areas.The number of university graduates hasremained low and is inadequate to satisfactori-ly contribute to the objectives of socio-econom-ic development and poverty alleviation.
A recent tracer study of university gradu-ates1 examined the socio-economic back-ground of 380 graduates from four differentcohorts in time (1980, 1987, 1994, 1999) andnoted that access is increasingly skewed infavor of students from higher socio-economicbackgrounds. For example, both parents ofgraduates had, on average, at least ten years offormal schooling (mother 13.3 years for femalegraduates, 12.5 for male graduates; father 14.5for female graduates, 11.6 for male graduates).It is also noticeable that the parents of femalegraduates have enjoyed more schooling, whichsuggests that that socio-economic status is stilla more significant determinant of schooling forfemales than for males.
The proportion of tertiary students whoseparents are professionals has increased overtime, while the proportion of tertiary studentsfrom ‘farmer’ households and from other cate-gories with non-professionals as parents hasdiminished over the years. As Annex 7.2 indi-cates, graduates whose parents are profession-als (higher income groups) accounted for 22percent of the traced 1980 cohort butincreased to nearly 50 percent by 1999. Con-versely, students whose parents were subsis-tence farmers comprised 33 percent of the1980 cohort but this had shrunk to only 21percent by 1999. There were also marked dif-ferences in the socio-economic status of femaleand male graduates: among all four cohorts,there were more female graduates from thehigher income groups than in the case of themale graduates.
In brief, it is apparent that a clear majorityof public resources for university is presentlybenefiting what are most likely students of thehighest socio-economic strata. At the sametime, women’s access to higher education con-tinues to lag significantly, only representing 30percent of total enrollment. While it is recog-nized that these issues are both long term anddifficult to address, it is clear that the currentsystem and facilities are not sufficiently robustto cope with the inevitable future demand forpost-secondary education following the intro-duction of FPE and the concomitant increasesin enrollment at primary and secondary levels.
Financing
Chapter 3 indicated that the universities areautonomous and sub-vented. As Annex 7.3.aillustrates, an approximate average of 50 per-cent of university recurrent expenditure wentto ‘personal emoluments’ and ‘benefits’between 1997/98 and 2001/02. Spending on‘students provisions & allowances’ is high, anddeclined only slightly from 11.5 percent to 9.3percent over the period. Utilities –whichinclude the utility costs of the boarding facili-ties– accounted for 7 to 10 percent. ‘Trainingand staff development’ is below 1 percent and‘research, publications, conferences, work-shops’ together account for 1–2 percent. Also,development expenditure for sub-ventedorganizations has become almost non-existent.As a result, UNIMA increasingly uses its recur-rent budget for development expenditures.
As can be seen from Annex 7.3.b, importantsub-items like ‘common services’ comprise‘superannuation’ and ‘accumulated deficit’.Respectively these accounted for 33 percentand 4.5 percent of total ‘common services’ in2001. However, the 2002/2003 estimates (notactuals) indicated an expected reduction for‘superannuation’ to 2.4 percent of commonservices, while ‘accumulated deficit’ and‘advances revolving fund’ rose to 16.8 percent
90 Cost, Financing and School Effectiveness of Education in Malawi
and 8.3 percent respectively. Other importantitems here are ‘conference & workshop’ (11.3percent), ‘examination/entrance’ (8.9 percent),‘sports association/soccer club’ (8 percent),‘staff welfare’ (7.8 percent) and ‘research/pub-lication’ (6.5 percent).
Real recurrent expenditures at UNIMAdeclined steadily between 1993/94 and1996/97, then spiked for one year in 1997/98;and then fell again, before starting to climbmore steadily (see Figure 3.4 in Chapter 3).Overall growth over this period has beenroughly ten percent and this is lower than forMOEST expenditure.
Unit costs. Real unit costs have risen sub-stantially over the period 1993/94 to 2000, assummarized in Table 3.2, Chapter 3. However,although unit costs have increased, they havefluctuated from year to year and this move-ment indicates uncertainty in the flow of gov-ernment funds in periods of fiscal stress. Thissituation is confirmed by the fact that over thepast two years (2002–2003), the university hasaccumulated considerable tax and pensioncontribution debts with the Malawi Revenue
Authority and with a number of external cred-itors for sundry goods. Here, Annex 7.3.cshows a breakdown of unit costs in US$ for thelast four available years: the total unit cost isUS$2,500–3,000, of which US$1,200–1,600 isallocated to emoluments and benefits andabout US$250–300 to students provisions/allowances—this does not include the utilitiescomponent of boarding. On the other hand,slightly less than US$100 is spent on teachingmaterials and equipment. Table 7.1provides abreakdown of unit costs by the different col-leges.
When the unit cost, presented in Table 7.1,is combined with the student/lecture ratio inTable 7.2, the direct correlation between thestudent/lecturer ratio and the unit costs at eachcollege are apparent. By any measure, andespecially when compared to other countries(see Figure 7.3), the colleges have inefficientlylow student/lecturer ratios. In particular,Kamazu College of Nursing and the College ofMedicine have extremely low student/lecturerratios combined with much higher than aver-age total unit costs. Per student spending on
Table 7.1: Unit cost in USD by college, UNIMA and Mzuzu University, 2000/01
Bunda Kamuzu College Agriculture Chancellor Nursing Polytechnic Medicine Mzuzu
Source: Expenditure data and number of students received from University of Malawi. Mzuzu Univ. expenditure data from Consolidated AnnualAppropriation Accounts for Financial Year Ended June 2001.Note: Exchange rate 2000/01 was 65.9.
Table 7.2: University enrollment and lecturer numbers by university and college, 2001
Bunda Chancellor Kamuzu Polytechnic Medicine Mzuzu Univ. Total
Students 592 1,555 270 1,239 87 385 4,128Lecturers 73 194 54 148 86 51 606Student/lecturer Ratio 8 8 5 8 1 8 7Students per
non-teaching staff* 6 23 29 18 3*** 3** 9
Source: Basic Education Statistics 2001. *Data from 1999; ** from 2001; *** in 2003 (in 2001 was 1:1).
University Sector 91
teaching material and equipment appears to below at most of the colleges, except the Collegeof Medicine. While there may be credibleexplanations for these discrepancies, such asthe general cost and features of the individualprograms, the data indicates that it is necessaryto analyze further the discrepancies, andaddress inefficiencies found in the allocationand use of resources in this sector.
Budget Allocation. The universities relyheavily on government for essential resources.Unfortunately, in the current economic envi-ronment, government is unable to guaranteethe steady and timely supply of the necessaryresources to support essential teaching activi-ties and stimulate quality research. Except forBunda College of Agriculture, the College ofMedicine, and to some extent Mzuzu Universi-ty, the remaining institutions have not devel-oped adequate capacity, or produced realisticplans, for how to generate their own resourcesto supplement meager government resources.This is relevant since, at present, the institu-tions only generate about 10 percent of theirtotal income. Moreover, the revenues generat-ed by tuition fees are limited since the fee lev-els only constitute a fraction of the real costs.In addition, instead of collecting fees directlyfrom students, the universities are forced torely on the government to pay these fees. Untilrecently, all students received a ‘loan’ ofMK25,000 from the government cover thetuition fee.2 While this source of income is, inprinciple, limited, it should nevertheless ensurethat the universities have access to some rev-enue but, again, these resources are generallynot provided in a timely manner.
The present government debt to the univer-sities for outstanding fees is in excess of MK250 million. This underscores the urgency ofexploring alternative ways of generating rev-enues to supplement government contribu-tions. In addition to defining fee levels, and themechanism for a loan system that will obligebeneficiaries to contribute to the cost of highereducation through cost-sharing, the universi-
ties need to focus on applied research, to pro-vide full tuition-based courses and to ensurethat they benefit from any consultancy workcarried out by university staff, which in mostcases is carried out using university resources.
Current government policies for universityeducation make the provision of higher educa-tion very costly. For instance, the Education Actlinks enrollment with number of bed spaces inhostels, and requires the provision of freeboarding and loans for all students. These poli-cies, while necessary in some cases, impose asignificant administrative and financial burdenon the colleges. As such, the funding and thestructure within which these services are pro-vided, needs to be revamped as the universitieshave drifted further towards precarious cashflow situations, with substantial unpaid fees tovarious entities and with associated high costborrowing needs, because of these mandatedgenerous provisions for tertiary students. It istherefore recommended to end the provision offree boarding, and only offer loans to the moreneedy, and to regulate repayment.
Role of Development Partners. Over theyears, development partners have played animportant role in the development of universi-ty education in Malawi. Their contribution hasbeen in the provision of infrastructure, learn-ing and teaching resource materials, includingequipment. Donors have also provided fellow-ships and technical assistance. However, in theabsence of a strategic university developmentplan, donor support tends to depend on howactive the college administrations are in solicit-ing resources.
Student Financing. The PER indicates that in1997, when tuition fees were MK1,500, theactual collection rate was 18 percent and thatthe total amount collected only represented 1percent of public expenditure to the universi-ties. At present, all students are theoreticallyrequired to pay a tuition fee of MK25,000 buta tiny minority in some of the colleges arerequired to pay a higher fee—this is supposedto be an ‘economic fee’. Further, government
92 Cost, Financing and School Effectiveness of Education in Malawi
has decided that in future all students who areaccepted into university will be provided witha loan of MK 25,000. In practice, this policyhas already been implemented since, as men-tioned, in 2002, all students received this so-called loan. However, there are no clear regu-lations to ensure repayment and these loansappear to be more in the nature of studentgrants.
Efficiency
In the university sub-sector, there are a numberof inefficiencies that limit the institutions’quantitative and qualitative outputs. Staffinglevels, in particular, affect the efficiency of theinstitutions and their resource utilization. Onthe positive side, the student to lecturer ratioand the student to support staff ratio areextremely low and this could facilitate expand-ed access without concomitant and significantincreases in staff numbers.
Student Lecturer and Student Non-TeachingStaff Ratios. Table 7.2 shows average lectur-er/student ratios of 7 in 2001, and indicates aconsistently low ratio for all colleges.
Figure 7.3 confirms that in comparison toall other Sub-Saharan African countries—for
which recent data is available—the student tolecturer ratio in Malawi is the lowest (with theexception of Equatorial Guinea). Not only isMalawi a low-end outlier, but it is also farbelow the ratio of the majority of countries(the non-weighted average is 17.8). This indi-cates that if Malawi manages to keep subjectarea specialization under control, it should bein a position to substantially increase its num-ber of university students without needing totake on significant numbers of extra staff.
The universities also have a very low ratiosof student to non-teaching staff: the average in1999 was 11 students per non-teaching staffmember. This ratio has possibly deteriorated inthe interim because the available data for 2003show that the ratio in the Polytechnic Collegewas 3, and in the College of Medicine andMzuzu University it was 4. These low ratiosare related to the numerous additional servicesthat the colleges provide (for example, clean-ing, cooking, maintenance, gardening,‘helpers’, etc.). These employees contribute tothe large institutional wage bills and to highunit costs in the system. On the positive side,the UNIMA Council has authorized all col-leges to out-source non-core activities to helpreduce costs by limiting the number of non-academic staff. Unfortunately, colleges have
nFigure 7.3: Student to lecturer ratios at tertiary level in Sub-Saharan Africa, 2000/01
Source: UNESCO Education website statistics. Note: some ratios are for 1999/00 or 1998/99.
University Sector 93
been unable to implement this strategy becausegovernment has yet to produce the necessaryretrenchment packages.
Use of Facilities. All tertiary colleges haveadopted a two-semester academic year, leavingthe institutions idle for about 3 months in theyear. In addition, most of the colleges do notoperate a credit hour system that would allowstudents to enroll as, and when, they are in aposition to mobilize the necessary tuition feesand thus increase enrollment. With improveduse of existing facilities and of teaching andnon-teaching staff, enrollment could beincreased without substantial additional costs.A clear option would be to increase the num-ber of shorter diplomas, or individual coursesfor which there is a real demand in the labormarket. These might be provided during theidle times in the institutions (e.g. night, week-end and holidays) on a cost recovery basis.
Duplication of Programs. There is duplica-tion in many of the programs offered by theuniversities. For example, Biology, Chemistry,Law and Home Economics are offered in morethan one institution. This wastage of scarceresources could be reduced, or eliminated com-pletely, through a rationalization process thatwould ensure disciplines, which re-enforceeach other, are only offered in the same institu-tion. There may, however, be a need for bal-ancing this process against trying to provideaccess to popular programs in different urbanareas and regions. A potential option is toexplore the creation of ‘satellite colleges’,which offer more general first year, and under-graduate programs with limited specialization.
Student Accommodation. The EducationAct limits enrollments to available bed space inthe colleges. Colleges are therefore forced toprovide accommodation for their students, butlack of capital investment has inhibited expan-sion of the hostels, which in turn limits enroll-ment. The recurrent cost implication ofexpanding boarding places is substantial andunsustainable. As long as cost sharing, or costrecovery, mechanisms are not in place, univer-
sities will not be able to expand access. MzuzuUniversity has had some success using limitedfunding to use prefabricated structures in hos-tel construction. Furthermore, some collegeshave begun to ignore this accommodation pro-vision in the Act and have started enrollingnon-residential students in parallel programs.These students, still few in number, pay closerto unit cost fees unlike government-sponsoredstudents.
Role of Central Administration. The MIMReport observed that central administration ispreoccupied with operational matters when itshould really be concentrating on providing astrategic policy framework for university opera-tions and activities. Efforts should be made toimplement the recommendations of the MIMReport in terms of delivering a well-planneddecentralization program—within a definedframework and with appropriate guidelines.This would result in the transfer of some of thefunctions, carried out by central administration,to the constituent colleges and would improveefficiency in decision-making processes.
Relevance
Over time, the investment in infrastructure andquality inputs has deteriorated,3 leaving mostinstitutions with dilapidated buildings, inade-quate and outdated equipment and lack oflearning and teaching resources. The relevanceof the teaching and research programs, and theskills and knowledge instilled in students, arecritical for later employment and for the inno-vations that graduate students bring to themarket place. Currently, however, there is anabsence of a clear mechanism linking universi-ty research and teaching programs to thehuman resource and skill requirements of theeconomy and labor market. There is also inad-equate linkage between research and teachingactivities. As a result, teaching has not benefit-ed from new knowledge being generatedthrough research activities. The lack of train-
94 Cost, Financing and School Effectiveness of Education in Malawi
ing programs and refresher courses for lectur-ers raises doubts about the relevance andappropriateness of the current content beingtaught and about the teaching methodologiesbeing used.
Employment of Graduates. The relevanceand quality of university education meritssome review. A recent study on skills foremployment concluded that graduates do nothave the skills needed by employers, nor arethey equipped to start their own enterprises.4
Limited contact between higher educationinstitutions and employers was cited as themain reason for this poor preparation for theworld of work.
On the other hand, and probably as a resultof the low number of graduates from the uni-versities relative to the need for universitytrained professionals in the country, this lackof contact has not really affected employmentopportunities. A recent tracer study on univer-sity graduates and secondary leavers5 foundthat unemployment of university graduateswas negligible in 2001. Only three of the 380traced graduates (0.8 percent) were unem-ployed.
However, there are indications that employ-ment prospects declined among the 1990scohorts relative to the 1980 cohort. Only fortypercent of 1994 graduates secured employmentimmediately after graduating from universityin comparison to 90 percent of 1980 gradu-ates.6 Employment opportunities for graduatesvaried according to the program of study.7
In order to expand the private sector anddiversify the economy, it will be critical to havemore graduates becoming private sector entre-preneurs, and the curriculum should be adjust-ed with this goal in mind. Only seven of the380 traced graduates were self-employed inmid 2001, only 15 in total had ever been self-employed and the seven self-employed gradu-ates employed only 45 other people in total.Particular attention should be paid to the areas
of science and technology, which are importantfor industrialization and economic growth.Finally, Malawi, like many other countries, hasexperienced a significant brain drain. This isparticularly true of graduates from theKamuzu College of Nursing, many of whomtend to leave Malawi to work in countries suchas the US and the UK. The government willhave to address this issue through incentivesand by establishing accountability mecha-nisms.
Relevance and Skill Utilization. The tracerstudy also sought the opinion of the graduatesthemselves on a range of topics relating to theiruniversity education and their subsequentemployment. It found that graduates appear tobe generally quite satisfied with most aspectsof their university education, with the overallsatisfaction level highest among the 1980cohort and slightly lower for the latter cohorts.While over 80 percent were satisfied with theknowledge and skills acquired, less than one-third were satisfied with their information andtechnology skills and just under half with theirmanagerial and entrepreneurial skills. Annex7.4 provides the response of the graduates to anumber of questions on the relevance of theiruniversity education. A second table in Annex7.4 shows the prioritized concerns of universi-ty graduates.
To summarize, it is clear that the universitysector in Malawi needs to be restructured withrespect to funding, efficiency, quality and rele-vance. The country needs to expand universityeducation enrollment and graduate output, butit must do so strategically to ensure that pro-grams and graduates meet the demands of bothsociety and the economy.
Notes1. Kadzamir et al.2. In the academic year 2002, ‘loans’ were
provided to a total of 4,000 students.
University Sector 95
3. Chapter 3: Educ. Financing indicates thecomplete breakdown of (on-budget) develop-ment spending to universities.
4. Thomas et al. 20015. Kadzamira et al.6. As a result, unemployment was quite high
(60 percent) in the immediate period aftergraduation. On average, it took 1980 gradu-ates less than a month to find their first job.For the 1999 cohort, this period was threemonths but this is still low.
7. Bunda College, Kamuzu College of Nurs-ing and the College of Medicine have a higheremployment track record for their graduatesbecause of the nature of their sectors. Chancel-lor College and the Polytechnic, which bothhave higher enrollments, face some challengesin providing programs that address the skillneeds of the sectors and in producing employ-able graduates.
CHAPTER 8
Critical Challenges and Policy Choices
his study has provided the analyticalunderpinning for synthesizing keyissues and this chapter highlights thecritical challenges. Using the results
of a financial simulation model, an attempt isalso made to lay the foundation for realigningthe policy targets with resources.
Macroeconomic context andeducation expenditures
For a country undergoing a transition periodof huge enrollment expansion (FPE in primary,and CDSS expansion in secondary), the priori-ty given to education, as reflected in govern-ment spending, has been relatively modest inthe last 10 years in the range of 12–20% oftotal government expenditure. However, in thepast couple of years, government spending hasbeen in the higher end of this range as agreedwithin the framework of HIPC. As the econo-my is unlikely to generate much in additionalresources, the government will either have to:(i) improve the efficiency (productivity) of thesystem and resource distribution, (ii) increasethe share of public spending on education, (iii)increase cost-recovery at post-primary orincrease access on a full cost-recovery basis,
(iv) increase external (donor) funding, or acombination of the above.
Furthermore, it is important to ensure amore stable and predictable flow of funds tothe education sector if the long-term benefitsfrom this investment are to be harvested. Fund-ing of the sector should be in line with a well-defined, long-term strategic plan.
Sub-sectoral allocations and allocations bytype of school need to be closely aligned witheducation policy goals. Although primary edu-cation obtains the highest share of recurrentexpenditures, it is not clear whether its share ofdevelopment expenditures is in line with thegoals of universalizing access. A striking incon-sistency in sub-sectoral allocations is alsoreflected in the stark differences within thedual secondary system, the CDSSs and theCSSs, and by the higher share of resources pro-vided for tertiary relative to secondary.
Unit costs in education are highly unbal-anced between the university level and all otherlevels, and within secondary between tradi-tional government schools and CSSs andCDSSs. Here, the government will need todefine acceptable levels of per pupil spendingand adjust public financed access at the post-primary level. This may entail capping publicfinanced expansion at secondary level,
96
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Critical Challenges and Policy Choices 97
although it would not exclude expansionthrough private provision.
Managing expenditure on personal emolu-ments will be crucial to achieving sustainablelevels of spending. Average salary levels havebeen declining in real terms, partly due to theincrease in untrained teachers—especially atprimary and secondary levels. As the numberof qualified teachers increases, and as moreteachers are employed due to higher enroll-ment and a lowering of the PTR, personalemoluments will rise.
In secondary education, medium-term tar-gets need to be set for access to quality sec-ondary education, in such a way that thefinancing requirements are sustainable.Questions regarding cost-effective organiza-tion and delivery need to be addressed toensure that personnel costs do not crowd outquality improving, non-salary inputs. Whilea rapid geographical expansion couldincrease access, it may result in availableresources being used almost exclusively forsalary expenditures, understaffed schools,and virtually no investment in crucial educa-tional resources.
Enrollment, repetition and survival
Primary completion rate and internal efficien-cy: Many children do not progress beyondlower primary because of high repetition rates.The level of repetition is very high throughoutprimary as a whole –an average of 25% ofeach grade repeat every year, and in particularin Standard 1 where about 40% of pupilsrepeat. This distorts the system right from thestart. Dropout in primary is also relativelyhigh, at between 5 and 10 percent in eachgrade. However, between 1992 and 2000, thePrimary Completion Rate increased by about15 percentage points from 20–25 percent to35–40 percent. To address problems of repeti-tion and dropout, the improvement in overallquality is a critical element.
Pupil to Qualified Teacher Ratio: There isan urgent need for additional qualified teach-ers to reduce the high PqTR of 123:1 in pri-mary schools. This will require a continuedeffort to produce approximately 5,000 teach-ers per year for the next 10 years, facilitated bycontinuing the present in-service training pro-gram with at least 2 cohorts graduating peryear. Investing in teacher training is a pre-con-dition for improving the quality of primaryschool in Malawi.
Secondary: CDSSs, which represent about70 percent of secondary enrollment, areextremely under-endowed in many ways, forinstance in the availability and qualification ofteachers, in the range of teaching/learningmaterials, and in the dilapidated school infra-structure. Although the PTR is 40:1 in second-ary, the high incidence of primary teachersteaching at CDSSs has produced a PqTR of120:1. As such, a determined effort is requiredto train teachers and fund schools adequately,which may entail putting a cap on the numberof publicly financed secondary schools.
Safety net for the youngest and orphans:The government might consider providingnursery schools for young children. Whileattending pre-school is educationally desirable,in the case of Malawi an expansion in publiclyfinances nursery schools for pre-school chil-dren may provide a strategy to reduce the num-ber of under-aged children starting school, andthus reduce the overcrowded classroom inStandard 1. One option is to use the commu-nities and provide minimum incentives tolocals to attend to the children at the schoolpremises. These nursery schools could alsofacilitate improvements in under-five malnutri-tion provisions.
Equity
With the introduction of FPE, public expendi-ture on primary education became more equi-table, however overall public education spend-
98 Cost, Financing and School Effectiveness of Education in Malawi
ing remains regressive and inequitable. Assuch, focusing resources more equally amongthe different grade levels in primary will have apositive and equalizing effect. It may simulta-neously improve both efficiency and quality byreducing repetition and dropout.
While the primary survival rates for boysand girls are relatively even, there is a signifi-cant discrepancy in survival rates in rural andurban areas: urban students have about 20 to30 percentage points more chance of survivalthrough to the end of primary. In addition tomicroeconomic conditions like poverty levels,there is a clear difference between rural andurban areas in PTRs and, especially, in PqTRs.In addition, rural areas lack female teachersand this deprives rural girls of potential rolemodels. The recently implemented decentral-ization policy may provide an opportunity toprioritize rural areas in future teacher alloca-tion decisions. For this to effectively take place,the overall composition of salary (salary, pro-fessional and housing allowance, potentialrural hardship bonus, and other) needs to pro-vide incentives for teachers to stay in ruralareas, and a functional teacher rotation systemneeds to be put in place.
At the secondary level, two crucial inequitiesare noted: the type of school in which pupilsenroll and urban/rural differences. Urbanyouth age 14–17 years are three times morelikely as their rural peers to attend secondaryschool (NER 21 versus 7 percent). Regionaldifferences in the secondary NER are also con-siderable and follow a similar pattern as theprimary level.1 Differences in access by socio-economic status at the secondary level arelarge, as seen from the GER of 62 among thewealthiest youth and 11 among the poorestyouth.
Quality of education and externalities
The performance, or learning outcomes, ofMalawian students is unacceptably low. While
the children perform quite well in Life Skills,Malawi had the lowest percentage of pupilsachieving ‘minimum’ and ‘desirable’ masterylevels in English literacy, relative to six othercountries in the region.
In Malawi, using the traditional school-based variables, there appears to be little rela-tionship between inputs and outcomes. Predic-tors for improvement in school achievementinclude: absolute resources levels (unit costs),the PTR and the qualification of teachers. Theweak correlation, however, means that otherimportant factors are associated with thelearning process in schools, for example, thelimited teacher time-on-task. Also, absenteeismis a widespread problem, both among pupilsand teachers. This results from multiple fac-tors, such as illness or hunger. The level ofabsenteeism also indicates that institutionalaccountability, or incentives to perform, arelargely non-existing. Further, pedagogical man-agement, and management in general, appearsto be quite weak. Any mechanisms establishedto improve student learning and the quality ofschooling will need to: (i) improve accounta-bility and devise teacher incentives to performassigned duties, (ii) ensure timely and adequateprovision of learning materials, (iii) empowerheadmasters and improve school management,and (iv) help low-achieving schools performbetter.
Prevalence of malnutrition affects survivaland learning capacity in the education system.Malawi has one of the highest levels of stunt-ing in children in eastern and southern Africa.Stunting and micronutrient malnutrition areassociated with reduced capacity to learn,delayed school enrollment, decreased schoolattendance and, eventually, with dropout.These problems are especially critical duringthe hunger period from November to April.Malawi is chronically food insecure because ofregular food shortages in some areas and sea-sonal food shortages in most of the country. Aminimum supply of de-worming and iron-for-tification could contribute significantly to the
Critical Challenges and Policy Choices 99
overall nutritional status of pupils. In addition,the government may wish to sustain currentemergency food structures or to establish adirect support to schools, financed by donors,to ensure cash transfers that could be used topurchase food in times of crisis.
The on-going HIV/AIDS crisis will put fur-ther pressure on the education system, andresult in higher dropout and repetition rates,and increase the number of orphans who willbe especially vulnerable in relation to educa-tional achievement. Government will need todevelop an effective HIV/AIDS policy in orderto prolong the active professional lives ofinfected teachers. Ensuring a supply of flexiblevoluntary teachers and teaching assistants,could also counter teacher absenteeism. A seri-ous debate on the issue of reducing absencesdue to funeral attendance would also be advis-able. In the same way, the issue of funeral ben-efits needs to be addressed so that this itemdoes not completely absorb expenditure onbasic teaching inputs. Possible options, here,are to set up a special fund for this purpose andreduce funeral costs by allowing sick teachersto transfer to their home districts.
Management of the system
Teachers’ deployment is highly inconsistent.Some of the specific difficulties have to do withthe manner in which the present system signif-icantly favors urban areas. This situation isfurther aggravated by the significant discrep-ancy in Pupil to Qualified Teacher ratiosbetween urban and rural districts; in urban dis-tricts it is between 60 and 70, in rural districtsit is approximately double this figure.
The management and deployment of teach-ers to schools needs to be based on an estab-lished PTR (funding formulae) and on theavailability of teaching places. The MOESTneeds to develop an equitable PTR for eachschool. In line with this, there is a need toexplore possible incentives (e.g. a ‘rural
allowance’2) to encourage, and obligations toensure that qualified teachers are available toteach in rural areas. The decentralizationprocess offers an ideal opportunity to rebal-ance these inequities in the teacher deploymentsystem. For example, under a decentralizedmanagement, the resources allocated from thecentral to district level to hire and pay teacherswill be based on a neutral formula and reflectthe number of pupils attending—with someadjustment criteria for poverty levels or popu-lation density. The direct management of thesefunds will allow rural districts to advertiseopen posts as soon as teachers leave. The PERhas already indicated that local recruitment ofteachers might be another way to reduce thetendency of teachers to move to urban areas. Inthe context of the current in-service teachertraining framework, this is feasible becauseteachers are already teaching in a particulararea, and only relocate to the teacher trainingcollege (TTC) for a relatively short periodbefore returning to their schools. This reducesthe probability they would automatically moveto an urban area after leaving the TTC.
One potential measure to increase the num-ber of qualified teachers in the system is toreview the current teacher retirement age. Ofcourse, this may have a limited impact in acountry where the life expectancy is 8 years(although life expectancy may be higheramong teachers).
Teacher remuneration scale setting. Sincemany new teachers are entering the systemeach year, and given that unqualified teacherswill need to be trained, this is an opportunemoment to establish a sustainable salary policyfor the next 10–20 years. As indicated in arecent World Bank study on the Education ForAll-Fast Track Initiative,3 a guideline for aver-age qualified primary teacher salary, in Africancountries, is about four times GDP per capita.The study suggests introducing a dual systemwith the new salary scale only applying tonewly qualified teachers.4 The qualifiedteacher salary in Malawi is currently slightly
100 Cost, Financing and School Effectiveness of Education in Malawi
higher, at about 5.5 multiples of per capitaGDP; on the other hand, this may be a reason-able level for Malawi where per capita GDP islower than in many other African countries.An adjustment of teacher salaries in Malawishould be based on a comparison with earningin other professional occupations.
Budget process, supporting systemsand harmonization of procedures
Budgetary reforms and improvements inaccounting are required to accurately estimatefinancing needs, ensure a smooth flow offunds, reduce unit costs and monitor budgetexecution. At a minimum, MOEST needs toestablish an overview of the total flows into theeducation sector, especially off-budget funds.The second issue is to examine the cash budg-eting system and the impact it has on thestrategic prioritization of medium-term budg-eting and the effective functioning of schools.A third issue is to accurately estimate the recur-rent cost implications of existing developmentprojects and to assess their financial sustain-ability. Efforts could be made to harmonizeprocedures and procurement rules with a viewto using government procedures. Thus accept-able fiduciary arrangements in the educationsector could pave the way for on-budget sup-port.
The introduction of a new account struc-ture—put in place to improve budget planningand analysis capacity—has actually made itvery difficult to analyze anything at a levelbelow emoluments and other spending (ORT).Different divisions/districts put major resourceallocations under different headings, makingconsolidation in a more detailed manner near-ly impossible. It is crucial, therefore, to estab-lish simple, clear guidelines and, especially, toprovide support training (at all levels, especial-ly in the divisions/districts) on the use of budg-eting and accounting. This will ensure consis-tency in recording so analysis is possible at an
aggregate level, and will facilitate comparisonsat divisional/district level.
EMIS. Availability of complete, timely, andreliable education statistics is critical to consis-tent planning of the education sector. The cur-rent computerized EMIS system provides asolid basis, but both the organizational frame-work and the information technology aspectswould benefit from an in-depth review. EMISshould also become more of a functional sys-tem, not just a central database, where data arestored and are used sparingly in decision-mak-ing. An important part of this is informationdissemination from the EMIS to educationstakeholders. The providers of information(i.e. schools) are given an information dividendat periodic intervals. A summary report couldbe published on an annual basis, even in news-papers. The list of potential areas for improve-ment of the EMIS is included in Annex 8.3.
University education
At university level, there are fundamental inef-ficiencies, many of which arise from the smallscale of operations. Enrollment is presently atless than 4,000 students and has shown onlymodest growth during the past decade.Malawi, therefore, has close to the lowest pro-portion of tertiary education students per100,000 inhabitants relative to the whole ofSub-Saharan Africa. The sector needs toexpand access in order to improve the utiliza-tion of existing resources, service the expand-ing education sector and provide more profes-sionals to the workforce.
There are a number of challenges that facehigher education, if it is to expand access andimprove quality and relevance. It must: (i)establish a national strategy and policy frame-work for higher education which will includefunding guidelines, accreditation criteria,establishment of private universities, credithour system and new delivery modes, such asdistance education; (ii) price out the real cost
Critical Challenges and Policy Choices 101
of university education in order to establishstudent financing and support schemes; (iii)revise tuition fees to lessen the government’sfinancial burden; (iv) reexamine the presentpolicy of providing accommodation and feed-ing to students. The linkage of student enroll-ment to bed space, although ignored by somecolleges, needs to be reviewed and the relevantsection in the Act amended accordingly5; (v)make a concentrated effort to implement therecommendations in the MIM Report on out-sourcing of non-core activities. To successfullyimplement this initiative, government will needto develop the required staff retrenchmentpackages.
Realigning policy targets to resources
The Policy and Investment Framework for theeducation sector, developed in the late 1990s,provides an excellent basis for moving for-ward. However, the fiscal and external condi-tions for implementing the PIF have changedsince its preparation. Furthermore, while thePIF is comprehensive it needs to be prioritizedand aligned to existing internal and externalresources as will be demonstrated in the fol-lowing simulation model.6 The model coversthe period up to year 2015, analyzes the long-term financial sustainability of the system, andchecks the realism of the general policy targets.It is based on one possible scenario of targetsand assumptions that were discussed with gov-ernment and it largely reflects the PIF. Howev-er, some alterations were made when PIF goals
were deemed unrealistic in the current macro-economic and social context. The ensuingresults are presented as a basis for discussionwith government and donors. The detailed sce-nario and assumptions are described in Annex8.1.7
Changes in repetition and dropoutrates
If the situation regarding repetition, dropoutand admission rates evolve as described in thePIF, this would result in an estimated primaryenrollment of 3.5 million by 2012. The num-ber of qualified primary teachers needed toachieve the PIF target PqTR teacher ratio of60:1, under this assumption, would be 58,000by 2012. If no changes occurred to the currentrepetition, dropout and admission rate, thenthe estimated enrollment for primary is 4.2million by 2012. The number of qualified pri-mary teachers needed to achieve the PIF target,under these assumptions, would be 70,000 by2012 or 12,000 more teachers. It is clear thatefforts to reduce repetition and dropout ratesare critical in relation to both how many teach-ers will need to be recruited, and which teachertraining model will be pursued. Obviously,both will have an impact on recurrent costsand additional funding required.
Under the ‘in-between’ scenario shownabove, where repetition and dropout rates arereduced gradually (but still optimistically), pri-mary enrollment would reach 3.9 million by
Table 8.1: Projections for primary education: enrollment, repetition, and PqTR, 2001–2015
102 Cost, Financing and School Effectiveness of Education in Malawi
2012 and the expectation would be 59,100qualified teachers (92 percent of all teachers)and a 67:1 PqTR by 2012. The trend in PqTRwould still be downward and the 60:1 goalcould be reached over time because more teach-ers would be trained than would be lost due toattrition. This would assume the stock of qual-ified teachers to be sufficient to achieve a 60:1PqTR, given attrition at maximum 6 percent.This evidently is a more realistic scenario butwill require effective interventions to reduce thenumber of pupils repeating or dropping out.
One very important conclusion concerningthe teacher training model can be derived: ifthe teacher training model reverts to a 2-yearpre-service training program, the number ofgraduate teachers produced every year at theexisting TTC and an additional new TTC, willbe so little that by 2012, only the stock of qual-ifies teachers will be only 33,700, and thePqTR will be as high as 115:1. Even if twoadditional TTCs are built, each with a capaci-ty of 625 students, the stock of teachers willonly reach 40,000 by 2012 corresponding to aPqTR of 96:1.
Political commitment and potentially peda-gogical reasons (although in Malawi the verdictis still out on the latter aspect) could advocate areturn to the pre-service system. However, thefocus now should be on accelerating as much aspossible teacher training, and once the system
has been balanced and the need for new teach-ers reduced, a teacher training program of alonger duration may be considered.
Secondary education and secondaryteacher training
In the scenario shown in Table 8.2, secondaryenrollment can be expected to reach 393,000by 2012, based on the assumption of main-taining GER in secondary at 30 percent.12
Since the GER in the base year (2001) wasalready 29 percent, the growth in enrollmentnumbers will be in line with the growth inschool age population 14–17.13
The Table shows that, in order to achieve aPqTR of 46:1 by 2012, 8,600 qualified sec-ondary teachers are needed. This could beachieved by expanding secondary teachertraining from the current about 400 to 970graduates every year. If the attrition rate ofteachers increases to 8 percent (instead of the 5percent assumed in Table 8.2) as a result ofHIV/AIDS, the PqTR would only reach 53:1by 2012 unless even more teachers are trained.
If, however, the current capacity in second-ary teacher training is not changed and theSSTEP program is phased out beyond its initial3 cohorts, and the capacity of the universitycolleges is maintained roughly at its current
Total enrollment in primary Gross Enrollment RateStandard 6 proxy Completion Rate
0
10000
20000
30000
40000
50000
60000
70000
Expected number of qualified teachers
Expected total number teachers
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Source: Authors’ calculations. Base year data are from EMIS 2001 and ED Data 2002.
Critical Challenges and Policy Choices 103
level, then, by 2012, the system will only haveabout 5,700 qualified teachers resulting in aPqTR of 70:1. The PqTR would not improvefurther, even with an attrition rate of 5 percent.
Finally, if secondary enrollment were toincrease substantially, for example reaching anenrollment of about 600,000 by 2012 (corre-sponding to a GER of about 45%), the numberof qualified teachers needed to achieve a PqTRof 40:1 would be more than 15,000, thusrequiring far more new secondary teachers. Inother words, public demand for secondaryeducation is very likely to increase beyond theexpected capacity to train teachers for second-ary and especially the capacity to pay theirsalaries. If the government does not put clearlimits on publicly funded secondary education,and expand support for private secondary edu-cation, it may face a critical political situation.
Recurrent cost implications
The recurrent costs of education from pursuingthe scenario described above will increase,because of the additional teachers required by2012,19 and due to the incremental cost of hav-ing a larger proportion of qualified teachers.The government may expect to have an aver-age annual recurrent expenditure shortfallbetween now and 2012 of between 11 to 13percent of the total national discretionarybudget, if the education expenditure as a per-centage of the national ‘discretionary’ recur-rent budget is maintained at 21 percent. If theeducation expenditure share were increased to
27 percent (PIF target), then the average annu-al deficit would fall to about 6 to 8 percent ofthe national ‘discretionary’ recurrent budget.
As has been shown above, the model targetsand assumptions indicate that recurrent costimplications of the different policies would belarger than the domestic resource availability.It is clear that MOEST, MOF and the donorcommunity need to determine the realism ofthis type of scenario. For instance, the expect-ed total resources available and the teachersalary costs (both unit cost and total cost) arecrucial issues for dialogue. Other issues, suchas planning teacher training, must not be donein isolation from the general issue of sustain-ability, which centers on the ability to payteachers once they are hired and trained. It isalso crucial to understand what the expecta-tions are in terms of resource availability underthe HIPC debt relief program. The results ofthis financial model can facilitate such a dia-logue. It is clear that the magnitude in thefinancing gaps or shortfall in reaching the setpolicy targets should be used to reopen andredefine targets and priorities.
Possible priority areas of policyintervention
Table 8.3 lists the most urgent policy reforms inthe education sector, as discussed in the variouschapters of this Study. Most of the proposedactions are already known by government anddonors, and have been flagged for the pastdecade. The Table also provides an evaluationof the feasibility of such policy interventions.
Table 8.2: Projections for secondary education: enrollment, PCR, repetition, GER and PqTR, 2001–2015
Source: Authors’ calculations. Base year data are from EMIS 2001.
104 Cost, Financing and School Effectiveness of Education in Malawi
Table 8.3: Possible areas of policy intervention, including assessment of Cost (C), Feasibility (F), Political Risk (P)and Success Probability (S) (low, medium or high)
Policy Options: Policy Options:Objective Medium Term (<4 years) Long term (4 years +) C F P S
Re-balance the • Recalibrate PIF (EFA) goals to • Take a strategic long term view L H M Heducation system financial and human resources and establish caps on public
• Amend Education Act funding for secondary and tertiary education
Re-establish • Establish accountability at • Restructure teacher salary M H M Maccountability, and school level through social provisionsestablish incentives contracting between • Empower headmasters (role in for teachers and communities and schools and promotions and in reprimanding headmasters to transparency systems teachers)perform their duties • Reward/Bonus scheme at • Improve supervision and
school level enabling inspection through an increase communities to reward in ORTteachers • Provide career development and
• Launch public information rotation, especially for rural campaign about the assignmentseducational strategy
• Ensure teachers accept strategies/consensus building
Equitable expansion • Lower repetition and dropout • Target disadvantaged areas and M L L Lof enrollment rates to shorten average of population groups
school completion (automatic • Utilize classrooms and other promotion/cycles of learning school facilities efficiently Standard 1–4) (double shift)
• Target districts or regions with • Use teachers efficiently, redeploy inequitable access using teachers; evaluate and adjust incentives. E.g. Expand food for accordingly the teacher resource education of girls during the requirements under a streamlined hungry season (November to curriculum at secondary levelApril) • Improve incentives for private
provision of education, particularly at secondary level
(continued on next page)
Critical Challenges and Policy Choices 105
Table 8.3 (continued)
Policy Options: Policy Options:Objective Medium Term (<4 years) Long term (4 years +) C F P S
Quality and internal • Redeployment of teachers to • Strengthen in-service teacher C H M Mefficiency ensure adequate availability of training and other teacher improvement teachers at school level as an professional support. Gradually
integral part of the rebuild the pre-service teacher decentralization plans training system in primary (this will
• Targeting of PTR in depend on the output capacity of a Standards 1–4 combined in-service (MIITEP)
• Curriculum Reform: Continue training system and the partial the Primary Curriculum and pre-service system relative to the Assessment (PCAR) process immediate needs for qualified and complete the proposed teachers in the system)review of secondary curriculum • Continue supervision of teachers
• Improvements in the conditions and provide teaching and learning in classrooms, other school materials at primary level, targeted facilities and learning materials provision of teaching and learning through a direct support to materials at secondary levelschool program financed under • Expand enrollment at teacher the development budget training colleges and at university
• Improve community involvement leveland through the DSS program • Implement national policy on lower indirect cost of education mother tongue instruction
• Distribute iron supplements and support de-worming
Efficiency • Appropriate distribution of • Adapt EMIS and funding formulae L M L Lenhancement of teachers according to to meet enrollment changes at public resource enrollment district levelallocation and • Voluntary re-deployment of • Adjust cross sub-sector resource utilization existing teachers with an allocation for future balanced
incentive package or transfer sector developmentof pupils where feasible
• Budget and expenditure framework for all resources/common procedures using GoM systems
Strengthening • Improve data; EMIS, • Strengthen central function of L L L Linstitutional codification of all schools and sector analysis, policy and arrangements and teachers, merging of MOF and planning, and system monitoring capacity for service MOEST salary and financial • Strengthen district-level capacity delivery databases of local system management,
including school inspection, teacher development, monitoring and reporting
• Strengthen management capacity at the school level, including the capacity of School Management Committee at primary level
106 Cost, Financing and School Effectiveness of Education in Malawi
Notes1. 6 percent of youth age 14–17 attend sec-
ondary school in the Southern region, com-pared with 10 percent in the Central regionand 16 percent in the Northern region.
2. It would be crucial to ensure that thisallowance is linked to location, not to teacherso teachers cease to receive the allowance oncethey leave the rural area. This would requirethat appropriate administrative systems be putin place to track teacher’s locations.
3. Bruns, B. et al. 2002.4. It is crucial to review the total benefits
packages (salary plus allowances) when dis-cussing teacher remuneration, particularly asallowances in Malawi represent higher publicexpenditures than the basic salary element.
5. Students currently enrolled in parallel ter-tiary programs pay fees that are closer to thereal unit costs and in this way they are sourcesof revenue for these institutions. Such parallelprograms could include students regularlyattending normal classes—but not in receipt ofpublicly supported boarding—or it couldresult in students attending a completely mod-ified university program comprising distanceeducation and/or usage of facilities during off-time for regular classes
6. The simulation model is based on theEducation For All, Fast Track Initiative modelbut it has been adjusted to reflect the specificsof the Malawian education system, and spe-cially to reflect crucial targets in the PIF docu-ment. The enrollment estimates for primaryare completed separately but they are based onthe simulation model that was used initially aspart of the PIF since it allowed a more detailedestimate using repetition rates and dropoutrates by standard. This simulation model wasprovided by UNESCO, and adjusted forMalawi, with the help of Sussex University. Forkey indicators in the model the assumption ismade that the system moves from the currentsituation to the target value (by the target year)in a linear manner.
7. The model based on EMIS data from2001 projects student enrollment until year2015. Based on the PIF target of a PTR ratio of60:1, certain assumptions of repetition anddropout rates by each Standard and assumingthat two of the six teacher training colleges willrevert to pre-service training while the remain-ing four TTC will continue the MIITEP pro-gram, estimate (i) the recurrent cost implica-tions for pursuing the target of a PTR 60:1 andhiring more teachers and (ii) the share of qual-ified teachers. The model covers primary andsecondary education, primary and secondaryteacher training, and higher education. Theseare most relevant for MoEST, since the recur-rent costs and the human resources availabilitywill most directly influence the sustainabilityof the education system over time by changingsome of the above assumptions. For targetparameters, the PIF targets by 2012 are used,unless indicated otherwise.
8. Public and private9. The number of qualified teachers expect-
ed is a result of the output of the teacher train-ing scenario that is used and of the expectedattrition (assumes all qualified teachers workin public primary schools, not in private ones)
10. The number of unqualified teachersexpected is the difference between the totalnumber of teachers expected and the expectednumber of qualified teachers.
11. The total number of teachers expectedin public primary schools is a result of a grad-ual expected transition from the current 77:1pupil: stream ratio to 60:1 at the end of theperiod, while at the same time the teacher:stream ratio is set to increase from 0.8 at pres-ent to 1 at the end of the period.
12. However, it is worthwhile mentioningthat in case the percentage of students enrolledin private secondary schools (thus withoutrequiring public funding allocation) wouldincrease from its current level, the gross enroll-ment rate could grow beyond 30% withoutoverburdening the public expenditure systemfurther.
Critical Challenges and Policy Choices 107
13. This would however mean that the cur-rent transition rate from primary to secondaryof 74 percent would not be maintained as morechildren pass the PSLCE.
14. Public and private.15. The number of qualified teachers
expected is a result of the output of the teachertraining scenario that is used here and of theexpected attrition. This need for qualifiedteachers is based upon expected enrollment inboth public and private schools, since teachersfor private schools—if qualified—will alsohave to come from the same teacher traininginstitutions. Of course the teacher remunera-tion cost only reflect those teachers teaching inpublic schools.
16. The number of unqualified teachersexpected is the difference between the totalnumber of teachers expected and the expectednumber of qualified teachers.
17. The total number of teachers expectedin public and private schools is a result of agradual transition from the current 36:1 pupil:teacher ratio to 40:1 by 2007, and of theexpected total student enrollment.
18. This is the average for the secondary sys-tem as a whole, i.e. including public and pri-vate schools.
19. About 12,000 primary teachers and2,300 secondary teachers.
ANNEXES
109
ANNEX 1.1
Evolution in population, GDP, totalgovernment revenue and expenditure
Overall balance after grant (current million MK) –187 –874 –515 –2377 –1441 –1063 –3278 –3158 –5117 –6070 –10493 –11921
Sources: IMF “Selected Issues and Statistical Appendix. August 2002”; WB SIMA database; and authors’ calculations. The data for 2001/02 and 2002/03 are estimatesfrom IMF “First Review under the Poverty and Growth Facility and a Request for Waivers of Performance Criteria. August 2003”. Population data are from WB-HNPStats. Inflation and exchange rates are from IMF as referenced in PER.
Annexes 111
90
100
110
120
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
GDP per capita in constant USD, indexed to 100 for the year 1982
Source: World Bank—SIMA database.
ANNEX 1.2
Government expenditure by functionalclassification, in percentages
Source: Discretionary spending and its components are from different years of the Economic Report. Note: Till 2000/01 all are ‘actuals’, thereafter ‘revised’ estimates.
ANNEX 2.1
Nursery school attendance
114
Percentage who Mean Number of Years Background Characteristics Attended Nursery School Attended Nursery School
Sources: – Population Census data are from ‘1998 Population and Housing Census – Analytical Report’ (www.nso.malawi.net), and for 2000 thedata are provided by Jameson Ndawala (Chief of Demographics Department – NSO)– School census data: Basic Education Statistics of the corresponding years. – IHS 1998: authors’ calculations using dataset. – DHS 2000: “Malawi Demographics and Household Survey – Final Report. August 2001”– Ed Data 2002: ‘Malawi DHS EdData Survey: Preliminary report’– NSO – adjusted population estimates: NSO website under ‘Data/Malawi Population Projections’.– UNESCO population estimates: World Bank SIMA database connecting to UNESCO Education Statistics.– UN–EFA population estimates
igure 2.3 shows enrollment rates in pri-mary by age group using three differentdata sources.9 The results after combin-ing school census data and population
data from both sources are different from theresults suggested in the household surveys.10
This implies that the number of over-aged chil-dren is much higher in the primary educationsystem than what the official school census sta-tistics records. The enrollment rates of over100 percent, found for the age group 7–10years olds, are actually largely because of themany under-aged children being registered. Asfar as the under-age children in primary areconcerned, the survey results show that closeto 30 percent of the population, aged 5, arealready enrolled (representing close to 100,000children) whereas school census data puts this
estimate at 15 percent.11 This probably arisesbecause parents claim their children are olderthan they actually are so they may avoid theproblems associated with official policy andcontinue to attend primary school. These dis-crepancies in the recorded ages of children isfurther complicated by the fact that the chil-dren themselves, possibly as a result of peer-pressure, may indicate an age closer to the‘normal’ age for that standard—or at leastwithin the most common age range indicatedby their classmates. The first table below is theequivalent of Figure 2.3, but for year 1998.The second table shows the similarity betweenthe results from the two completely independ-ent household surveys in 1998 and 2000. Thisstrengthens the case for the reliability of theresults from these household surveys.
ANNEX 2.3
Enrollment by age comparing householdsurveys and school census
116
F
Annexes 117
Enrollment rate in primary by age, different sources, 1998
Sources: Authors’ calculation using data from the IHS 1998 survey, the DHS 2000 Survey, and from the NationalStatistics Office and UNESCO for population estimates.
ANNEX 2.4
Analytical review of entry rate to standard 1
bviously, in an expanding system,one moving towards universal cov-erage, the issue of children beingover-aged due to late entry, or repe-
tition, is commonplace. This was the case inMalawi. Primary fees were abolished in 1994and the number of new entrants (i.e. those whohad not yet entered school) increased signifi-cantly—in fact, it approached universal cover-age relative to the population group. Thisincrease was short-term (the ‘big bang’ effect)and in subsequent years an increasing propor-tion of children of appropriate age entered thesystem. Therefore, it should not be possible tocontinually have more “new” entrants thanchildren in the population group of normal ageof entry by the year 2003—almost 10 yearsafter the introduction of FPE.12
It follows that the 2.29 rate of entry, notedin 1998, is not logically possible13; it suggestspossible confusion in: (i) an over-count of totalenrollment; (ii) the definition of new entrantsinto Standard 1 versus repeaters; and/or (iii) anunder-count of school-age population. Sinceenrollment data is obtained through headteachers (both for the school census or in sep-arate studies14), and no other source is avail-able, clarification of the level of error related toover-count of enrollment is not possible. How-
ever, in the following section, possible explana-tions for the discrepancies in recorded repeti-tion and population estimates will be reviewed.
The table below indicates that repetitionrates recorded in the DHS 2000 and EdData2002 were much higher than the repetitionrates recorded by the number of repeaters ver-sus total enrollment in the Basic Education Sta-tistics. For primary, as a whole, there is a dif-ference of at least 10 percentage points, and forstandard a difference of approximately 20 to25 percentage points.
One explanation for discrepancies in record-ed levels of repetition may be connected to thedefinition of ‘repeater’. In the household sur-veys, a repeater is either a child that completeda school year and then repeated the same stan-dard the following year, but it can also be achild that interrupted his/her schooling duringthe school year but subsequently returned tothe same standard in the following school year.The latter occurrence may be quite common,particularly in Standard 1, as children maystart but later be considered too immature forStandard 1, drop out but return the followingyear. Although head teachers were not provid-ed with specific instructions, it is acknowl-edged that in the school census, only childrenwho completed the year in school and are not
118
O
Annexes 119
considered sufficiently mature to progress tothe next standard are recorded as repeaterswhile children who left during the year andreturn to the same grade the next year are reg-istered as new entrants again.
The definition of repeaters may vary, but ininternational comparisons the accepted defini-tion is a child who takes up the teachers timeand absorbs resources. Furthermore, to meas-ure efficiency in resource usage, it is logical toseparate the children returning the subsequentyear to the same grade from the real newentrants. Otherwise, if PTR is based on enroll-ment numbers at the beginning of the year, thepublic expenditure will be incurred twice and,as a result, more teachers will be assigned onthe basis of the children who begin the schoolyear, but who subsequently drop out. The dataanomalies between household surveys andschool census data might also be explained bya separate factor: teachers have no system toestablish whether or not a child has been pre-viously enrolled in school. In such a situation,children may be incorrectly listed as enrolled ina grade for the first time.15
If the repetition rate from the household sur-veys is applied to total enrollment in Standard1, as found by the school census statistics (seeTable below, point (b)), then the cohort rate ofentry reduces from 2.29 to 1.60 (160 per-cent).16 The 1998 population census could also
be underestimating the total number of chil-dren of the corresponding age. Using a high-end population estimate for Malawi from UN-EFA (United Nations-Education For All), thecohort rate of entry is further lowered to 1.33(see Table below, (c)).
With a cohort rate of entry to Standard 1 of1.33 for 1998 (and of 1.39 for 2000), there isstill significant unexplained variance. Howev-er, given the lack of alternative data, in partic-ular in enrollment numbers, the cohort rate ofentry of 1.33 (for 1998) and 1.39 (for 2000)will be used as the most credible estimate.
Population in the 1998 population censusmay have undercounted the actual populationat the entry age to primary. Three scenarioswere compared:
(i) original 1998 population census whichrepresents an annual growth rate forthe 6–13 age group of 1.4 percent17
since the previous population censusfrom 1987;
(ii) high-end population estimate (UN-EFA) which represents an annualgrowth rate for the 6–13 age group of2.7 percent18 between 1987 and 1998;
(iii) using the same annual growth rate of4.9 percent between 1987 and 1998, as
Comparing repetition rates using different sources, 1998, 2000 and 2002.
1998 2000 2002
School census based estimatesPrimary total 14.5% 15.6% –Standard 1 18.2% 19.2% –
Household surveysDHS 2000
Primary total – 29%* –Standard 1 – 45.3% –
EdData 2002Primary total 25.8%Standard 1 – – 40.6%
Sources: Authors’ calculations, using Basic Education Statistics 1998 and 2000.“Malawi Demographics and Household Survey – Final Report. August 2001.”Ed Data 2002: ‘Malawi DHS EdData Survey: Preliminary report’.* Authors’ calculation using DHS 2000 dataset.
120 Cost, Financing and School Effectiveness of Education in Malawi
was recorded between 1977 and1987.19
Under scenario (iii) the estimated populationof age 6–13 would be 3,118,14220 for 1998 or3,439,19521 for 2000. With an enrollment inprimary of 2,805,785 in 1998, and 3,016,972in 2000 according to the school census, thiswould give a GER of 90.0 percent in 1998 andof 87.7 percent in 2000, which is significantlybelow the GER found by the household sur-veys, and therefore not very plausible.
Also, as can be seen from the table below,the annual growth between 1977 and 1987 is
at the very high end given the historic popula-tion data for Malawi. According to the NSO,two specific factors contributed to the morethan average population growth from 1977until 1987 and to lower population growth inthe period from 1987 until 1998. First therewas the influx of Mozambican refugees duringthe civil war and the then returning in the peri-od thereafter. For instance, annual populationgrowth rates at district level show that popula-tion in the districts that lie along the borderwith Mozambique grew with the slowestrates.22 This suggests that the repatriation ofMozambican war refugees who were concen-trated in these districts during the 1987–1998intercensal period had an impact on thegrowth of the population. The second factor isthe impact on population of the AIDS crisis,slowing the growth rate.
Given the fact that UN-EFA estimates takethe previously mentioned factors into account,additionally to using advanced demographicmodeling, based upon a longer historic trend,this will be considered the most plausible pop-ulation estimate and will be used. Using thepopulation from UN-EFA and the householdsurvey repetition rate, the cohort rate of entrywould be 1.3323 in 1998 and 1.395 in 2000.24
Entry rate to standard 1, different data sources
Enrollment Population Cohort rate of 1998 situation standard 1 New entrants age of entry entry
(a) MoEST enrollment and 1998 population census data 751,002 638,865 278,438 2.29
(b) MoEST enrollment, but survey average repetition rate (42.9% standard 1), and 1998 population census data 751,002 441,087 278,438 1.60
(c) MoEST enrollment, but survey average repetition rate (42.9% standard 1), and UN-EFA population 751,002 441,087 330,900 1.33
Source: MLA 1999. With Africa for Africa: Towards Quality Education for All.
ANNEX 2.6
Factors in primary school pupil dropout(from Ed Data 2002)
122
Percentage of de jure children age 5–14, who had dropped out of school, 2002.
Cost-related factors Child factors School factors
Long- School No Background Monetary Labour Repeat / Enough term School travel Poor places in No characteristic cost needed exam fail school illness Disabled too far unsafe quality secondary jobs
Note: More than one response possible. Questions were asked about a total of 284 children who had dropped out of school. First, the parent/guardian was asked whether a child had dropped out because (s)he was physically or mentally disabled, and if the answer was yes, no furtherquestions were asked about reasons for leaving school. Next, the respondent was asked whether a child had dropped out because (s)he hadbeen very sick for 3 months or longer, and if the answer was yes, no additional questions were asked. There were 16 children who had droppedout because of a disability and 33 who had left because of long illness, so for the remainder of the questions, the sample size was only 237.
ANNEX 2.7
Survival rate in primary, different methods and moments in time
n the table below, different methodsand years to calculate the survival ratesfor primary education are used.25 Theyindicate that there is a decline in the
number of pupils surviving through to the endof primary in the years prior to FPE (28–30percent) relative to recent years (24–26 per-cent) when using a simplified cross sectionalapproach. Based on the results from the quasi-time series survival estimates26, a similar,albeit more stark, picture emerges: it indicatesthat a student’s chances of “survival” through-out primary went down from 41.5 percent in1989/91 to 22.9 percent in 1998/00.
In this context, it is important to highlightthe likely impact of the FPE policy, since afterits introduction enrollment increased by morethan one million pupils. Here, both the cross-sectional method for recent years and the full-time series method are likely to be distortedby this major enrollment surge that has yet tobe reflected in analysis across all grades. Thefull-time series perspective indicates a figureof 44.9 percent from 1989/90 to 1999/0028
and this, in effect, reflects the position priorto FPE. Those in Standard 8 in 1999/00 werenot very affected yet by the FPE policy,because the huge increase in the number of
41.5% !-------- quasi-time series method --------" 22.9%
Source: School Survey Data in EMIS 2000 for enrollment and repetition rates,27 NSO population estimates.
124 Cost, Financing and School Effectiveness of Education in Malawi
children who entered in 1994 as a result ofFPE were primarily in Standard 1. The quasi-time series calculations for 1998/00, usingdata from only two consecutive years, is not
distorted by the FPE policy29 It thereforemore accurately reflects the situation a fewyears before, and after, the FPE policy.
ANNEX 2.8
Survival rates for primary and secondaryusing different data sources
The pattern of access and survival (cross-sectional method), 1999/0030
Intake rate to the grade31 Survival Rates (%)
Student in grade 1 129.9 100.0Student in grade 4 93.1 71.7Student in grade 5 82.9 63.9 Student in grade 8 33.0 25.4 Student in form 1 29.5 22.7 Student in form 2 30.5 23.5 Student in form 3 23.7 18.3 Student in form 4 17.1 13.2
Source: School Survey Data: in EMIS and Basic Education Stats, 2000. DHS 2000 for repetition rates, UN-EFA population. The non-repeaters arecalculated using the repetition rate from DHS 2000.
The pattern of access and survival (cross-sectional method), 1999/0032
Intake rate to the grade Survival Rates (%)
Students in grade 1 217.3 100.0Students in grade 4 108.0 49.7Students in grade 5 97.7 44.9Students in grade 8 53.1 24.4Students in form 1 33.6 15.5Students in form 2 35.1 16.1Students in form 3 26.2 12.1Students in form 4 22.7 10.4
Source: School Survey Data: in EMIS and Basic Education Stats, 2000, also for repetition rates. NSO population estimates, version from Oct 2002.
125
ANNEX 2.9
Proxy primary completion rates for standards 4, 6 and 8
and international comparison
126
Grade 4 proxy
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Grade 6 proxy
0.0%
20.0%
40.0%
60.0%
80.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Annexes 127
Grade 8 proxy
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Source: Basic Education Stats, NSO population; Highest level is standard NSO population. Lowest level is using NSO population plus 15%.(UN-EFA population is not available this far in the past).
Primary GER and completion rates for selected African countries, 1997–2000
Source: Bruns et al. 2002. Note: The numbers are related to the entire primary cycle – or to the first 6 grades, whenever primary is longer than 6grades.
ANNEX 2.10
Highest grade of instruction offered in primary, and walking time
and distance to the nearest school
128
Distribution of primary schools by highest grade of instruction offered, 1999/00
Number of schools Non-repeaters (new entrants) in Standard 1
Highest grade of Long Recently Long Cumulative Recently Cumulative instruction offered established established established share established share
(i) Government Day Schools and GovernmentBoarding Schools: Operated and fundeddirectly by Government through EducationDivision Offices.
(ii) Grant-Aided Schools: Operated by churchorganizations with Government contribu-tion to teachers’ salaries and monthlygrants for day-to-day running costs. Stu-dent tuition and boarding fees are cumula-tively much higher than in governmentschools.
(i) and (ii) together are also called Convention-al Secondary Schools (CSS)
(iii)Community Day Secondary Schools(CDSSs): Mostly established and financed
by School Committees but in receipt ofsome government funding to supportteacher and staff salaries and assist day-to-day administration requirements.
(iv) Private Schools: Owned by private individ-uals, or non-governmental organizations,in receipt of no government grants andcharge economic fees.
(v) Malawi College of Distance Education(MCDE) and Night Schools: Cater for full-time workers or adults interested inimproving their academic qualifications. Inaddition, youths who fail to secure a placein other secondary institutions can opt tojoin the MCDE.
129
ANNEX 2.12
Technical and vocational training description
raditional public technical and voca-tional training in Malawi consistmainly of two types: an apprenticeshiptraining system; or full-time institu-
tional training. They have been limited in scope;they only enrolled 1,500 students in the com-bined programs up to the end of the last decade.
Between the years 2000–2003, the Ministryof Labor and Vocational Training indicatedthat a total of 1,723 male and 883 female stu-dents have graduated from the public Techni-cal Colleges, as follows: 936 in ‘construction’;780 in ‘commercial’; 540 in ‘automobile engi-neering’ and 350 in the field of ‘engineering’.So despite the large increase during the lastdecade, the absolute numbers are still smallcompared to enrollments in secondary educa-tion and primary education.
The apprenticeship combines on-the-jobtraining by industry with institutional trainingby seven Technical colleges—all managed bythe Ministry of Labour and Vocational Train-ing. It is a four-year training scheme and isoffered in a significant number of technical
trades. The full-time institutional training pro-grams take place in some of the technical col-leges and they provide courses to cover thesame range of technical trades.
A range of courses are available at the pub-lic technical colleges. These include: bricklay-ing, carpentry & joinery, painting and decorat-ing, plumbing, wood work machining (as acomponent of ‘construction’), bookkeepingand accounts, secretarial, ICT, auto electrics,motor vehicle mechanics, vehicle body repairand refinishing under ‘automobile engineer-ing’; and electrics/electronics, general fitting,welding and fabrication.34
Since 1999, a new TEVET Act has becomeeffective and it also established an independentsecretariat called Technical, Entrepreneurial,Vocational Education and Training Authority(TEVETA). The main aim is to link Technical& Vocational Training more closely with theprivate sector by promoting a demand driven,modular, technical and vocational training sys-tem; monitoring gaps between supply anddemand; supporting the application of appro-
130
T
Enrollment in public technical & vocational colleges
Year 1991/92 1993/94 1995/96 1998 1999 2000 (estimate)
Enrollment 840 1007 1054 1308 1290 1504
Source: Basic Education Statistics.
Annexes 131
priate technologies; and promoting managerialand business skills and a spirit of entrepre-neurial culture in respect to both wage andself-employed personnel.
Funding for this new approach is innovative inthe Malawian context. Since the fees paid bytrainees do not cover the economic cost of thetraining provided, additional funding is generatedin two ways. Firstly, the training provider institu-tions arrange various parallel income-generatingactivities and secondly, a TEVET fund has beenset up into which private sector and governmentemployers pay a 1 percent payroll-levy. It is alsointended that the funding will be further topped-up through additional available HIPC debt reliefand cooperating partner support.
In addition to assuming responsibility forthe traditional technical colleges, TEVETA alsosupports staff training programs for privatesector employees and it reimburses part of thetraining costs incurred by the employer forapproved training. This scheme benefited 259employees from 13 companies in 18 coursesbetween July 2002 and June 2003. TEVETAconducts a number of other training programswhich use local masters, for instance, in car-pentry, cane furniture production, etc. and it isintended to increase the range of availablecourse still further. On completion of all cours-es official certificates are issued.
The box below provides a typical exampleof the ad-hoc training supported by TEVETA.
Example of training scheme supported by TEVETA
In an effort to promote skills training for unemployed people, four partners are workingtogether. First there is the German donor KfW, which supports the construction activities ofincome-generating urban infrastructure, such as craft centers, markets, bus stations, commer-cial areas, etc. They contract construction companies and make training activities a part oftheir tender papers. The selected construction company, as another partner, is responsible forproviding skilled laborers who will implement the training. The company contracts trainees,for three months, who are entitled to receive a wage lower than the skilled laborers.
The town assemblies of the smaller urban centers where the infrastructure works are takingplace form a third party in the initiative. They are responsible for the selection of young peo-ple to serve as trainees, for example, school dropouts or unemployed.
TEVETA has the overall responsibility for ensuring a consistent quality assurance system isin place. The training staff and the site agents of the construction companies have participat-ed in a seminar on how to conduct the training and assessment and TEVETA developed theassessment documentation. In order to ensure greater public confidence and confirmation ofthe internal assessment results, external assessors from industry, and from private and publictraining institutions, have been trained and contracted by TEVETA. The assessment results areforwarded to TEVETA to validate and certify the candidates. The training participants can alsogain credits and build up a national, recognized qualification if they wish to extend the train-ing with other providers.
TEVETA also attempts to implement similar training arrangements with other industrialpartners or donor agencies. It is currently in discussion with DFID on how to include this ini-tiative in their school construction program and with the World Bank MASAF program whichfunds construction and rehabilitation projects with community participation.
Source: “Promotion of non-formal Technical Entrepreneurial Vocational Education Training components in Malawi” by TEVETA.
ANNEX 3.1
Recurrent and development expenditures at real prices
Source: PER for data until 1998/99. For 1999/00, primarily from Basic Education Statistics. For 2000/01, from ‘Consolidated annual appropriationaccounts’.
ANNEX 3.2
Recurrent, development and totalexpenditure by sub-sector over time, in real
Sources: PER for data until 1998/99. For 1999/00, primarily from Basic Education Statistics. For 2000/01, from ‘Consolidated annual appropriationaccounts '. For 2001/02 and 2003/03 the data are ‘approved estimates’ from FOM Draft Estimates of Expenditure and Financial Statements.Note: it is important to remember that the percentages from 1998/99 onwards for development expenditure and total expenditure are notcompletely comparable to the years before, seen no data is available on development expenditure for sub-vented organizations.
ANNEX 3.3
International comparisons of unit costs
135
Public spending as a multiple Public spending as a multiple of of per capita GNP spending in primary education
Number of Region35 countries Primary Secondary Higher Secondary Higher
Source: Mingat and Suchaut (2000) for the regional values, with data from 1993. World Bank Sector Studies for individual countries, with datafrom 1998. For Malawi authors’ calculations, using 2000/01 actual expenditure data. Note: For higher education, refers to per-student spending intraditional public institutions.
ANNEX 3.4
Nominal per pupil expenditure by sub-sector (current USD)
Source: PER and authors’ calculations. For university 93/94 – 96/97 is from PER, thereafter authors’ calculations using official enrollment,exchange rate, and actual expenditure data received from UNIMA (thus this does not include Mzuzu University).
ANNEX 3.5
Decomposition of 1999/00 and 2000/01 education sector
development expenditure by source
137
1999/00 Education Sector Development Expenditure
% of % of Develop-Part I: dev Part II: dev ment % of Bilateral % of % of
Program Loans bud GoM bud budget total (Estimate) total Total total
Source: PER for 1999/00 and for 2000/01 off-budget estimates. For 2000/01, from ‘Consolidated annual appropriation accounts'.
ANNEX 3.6
Off-budget bilateral grant support for education
138
Disbursed 2002 Project Years Currency Cost (mill.) to date disbursement
Primary EducationUSAID Quality and Efficiency 2001–06 US$ 22.0 10.5UNICEF School health and hygiene 2002–06 US$ 2.4 1.3KFW Physical infrastructure 1997–2004 Euro 13.8 12.0 2.9DFID Sector support program 2001–07 Sterling 61.0 1.7Netherlands Sector support program 2001–07 Sterling 17.7 2.2WFP mid-day meals 2002–06 US$ 7.7
Primary and SecondaryGTZ Teacher education/curriculum 2002–05 US$ 4.7 0.6CIDA Textbooks 1999–04 US$ 15.0CIDA Trained teachers for CDSS 1999–04 US$ 5.0
ANNEX 3.7
Examples of potential problems from extra-budgetary funding and
uncoordinated donor financing
he externally financed textbook initia-tive costs US$4.80 per enrolled pri-mary student36; this figure can be com-pared to the current US$2.70 per
student provision for teaching learning materi-als. However, inclusion of a similar level oftextbook provision would raise expenditure onteaching-learning materials by 1.8 times andresult in substantial increases in the recurrentbudget. As such, the financing of textbooksthrough extra-budgetary grants, artificiallylowers the cost to the government—and to therecurrent budget—but it also results in a fail-ure to explore more cost-effective, and sustain-able, strategies to provide textbooks. Since aregular supply of textbooks is obviouslyimportant if the quality goals, outlined in thegovernment policy documents, is paramount.
This should include a more detailed analysis ofsustainable textbook provision, includingexamination of the book chain and measuresto improve writing, publishing, printing anddistribution. The second example relates toconstruction costs and illustrates how uncoor-dinated donor funding can undercut efforts tofind cost-effective strategies that might eventu-ally become domestically sustainable. As thetable below shows, the cost of constructing oneclassroom, a single pit latrine and a borehole,varies from one donor project to another. Forexample, the Malawi Social Action Fund(MASAF) uses a community based approachand is about 30–60 percent cheaper—althoughthis lower cost may hide (i) in-kind contribu-tion by communities, (ii) variance in standardsand (iii) likely lifespan.
Source: January 2003, "Review of cost Effectiveness and Design Standards." EMC Jatula Associates, Malawi (in “PAD – Third Social ActionFund.” Report 25562–MW. April 2003)
ANNEX 3.8
Household monetary contribution toprimary education as a percentage of
Sources: Authors’ calculations using Malawi, Uganda, Zambia DHS EdData Survey 2001 for household (HH) education spending. For Kenyaresults are from WB education sector review draft “Education and Training in Kenya” from 2003 using DHS 1998 input data. ** In the case ofKenya this represents the results for both primary and secondary education and not just for primary. The number in parentheses indicateseducation expenditure as a % of only non-food expenditure.
ANNEX 4.1
Index of efficiency for primary
To indicate how the efficiency index is calcu-lated, it is convenient to use a pseudo cohort of100 pupils entering Standard 1 and see howthey progress. As shown in the table above, itis estimated that 33 eventually will survivethrough to Standard 8. To produce these 33students in Standard 8, it would have been nec-essary theoretically to finance 261 (32.6x8)years of schooling in absence of repetition anddropouts.
However, in reality the system requires alarger number in early grades that progressive-ly shrinks as grades evolve. The consequence isthat to finally produce the 33 pupils in Stan-dard 8, the system has to finance in each gradethe number of survivors until that level,increased by the repeaters. For instance inStandard 1 that would be 145, as a result of100+(100*45.3%); or in Standard 5 thatwould be 69, as a result of the 60 survivors
Sources: EMIS 2000 for enrollment, DHS 2000 for repetition rates, UN–EFA for population• Promotion rate = non repeaters in grade X+1 in year 2 divided by total enrollment in grade X in year 1• Repetition rate (as used in DHS2000) = percentage of students in a given grade who are repeating that grade• Dropout rate = 1 – Promotion rate – Repetition rate• Cumulative dropout year 2 = Cumulative dropout year 1 + Yearly dropout• Yearly dropout in year 2 = dropout rate in year 2 * (100 – Cumulative dropout year 1) • Survivors year 2 = 100 – Cumulative dropout year 1(Calculating the yearly dropout is a step that is required because the absolute numbers of dropouts as a result of the same dropout rate instandard 5 for instance will be lower than in standard 1, seen we are already dealing with a lot fewer pupils in the system)* The slightly negative value here is a result of combining data from two different sources, i.e. enrollment from the school census and repetitionrate from the DHS household survey.
142 Cost, Financing and School Effectiveness of Education in Malawi
until this level plus the repeaters 60*15.2%.Summing this over all the grades for primary,this would give a total of required actual yearsto finance of 657 to ultimately produce the 33students in Standard 8.
Dividing the number of school years the sys-tem effectively needs to finance to producethese 33 Standard 8 students by the theoreticalnumber of years (261), we get the efficiencyratio (a value of 1 would describe a systemwithout dropout nor repetition). The index ofoverall efficiency in the case of Malawi is 39.7percent, indicating by complement to 1, that60.3 percent (100–39.7) of the publicresources are used on children who never fin-ish primary or on repetition years (even ofthose who eventually finish).
Additionally, it is possible to look at whatwould be the situation in case there would be
no repetition in the system (only drop-out). Inthat case, to produce the 33 pupils in Standard8, the system has to finance in each grade thenumber of survivors (not loaded by the repeti-tion rate). For instance in Standard 1, thatwould be 100; or in Standard 5 that would be59.8. Summing this over all the grades for pri-mary, this would give a total of required actu-al years to finance of 523 to ultimately producethe 33 students in Standard 8. Therefore theefficiency ratio in this case would increase to49.9 percent.
It is also possible to look at the differencebetween the number of years required underthe previous two scenarios (657 and 523). Thisgives an indication for the efficiency of a sys-tem where no dropout would exist but only theactually existing repetition would remain. Thisefficiency is 79.6 percent (523 / 657).
ANNEX 4.2
Allocation of teachers in public primaryschools in each individual district, and pupil
teacher ratio by district, 2000
District No. of schools Randomness PTR PTR qualified teacher
Source for randomness: authors’ calculations based upon EMIS 2000.Source for PTR and PTR qualified teacher: Basic Education Statistics 2000.Note: The values in parentheses are less reliable, because they represent very few schools and as result even very few schools that areextremely different from the norm can significantly influence the overall result.
ANNEX 4.3
Current teacher deployment process in primary
he inequities in teacher deploymentresult from inadequate enforcement ofexisting policies and a need to improveexisting policies, particularly at the dis-
trict level where the recruitment of teachersneeds to take account of the following:
• Pupil–teacher ratio (objective 60:1);
• Teacher attrition due to retirement, deathand resignations;
• The assignment of teachers to newly com-pleted schools on the basis of the numberof classrooms and standard classroom/teacher ratios.
However, the above criteria, especially thepupil–teacher ratio, are not fully applied,because there are recruitment constraints setby:
• The amount of finances allocated to theeducation sector for man power develop-ment by both the Department of HumanResource Management and Development(HRMD) and the Ministry of Financeeducation sector; and
• The budgetary ceilings allocated to per-sonal emoluments for the different levelsof education.
Once districts have prepared their teacherrequirements, the information is circulated tothe division for consolidation. Thereafter, thedivisions pass district teacher requirementsdata to the HR services section of the MOESTfor further consolidation and an estimation ofnational teacher requirements. These nationalteacher needs are then submitted to theHRMD, Ministry of Finance, Office of thePresident and Cabinet. If all three departmentsapprove these numbers, then MOEST’s HRservices section sends the information to theTeacher Service Commission (TSC) and theyinitiate the recruitment process by instructingthe districts to recruit.
At the district level, a district manager has toapprove all transfers where a teacher is accom-panying a spouse.37 Although most district man-agers endeavor to reflect local PTRs, they arepersistently pressurized by families who wish toremain together when a spouse is relocating (typ-ically from rural to urban areas). Furthermore,teachers appear to apply pressure through vari-ous networks and thereby make it even more dif-ficult for the DEMs to manage deployment in an
145
T
146 Cost, Financing and School Effectiveness of Education in Malawi
impartial manner. Indeed, at times, teachers donot report that they have moved.
In addition, teachers employed at centrallevel can work anywhere in Malawi. For exam-ple, if teachers wish to transfer from one dis-trict to another, they do not need to resign—even if it is known that the district they aregoing to has already achieved the requiredPTR—and this practice results in a dispropor-tionate number of teachers in urban schools.When this happens, the budgetary salary allo-cation follows these teachers wherever they gorather than remaining with the district that ini-tially hired these teachers.
The reasons for the inconsistencies indeployment practices among individualschools within single districts are not fullyclear, but issues that motivate this frequentmobility are: spouse relocation considerations;a desire for improved access to roads and facil-ities; lack of housing or incentives to remain inremote rural regions; and lack of promotionalopportunities. In addition, the lack of knowl-edge or information sharing by schools andPTAs about the situation in other schools inthe district, or about the existence of powers toredress the situation for individual schools,may be equally significant.
ANNEX 5.1
Percentage of pupils in standard 6 reaching minimum and desirable
mastery levels in reading literacy, 1998
147
Minimum DesirableMastery Level Mastery Level
% %
GenderBoys 24.3 0.7Girls 18.7 0.6
Socio-Economic Level38
Very Low (0–2) 14.4 0.0Low (3) 14.0 0.6High (6–7) 27.3 0.8Very High (8–9) 32.4 3.1
School LocationRural 19.7 0.2Small Town 19.9 0.0Large Town 43.8 5.0
Malawi 21.6 0.6
Source: SACMEQ Study, 2001.
ANNEX 5.2
AIDS/HIV
he table below summarizes the resultsand impact on teachers over a 10-yearperiod, with and without HIV/AIDS,and with negative impact on repetition
and dropout rates. The growth rates for thetotal and the school-age population areassumed to be 2.2 and 3.0 percent, respective-ly, in the absence of HIV/AIDS.39
The attrition rate, without AIDS, reflectscurrent attrition rates due to retirement, death,or changes in employment. But HIV/AIDS willimpact on women’s fertility and mortality ratesand result in lower growth rates in the popula-tion of school-age children. As a result, fewerteachers will be needed to maintain the ratio ofpupils per teacher. For example, instead of
requiring 75,600 teachers by 2014, only73,600 teachers will be required because of theslightly smaller school-age population. Thisscenario assumes that with the current growthin the school population (3.2 percent in 1987and 2.2 percent in 1998), the number of teach-ers would need to increase from 50,000 in2000 to 75,600 by 2014—an increase of25,600. However, because HIV/AIDS alsoaffects the mortality rate of teachers, thereplacement of teachers due to deaths causedby AIDS will need to double by 2014—fromapproximately 3,000 teachers under normalattrition conditions to 6,500 teachers due tonormal attrition combined with the impact ofAIDS.
148
T
Increases or decreases in school enrollment, teachers under three AIDS scenarios from 2000 to 2014 assumingsteady state (no changes in pupil teacher ratio (PTR))
With AIDS and adverse impact on repetition
Without AIDS With AIDS and drop out rates
School Population + 1,500,000 +1,400,000 –100,000Total teachers 2000 50,000 50,000 50,000Total teachers 2014 75,600 73,600 48,300Total increase in teachers +25,600 +23,600 –1,700Teachers requiredper year +3,000 +6,500 +3,700
Source: 2001 study “The Impact of HIV/AIDS on Primary and Secondary Schooling in Malawi: Developing a Comprehensive Strategic Response.40
World Bank calculations.
Annexes 149
Evidence from the HIV/AIDS pandemic inUganda, Malawi, and Zambia suggests thatthe growth rates in both total and school-agepopulation will decline. Both populationgroups will grow at a slower pace, althoughgrowth of the school population will remainalmost unchanged. It is assumed that the attri-tion rate due to death from AIDS will increasein the region of 3 percentage points to 7 per-cent. Therefore, it is calculated that during theperiod 2000 to 2014, government will need toincrease the annual replacement of teachers by100 percent because of deaths from AIDS. Thisphenomenon clearly has important implica-tions for the development of the pre- and in-service teacher training systems and the issue isdiscussed in the main body of this report.Finally, the total number of teachers that willbe required by 2014, and the recurrent costimplication, appear largely neutral; howeverthe cost and training implications for thereplacement of these teachers is enormous.
The 2001 study41 estimates that the schoolage population will actually decline from itscurrent level of approximately 3 million pupilsto 2.8 million pupils. This decline reflects thenegative impact on repetition and dropoutrates, as described in the last scenario. It also
reflects the adverse effects on attendance, theincreasing number of orphans and the growingpoverty—especially during the hungry sea-son—as a result of HIV/AIDS. Furthermore,the many orphaned and impoverished childrenwill not have access to education under thecurrent framework and support mechanism.Based on this scenario, namely, maintaining aconstant PTR with no improvement in theretention rate, the number of teachers requiredwill actually fall by 1,700 teachers to a total ofapproximately 48,300. Consequently, govern-ment will need to recruit additional teachersbut on a smaller scale. In effect, an additional700 (total + 3,700 p.a.) new teachers need tobe recruited annually to replace the teacherswho have died from AIDS. The negative con-sequences of both the annual training and thereplacement of teachers, as well as improvingthe retention and access of an increasing num-ber of children who will be orphaned, has sig-nificant implications for attaining universalprimary education in Malawi. Furthermore,the teaching and learning conditions for stu-dents who actually attend school will undoubt-edly be adversely affected by the higher level ofteacher and student absenteeism because of ill-nesses and increasing opportunity costs.
150
ANNEX 6.1
Relative gender gap and GER in the different districts, 2000
Source: Basic Education Statistics and UN-EFA population.
ANNEX 6.2
Estimated survival rate by gender in primary and secondary, 2000
(cross-sectional method)
151
0.010.020.030.040.050.060.070.080.090.0
100.0
1 2 3 4 5 6 7 8 9 1 0 1 1 1 2boys girls
Source: EMIS for enrollment, DHS2000 for repetition, UN-EFA population.Note: The last point of measurement is the new enrollment (non-repeaters) in form 4, NOT the MSCE passers.
152
ANNEX 6.3
Completion rates for standards 6 and 8(PSLCE passers), by gender
Standard 4
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
120.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
YYYY eeeeaaaarrrr
Boys
Girls
Standard 8
0.0%
20.0%
40.0%
60.0%
1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
Perc
ent
Boys
Girls
Perc
ent
Source: Basic Education Statistics for enrollment and repeaters, and NSO population.Notes: ‘Proxy’ completion is calculated as the number of non-repeating students in Std. 6 divided by the corresponding age cohort. UN-EFApopulation is not available this far in the past, nor are household surveys for repetition rates. However, seen that the goal is to look at relativedifference in completion by gender, the potential shortcomings in population estimates and repetition rate are less relevant.
ANNEX 6.4
Incidence of public education expenditureby consumption quintile and sex, 1997/98
Source: Kadzamira et al (tracer study). Note: given the relatively small sample of graduates, especially among girls, the general trend is morerelevant rather than absolute percentage levels.
ANNEX 7.3
Actual expenditure data from University of Malawi, 1997/98 till 2001/02
158
a. Proportion of actual recurrent expenditure University of Malawi, 1997/98 till 2001/02
Source: Expenditure data received from University of Malawi; enrollment from Basic Educations Stats.
ANNEX 7.4
University graduates who ‘agreed strongly’and ‘agreed’ with the relevance and quality
statements (rounded percentages)
verall, the majority of both femaleand male graduates were more con-cerned with the quality of universityeducation (45 percent) and curricula
issues (44 percent) than with the competenceand commitment of lecturers (36 percent), stu-dent welfare (11 percent) and the acquisitionof relevant knowledge and skills (11 percent)(see second table). The proportion of graduateswho were concerned with the competence andcommitment of lecturers was significantlyhigher among the 1990s cohorts than the1980s cohorts, whereas perceived curriculaproblems were slightly lower. In part, this isbecause the university has been unable toretain well-qualified staff due to the generaldecline in real incomes, particularly since the1980s, and the failure of university to offercompetitive salaries.
When queried about recommendations toimprove university education, graduates wereconcerned about the outdated and irrelevantstocks of library books, the deterioration of thephysical infrastructure and the general lack ofreading and learning materials and equipment.Many graduates also emphasized the urgent
need to strengthen the links between universityand ‘industry’. Here, graduates suggested anumber of steps that should be taken. Theseinclude: organizing industrial attachments forall students, more practical work in the cur-riculum, more industrial/employer sponsoredprojects, and greater involvement of employersin the development of curriculum.
Sixteen percent of the graduates also sug-gested that government should increase fund-ing to the university. However, this suggestionwas made in the light of the frequent closuresexperienced by the university, which are partlydue to lack of adequate funding from govern-ment. The students cited the frequent interrup-tions as one of the weaknesses of universityeducation, and this was seen as negativelyaffecting curriculum delivery and quality.Given the probably fiscal pressure on govern-ment spending for the foreseeable future, largeincreases in government funding to the univer-sities will not be possible. However, ensuring areasonable, but stable and predictable flow offunds is just as crucial at this level. More real-istic tuition fees can clearly contribute to thisobjective.
160
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Annexes 161
Statement 1980 1987 1994 1999 Total
My university education was a good preparation for my working life 100 96 64 95 96Most of my lecturers at university were committed to their work 96 79 86 816 85Most of my lecturers at university were competent 92 84 82 83 84The curriculum for my degree course was relevant and up to date 83 69 70 65 71The job expectations have been fulfilled 67 56 52 43 52I had acquired the necessary knowledge and skills required
for my chosen profession 85 82 82 82 83I was satisfied with my verbal communication skills 92 91 86 97 90I was satisfied with my written communication skills 96 93 86 93 91I was satisfied with my information technology/computer skills 20 27 39 36 32I was satisfied with my analytical/problem solving skills 75 73 74 79 76I was satisfied with my managerial/entrepreneurship skills 46 45 48 54 49
Weaknesses 1980 1987 1994 1999 Total
The quality of education was poor 45 44 39 46 43The curriculum was irrelevant, too academic & overloaded 55 53 39 33 42The lecturers were inadequate, not well qualified and demotivated 15 33 48 37 36Poor student welfare regime 25 17 13 11 11Did not provide skills and knowledge required for the job market 13 17 8 11 11
Source: Kadzamira et al (tracer study). Note: results are from a tracer study with 380 university graduates from four separate cohorts.
ANNEX 8.1
Details of policy scenario and cost implications
his section discusses the long-termsustainability of the general evolu-tion of the education system. It isbased on one possible scenario of
targets and assumptions that were discussedwith government and it largely reflects thePIF—although alterations were made when PIFgoals were deemed unrealistic. The ensuingresults are presented as a basis for discussionwith government and donors.
The scenario attempted to be more realisticthan would be possible if the pure PIF targets,established several years ago, were strictlyadhered to; however, assumptions about thelowering of repetition and drop-out rates maystill turn out to be overly optimistic. The simu-lation model is based on the Education For All,Fast Track Initiative model but it has beenadjusted to reflect the specifics of the Malaw-ian education system, and specially to reflectcrucial targets in the PIF document. The enroll-ment estimates for primary are completed sep-arately but they are based on the simulationmodel that was used initially as part of the PIFsince it allowed a more detailed estimate usingrepetition rates and dropout rates by standard.This simulation model was provided byUNESCO, and adjusted for Malawi, with thehelp of Sussex University.44
At present the model looks at the expectedhuman resource flow (students and teachers)through the education system, and at the recur-rent cost items, related to primary and second-ary education, primary and secondary teachertraining, and higher education. These are mostrelevant for MOEST, since the recurrent costsand the human resources availability will mostdirectly influence the sustainability of the edu-cation system over time.45 The scenario forwhich the results are presented here is based onthe assumptions mentioned hereafter. For tar-get parameters, the PIF targets by 2012 areused, unless indicated otherwise.
Scenario assumptions
Primary enrollment estimates. To estimate pri-mary enrollment, the key indicators are set bythe target year to levels somewhere betweenthe PIF targets46 and the current situation.47
Repetition in Standards 1 and 8 are set to reach15 percent by 2015,48 for standards 2 to 6 toreach 10 percent; drop-out is set to reach 5 per-cent on average over all grades; and admissionrate to reach 110.
Secondary enrollment estimates. Secondaryenrollment projections, and thus the need for
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Annexes 163
qualified teachers in secondary can be derivedby using the current transition rate from pri-mary to secondary or by using the target GERfor secondary, as stated in the PIF. Both willhave a substantially different outcome inenrollment projections. The issue of placing acap on the GER and on public funded second-ary education is a major but important policyissue and it will have a wide range of implica-tions on secondary teacher needs and recurrentteacher remuneration costs.
The scenario presented here uses the GERtarget for secondary as the driving factor forenrollment estimates. Since it is already 29 per-cent in the base year 2001, the GER will hard-ly have to change and thus growth in enroll-ment is almost exclusively a result of growth inthe school age population 14–17 years.
Primary and secondary teacher training.There are a number of varied models forteacher training and in the analysis several sce-narios were examined to assess the impact onprimary goals by maintaining the currentMIITEP program, as planned, or alternatively,re-introducing the traditional 2-year pre-serv-ice teacher training program. A similar strate-gy was followed for secondary teacher train-ing, although it should be noted that thescenario retained and presented, here, does notsuggest it is specifically endorsed—or thatother options are not equally, or more, valid.
For primary teacher training, the scenarioassumes that two of the six Teacher TrainingColleges (TTC) will revert to the traditionalpre-service system, but with the first group ofstudents only starting the pre-service programin 2006 (thus graduating in 2008). Theremaining four TTCs continue with the currentMIITEP program and manage two cohortseach year. One extra TTC is already planned tobe built and it would start producing graduatesunder the MIITEP program in 2006.
For secondary teacher training, it is assumedthat Domasi pre-service training remains at itscurrent capacity level and that the presentSSTEP program will also continue beyond thecurrent three cohorts and with one cohort of270 teachers expected graduates each year. Asfar as the university colleges are concerned, thecurrent on-site capacity would remain thesame but there would be a separate distancelearning model with a total of 250 graduateseach year (e.g. Mzuzu 100 and Chancellor Col-lege 150). Their first teachers would graduatein 2007 given the four year duration of thecourse.
Resources availability and populationestimates
The GDP for the base year is taken from theIMF for 200149 and a GDP growth rate of 2.9percent per year is applied.50 For nationalrecurrent ‘discretionary’51 expenditure (i.e. lessstatutory expenditure) it is assumed that it willremain at about 14 percent.52 For the recurrentspending on education, the actual expenditures(‘actuals’) are used for 2000/01.53 The result ofthe scenario, presented here, is based on usingthe recurrent education spending as a percent-age of total recurrent spending as a constantover time (21–22 percent). A second scenario,but not presented here, assumes this percent-age would increase rapidly to 27 percent (asindicated in the PIF).54
For the total population, NSO projectionsfor each individual year between 2001 and2015 are used; for the population age 6–13and population age 14–17 the population esti-mate from NSO for the base year 2001 is usedand then a growth rate of 2.9 percent per yearapplied (which is a high end growth rate esti-mated by UNESCO).
164 Cost, Financing and School Effectiveness of Education in Malawi
Primary education and primaryteacher training
Total enrollment by standard in primary istaken from EMIS 2001 statistics for the base
year. Repetition and drop-out rates for the baseyear are taken from the Ed Data 2002 house-hold survey (with very similar results as theDHS2000 survey).
Assumptions and projections, 2001–2015
2001 2002 2003 2004 2005 2006 2009 2012 2015
Recurr. educ. spending as % of national recurrent discretionary budget 21% 21% 21% 22% 22% 22% 22% 22% 22%
National recurrent discretionary budget as percentage of GDP 14.0% 14.0% 14.0% 14.0% 14.0% 14.0% 14.0% 14.0% 14.0%
Sources: Authors’ calculations. Base year data are from IMF (GDP), Malawi economic report (budget) and NSO (population). The populationgrowth rate is from UNESCO
Private school enrollment in primary is con-sidered to remain at less than one percent overtime—this is what it is at present, according toEMIS 2001. EFA-FTI targets estimate this at
10 percent by 2015 (because it reduces costsfor government), but the PIF does not suggestany target for primary. Teacher attrition rate isconsidered 6 percent.55
Primary projections: enrollment, PCR, repetition, GER and PqTR, 2001–2015.
This scenario results in an estimated primaryenrollment of 3.9 million by 2012. The quali-fied primary teacher needs to achieve the PIFtarget of a PqTR of 60:1, under this scenario,is 64,500 by 2012. If instead the situationregarding repetition, dropout and admissionrate evolved as described in the PIF, this wouldresult in an estimated primary enrollment of3.5 million by 2012. The qualified primaryteacher needs to achieve the PIF target PqTRteacher ratio of 60:1, under this scenario, is58,000 by 2012.
If no changes occurred to the current repeti-tion, dropout rate, and admission rate, then theestimated enrollment for primary is 4.2 millionby 2012. The qualified primary teacher needsto achieve the PIF target PqTR teacher ratio of60:1, under this scenario, is 70,000 by 2012. Itis clear that the failure to reduce repetition anddropout rates will result in having to train, andpay, a large numbers of extra teachers.
Under the ‘in-between’ scenario, the expec-tation is to have 59,100 qualified teachers, or92.5 percent of all teachers qualified, and a67:1 PqTR by 2012. The trend in PqTR wouldstill be downward and the 60:1 goal could bereached over time because more teacherswould be trained than would be lost due toattrition if the stock of qualified teachers was
sufficient to have a 60:1 PqTR, given attritionremains at 6 percent.
If however, all TTCs reverted to the 2-yearpre-service training program, with the firstgraduates available in 2005 (and only MIITEPgraduates until then), and the planned extraTTC also runs the pre-service system, then by2012 the expectation is to have 33,700 quali-fied teachers, and a 115:1 PqTR. Even if twofurther TTCs are built with 625 enrollmentcapacity each, and commence producing grad-uates in 2007, the PqTR will not reduce any-where near the PIF target, because in total40,000 qualified teachers are expected by2012, and a 96:1 PqTR. Thus, while pedagog-ical reasons and political commitment wouldadvocate a return to the pre-service system, theimpact of maintaining a high PqTR is evident.
Secondary education and secondaryteacher training
Transition from primary to secondary is esti-mated in the PIF by dividing the non-repeatersin Form 1 in 2001 by the PLSCE passers in2000, and gives a 74.2 percent result. There-fore, access to secondary, as measured by tran-sition from primary to secondary, is presently
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
0%
5%
10%
15%
20%
25%
30%
35%
Total enrollment in secondary
Gross Enrollment RatePercentage private school enrollment
0
2000
4000
6000
8000
10000
12000
Expected number of qualified teacherExpected total number teachers
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Sources: Authors’ calculations. Base year data are from EMIS 2001 and Ed Data 2002.
166 Cost, Financing and School Effectiveness of Education in Malawi
far beyond the PIF target to be reached by2012 (30 percent). This is the case because ofthe introduction of the CDSSs. As indicatedpreviously, two very different enrollment sce-narios for secondary can be modeled. The first,whereby the GER of 30 percent is taken as adriving factor to estimate the number ofenrolled students in secondary, and the second,
whereby the transition from primary to sec-ondary of 74.2 percent is taken as a drivingfactor. The scenario used here is based on theGER of 30 percent.
Private school enrollment in secondary wasfound to be 11 percent in 2001 (EMIS 2001),and set to further increase to 25 percent by2012, as put forward in the PIF. Teacher attri-
Secondary projections: enrollment, PCR, repetition, GER and PqTR, 2001–2015
Gross Enrollment RatePercentage private school enrollment
0
2000
4000
6000
8000
10000
12000
Expected number of qualified teacherExpected total number teachers
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Source: Authors’ calculations. Base year data are from EMIS 2001.
Annexes 167
tion rate is considered 5 percent for the stan-dard scenarios.60
Secondary enrollment by 2012 can beexpected to reach 393,000, since the GER inthe base year (2001) was already 29 percentand therefore the growth in enrollment num-bers will be in line with the growth in schoolage population 14–17. (This would howevermean that the current transition rate from pri-mary to secondary of 74 percent will not bemaintained as more children pass the PSLCE.)The required number of qualified teachersrequired under this assumption to achieve thePIF target of 40:1 PqTR, and having only qual-ified teachers after 2007, is 9,800.
If the driving factor for secondary enroll-ment is to maintain the 2001 transition rate of74 percent (which is much higher than the PIFtarget of 30 percent by 2012), then the enroll-ment projections will be strongly dependent onthe number of children who are expected topass the PSLCE over time. This in itselfdepends on what will happen with primaryenrollment over time. If, as before, the ‘in-between’ scenario is used for primary, the tran-sition rate is kept at the current level, thenGER in secondary will be approximately 46percent by 2012, and secondary enrollment atabout 608,000. The required number of quali-fied teachers to achieve the PIF target of 40:1PTR, and having only qualified teachers after2007, would be 15,200.
Under the scenario of a 30 percent GER asthe driving factor, the expectation is to have8,600 qualified teachers by 2012, and a 46:1PqTR. With attrition of 8 percent (instead of 5percent) as a result of HIV/AIDS, the PqTRwould come down to around 53:1 by 2012. If,however, the current capacity in secondaryteacher training is maintained, without contin-uing the SSTEP program beyond its initial 3cohorts, and without increasing the capacity ofthe university colleges by 250 by 2012, theexpectation is to have 5,700 qualified teachersand a 70:1 PqTR. As a consequence therewould be no real further downward trend in
the PqTR even if an attrition rate of 5 percentis achieved.
Recurrent cost implications
Assumptions for primary. Teacher remunera-tion is a crucial element of the recurrent costcalculation and qualified teacher remunerationin primary was found to be about 5.5 timesGDP per capita, and was assumed to be kept atthat level, i.e. only increasing in real terms atthe same rate of the GDP per capita.66 Unqual-ified teacher remuneration was found to beabout 2.9 times GDP per capita, and wasassumed to be kept at that level.67 Spending onteaching and learning materials (T&L) as apercentage of total recurrent spending in pri-mary was found to be 6 percent,68 and was setto increase to 13 percent by the end of the peri-od—as prescribed in the PIF. Spending on totalORT as a percentage of total recurrent spend-ing in primary was found to be about 15 per-cent.69 It was assumed that over time this per-centage would only increase as a result of theincrease of the T&L component. This results inan estimate of total ORT as a percentage oftotal recurrent spending in primary of about18 percent by 2012.
Assumptions for secondary. Qualifiedteacher remuneration was found to be about11.5 times GDP per capita, and was assumedto be kept at that level, i.e. only increasing inreal terms at the same rate of the GDP percapita, although it is likely there will be furthernominal increases to compensate for infla-tion).70 Unqualified teacher remuneration wasfound to be about 5.5 times GDP per capita.This is realistic since they are qualified primaryschool teachers and this is the amount notedfor qualified primary teachers.
Spending on total ORT as a percentage oftotal recurrent spending in primary was foundto be about 50 percent.71 It was assumed thatthis percentage would decrease to 40 percentby 2007 due to a large increase in teacher
168 Cost, Financing and School Effectiveness of Education in Malawi
remuneration as a result of the many morequalified teachers in the system, and the result-ant higher salaries than for unqualified second-ary teachers. In the total recurrent cost calcu-lation, the secondary teacher training cost atuniversity colleges is not added separatelybecause it is considered automatically includedin the fixed portion of funding allocated touniversities. This, however, is also a major sim-plification since a substantial increase inteacher training costs at the university collegesmeans savings will have to happen elsewhere inthe universities to ensure the universities, as awhole, have the same portion of the total edu-cation budget over time.
Assumptions for universities and other sub-vented organizations. According to the PER(Public Expenditure Review—MOF website),the proportion of recurrent education cost thatis allocated to the universities, and other sub-vented organizations, fluctuated between 27percent in 1993/94 and an expected 20 percentin 2001/02. Given the PIF goals to make uni-versity education more efficient (lower unitcost per graduate, especially the publicly paidcomponent of the unit cost), the assumptionwas made that this 20 percent would be main-tained over time until 2012 even though thereis strong system expansion. Since there is anestimate of the recurrent costs of primary, sec-
Sources: Authors’ calculations. Base year data are from EMIS 2001.
Annexes 169
ondary and teacher training, this allows a cal-culation of the expected recurrent costs of uni-versities and other sub-vented organizations.72
In the table above, the assumptions madeare similar to assumptions made in the firsttable, but with spending on education as a per-centage of national ‘discretionary’ recurrentbudget increasing to the PIF target of 27 per-cent by 2005. This will have the followingrepercussions:
• Recurrent expenditure on primary educa-tion would require about 71 percent oftotal available recurrent education budgetin 2012
• Recurrent expenditure on secondary edu-cation would require about 29.5 percentof total available recurrent educationbudget by 2012
• The total shortage between the expectedrecurrent education costs and expectedrecurrent education budget seen as a per-centage of the total national discretionary
budget will be continuously around 6–8percent over time between now and 2012.
The model targets and assumptions indicatethat recurrent cost implications of the differentpolicies would be larger than the domesticresource availability. It is clear that there is aneed to have in-depth discussions withMOEST, MOF and the donor community, atlarge, on the realism of this type of scenario.For instance, the expected total resourcesavailable and the teacher salary costs (bothunit cost and total cost) are crucial issues fordialogue: the latter because it requires such amajor portion of the total resources. In fact,this is also why issues such as planning teachertraining must not be done in isolation from thegeneral issue of sustainability. This issue cen-ters on the payment of teachers once they arehired and trained. It is also crucial to under-stand what the expectation is for furtherinvolvement of the HIPC debt relief program.The results of this financial model can facilitatesuch a dialogue.
ANNEX 8.2
EMIS
his list is only intended as a startingpoint for a review of the EMIS sys-tem and does not claim to be exhaus-tive.
(1) At the end of 2003, no EMIS statisticswere available because there is always morethan a one year backlog between data collec-tion and dissemination. As such, a speeding upof this process would ensure policy decisionsare based more on the current situation. (2)The fact that in recent years a large number ofsecondary government schools and privateregistered schools did not provide feedback toEMIS questionnaires should not be acceptableas it makes estimates of even the most basicindicator of total enrollment unreliable. It alsomakes any serious analysis of the current situ-ation, and planning for the future, close toimpossible. It is also in the government’s inter-est to work with private schools to providestatistics and it may be an effective tool toshow the public at large that because of the‘stimulating environment’ for private second-ary school sector, a significant percentage ofMalawians still have access to secondary—even though severe budget constraints requirethe government to keep its focus mainly onprimary. (3) Household surveys consistentlyshow much higher repetition rates than the
school census and, as such, a clarificationreflecting internationally accepted guidelinesof the definition of repeaters versus newentrants into a grade, and the subsequent con-sistent use of this definition, would improvethe reliability of the data. (4) There is also aprobable overrepresentation of the enrollmentnumbers from the school census (albeit clearlyless extreme than the issue of repeaters vs newentrants). It would be good to look at theinstitutional mechanics behind the reportingof the enrollment data in the school census. Itmight be that certain changes in the incentivesstructure have contributed to a tendency toover-report. On the other hand, it might alsobe that even without changes in the formalincentives structure, the introduction of FPEgenerated a behavioral change.74 (5) Statisticsgathering should be adjusted to the reality ofrepetition in secondary (at present no repeti-tion is assumed). With the enrollment of mass-es of pupils in typically low quality CDSSs, thepressure for repetition must surely haveincreased, and the policy of not allowing rep-etition in secondary is certainly untenable inthis context. (6). It is clear that there are enor-mous inequities in teacher deploymentbetween primary grades. As such, it is neces-sary to provide data on PTR and PqTR by
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Annexes 171
grade since these are crucial indicators totrack. It might even be possible to obtain thisinformation from the current EMIS question-naires but currently this indicator is notreported on. (7) There is an enormous dis-crepancy between ages of primary pupilsaccording to household surveys versus datafrom EMIS. Establishing better age estimatesfrom questionnaires in schools will remain dif-ficult as long as no birth certificates are avail-
able. However, it makes little sense to place allprimary students, older than 14, in one singlecategory, particularly when the household sur-veys indicate that substantial numbers ofyoung adults aged between 15 and 22 yearsare attending primary schools. However, it isonly intended as a starting point for a reviewof the EMIS system and does not claim to beexhaustive.
172 Cost, Financing and School Effectiveness of Education in Malawi
Annexes Notes1. This is the 2000 value instead of 2000/01.2. This is the 2002 value instead of 2002/03. 3. For 1990/91–1991/92 the source is IMF
“Malawi: Statistical Appendix. June 1995”.For 1992/93–1995/96 data are from IMF“Malawi: Recent Economic Developments.August 1997.” The remainder is from IMF“Selected Issues and Statistical Appendix.August 2002.” From 1996/97 till 2000/01 areactuals. For 2001/02 is estimate. For “TotalGrant”, “Total Revenues”, “Total Govern-ment Expenditures”, “Total current expendi-tures”, “Total development expenditure” thesource is the same.
4. Information used in this section wasextracted from the Malawi Ed Data 2002 andis summarized in Table 2. A sample of chil-dren, aged 6–14 years, who had ever attendedschool, were involved in the survey.
5. The GER based upon the population cen-sus uses one set of data for both the nominator(enrollment) and denominator (population),which is not the case for the school census thatonly can provide enrollment data. The fact thata ratio is presented also preempts the argumentthat maybe not the whole population isaccounted for in the population census,because any no-counts will cut out both pri-mary pupils and people in the age group 6–13,unless the no-counts would be disproportion-ately from the ones in primary but outside6–13 age range.
6. Only includes children age 5 to 29.7. Another interesting piece of data is that
IHS 1998 calculated a weighted population of2,256,896 for the 6–13 age group.
8. The result here is very similar to the otherestimate based upon GER for boys and girlsseparately, as done in ‘Profile of Poverty inMalawi, 1998. Poverty Analysis of the MalawiIntegrated Household Survey 1997–98’, whichhas GER 125.9 (boys) and 115.2 (girls).
9. Calculated in three ways: (i) based on theDHS 2000 household survey; (ii) based uponthe results from the school census (EMIS 2000)
on enrollment by age combined with popula-tion data by age from the National StatisticalOffice (NSO) (low-end estimate); and (iii)based upon the results from the school censuscombined with population data by age fromUNESCO (high-end estimate). To ensure com-parability, children who are already in second-ary, or beyond, were eliminated and only thosepupils attending primary were included. Asexpected, the enrollment rates from the house-hold survey show a gradual increase until theage of 8 or 9 years (due to some late enroll-ments), and they then remain largely stableuntil the age of 13–14 years before decliningonce more. However, this decline is at a slow-er pace than would be expected. The surveyalso finds that a very high percentage of chil-dren ages 14 to 21 years were still in primary(e.g. 80% at age 14, 60% at age 17, 20% atage 21) and that it was only young adults ofages 22 years and above that had an enroll-ment rate of less than 10%. It is clear thatmany of the children entering primary remainuntil at least the normal age of finishing pri-mary. This does not mean they finish standard8 but rather that they may be repeating thesame, or several grades, before eventuallydropping out. The findings from the DHS sur-vey closely match the results from the Integrat-ed Household Survey (IHS) of 1998 (see Annex2.2).
10. Here, using the high-end population esti-mates, enrollment rates for children of normalprimary school age (6 to 13) are consistentlyhigher than those of the household surveys.For the children of ages 7 to 10, more childrenare found to be in school than are present inthe corresponding population group (enroll-ment rate more than 100%), even when usingone of the highest available population esti-mates for the country (UNESCO). At the sametime, however, the school census statistics indi-cate that the category ‘all children older than14’ represented less than 80 percent of the pop-ulation at age 15. This is slightly less than the80 percent that DHS 2000 indicates is the
Annexes 173
enrollment by age for children aged 15. Inother words, all the enrollment rates for thoseage 16 or higher from the DHS 2000 wouldnot be accounted for in the school census esti-mates.
11. The school census also categorizes allchildren of age 5, or below, in one categoryand the 15%, here, represents all these childrenas a proportion of the children of age 5 only.The surveys on the other hand only start gath-ering data from children age 5. As such, somechildren may need to be added to the approxi-mate 30% for children age 5, who alreadyattend primary at age 4, or below.
12. This assertion holds irrespective of allchildren, in practice, entering primary at age 6or at another age (typically anywhere between5 and 10), because a new entrant of age 10should never before (i.e. theoretically 4 yearsearlier) have been counted as a new entrant inthe system. As such, in a steady state system—as the Malawi one would be predicted to be bynow—each child can only be a new entrantonce, and the number of new entrants intoStandard 1 should be influenced only by popu-lation fluctuations and the degree of access toprimary.
13. Using the 1987 non-repeating enroll-ment numbers from the Basic Education Statis-tics, together with the population found fromthe population census in that year, the rate ofentry to Standard 1 is 0.87, which is actuallyclose to the estimate of 0.84 found based ondata from the 1992 Demographic and HealthSurvey (DHS). It is also noteworthy that in1987, the enrollments reported by the schoolcensus —1,022,765 children— are very closeto the 1,002,343 children in primary schoolsenumerated in the 1987 population census.The consistency in these cross-checks increasesthe confidence that the data for 1987 are prob-ably reasonably accurate. For 1998 however,the situation is different. According to the1998 Integrated Household Survey it is esti-mated that about 96 percent of each age cohorteventually begin primary schooling, which is
confirmed by the DHS 2000 Survey indicating95 percent eventually start primary. Given theassumption that the new entrants into stan-dard 1 in a system that has reached a steadystate (which Malawi should have for at leastthe first grade of primary in 1998 or at the lat-est by 2000) cannot be more than the numberof children of the entry age, it is possible toestimate what the population at entry ageshould be in order to be able to have a numberof new entrants to Standard 1 at the levelfound in the school census statistics. The sizeof the entry age population in 1998 wouldhave to be about 665,484 (=638,865/0.96),with 638,865 being the new entrants to Stan-dard 1 according to the school census. Com-paring the result with the children at entry agein the 1987 census (which we assume to becorrect in light of the arguments presentedabove), the population in this age cohortwould have grown at the rate of 8.4 percent ayear (=[ln(665,484/263,643)]/11) between1987 and 1998—surely an implausible rate ofincrease in any human population. This is whyit is worthwhile to review the number of newentrants into Standard 1 in more dept.
14. For instance one performed by CIDA inrelation to its primary school book distributionproject.
15. In the survey, data it is automaticallymeaningful if the child is repeating becauseboth the child’s current grade level is asked aswell as the grade level (s)he attended the previ-ous year.
16. Using for instance the average repetitionrate for standard 1 according to the DHS 2000and Ed Data 2002 household surveys, which is42.9% (Average of 45.3% from DHS 2000and 40.6% from Ed Data 2002; which is aconservative value, lower than when using thehigher rate from only DHS 2000.), it is possi-ble to recalculate the number of new entrantsfor both 2000 and 1998 (assuming the repeti-tion rate was already at that level in 1998). Thenumber of new entrants would have been441,087 in 1998 (deduct 42.9% of 772481;
174 Cost, Financing and School Effectiveness of Education in Malawi
and for 2000 deduct 42.9% of 804,312; whichare respectively the total enrollment numbersfor 1998 and 2000 from the school census),and 459,263 in 2000. With this new count ofnon-repeating enrollments in standard 1, thesize of the population at entry age in 1998would have to be about 459,466(=441,087/0.96) in 1998 and 478,399 (=459,263/0.96) in 2000. The population in thisage cohort would have grown at the rate of 5.1percent a year (=[ln(459,466/263,643)]/11)between 1987 and 1998, which is more plausi-ble than the 8.4 percent a year found earlier,but is still quite unlikely given the analysis inthe section on population. The average age ofstandard 1 pupils was 7.7 years in 1998; giventhat the corresponding rate of repetition isassumed 42.9%, it means that the average ageof new entrants is 7.3 years. The algebra is asfollows: A=N(1–r)+R(r) where A, N and R are,respectively, the average age of all pupils, non-repeaters (i.e. new entrants) and repeaters (i.e.only looking at if the pupil is a repeater in thecurrent year, not at the past); and r is the pro-portion of repeaters. Since R=N+1 by defini-tion, we can make the appropriate substitutioninto the first equation, and obtain after rear-ranging, the desired function, N=A–r. Relatingthe number of non-repeaters in standard 1 tothe population corresponding to these ages(using original population census data), a newestimate of the cohort rate of entry to standard1 is obtained: 1.60 for 1998 (The populationcorresponding to age 7.3, is obtained simply byprorating the population enumerated for ages7 and 8, i.e.(0.7 x 270,036) + (0.3 x 286,841 =275,077. The difference of using this moreadvanced way to estimate the correspondingpopulation cohort versus simply using the pop-ulation of official age of entry 6 (315,612), isnot of such magnitude to make a huge differ-ence. Using age 6 population, the cohort rateof entry to grade 1 would still be 1.40 in1998). For 2000 this would be 1.55. (2000 age6 population 303,785, age 7 298,554, age 8291,792. Population corresponding to age 7.3
is (0.7 x 298,554) + (0.3 x 291,792) = 296526.Using age 6 pop the cohort rate of entry wouldbe 1.51.)
17. The 1998 population census (see 1998Population Census Analytical Report onwww.nso.malawi.net) states that between1987 and 1998 pop grew with 23.2 percent, or1.9 % per annum. The growth for age group6–13 was 1.4 percent ( [ln(2,115,870/1,818,910) ] / 11 ), with 2,115,870the 6–13 population in 1998 and 1,818,910the one in 1987.
18. = [ln (2437000/1818910) ] / 1119. The 1987 population census (see Gov-
ernment of Malawi. 1991 and 1993.) statesthat between 1977 and 1987 population grewwith 44 percent, or 3.7 % per annum. Esti-mated growth per year for the 5–14 age groupbetween 1977 and 1987 is 4.9 percent ([ln(2,286,959/1,395,961) ] / 10 ). Specificgrowth rates for the 6–13 age group are notgiven, but should not significantly differ.
20. The 6–13 age group population in 1987was 1,818,910. ln(x)= (11*0.049) +ln(1,818,910)= 14.95275–> ex of this is3,118,142
21. ln(x)= (13*0.049) + ln(1,818,910)=0.637 + 14.6427335 = 15.05075–> ex of this is3,439,195
22. The results, reveal that the population ofthe Northern Region increased by 35 percentwhile that of the Central and SouthernRegions—where the districts are found thatborder with Mozambique—rose by 31 and 17percent respectively between 1987 and 1998
23. 1998 age 7: 333000, age 8: 326000.Population corresponding to age 7.3 is (0.7x333000) + (0.3 x 326000) = 330,900. This isused together with the new entrants at 441,087for 1998.
24. 2000 age 7: 330000, age 8”: 327000.Population corresponding to age 7.3 is329,100. This is used together with the newentrants at 459,263 for 2000.
25. Cross sectional method is calculated asthe gross admission rate to the last grade of
Annexes 175
cycle divided by the gross admission rate tofirst grade of cycle of the same year, with thegross admission rate being the non-repeaters ina certain grade divided by the population ofnormal age for that grade. For instance forstandard 8 this would be the non-repeatingpupils in standard 8 divided by the children ofage 13.
Quasi-time-series estimate is calculated asthe multiplication over the whole cycle of thedivision of the number of non-repeaters in 2consecutive grades in 2 consecutive years. Forprimary in Malawi this would be:
(Non rep year 2 standard 2 / Non rep year 1standard 1) * (Non rep year 2 standard 3 /Non rep year 1 standard 2) * (Non rep year 2standard 4 / Non rep year 1 standard 3) *(Non rep year 2 standard 5 / Non rep year 1standard 4) * (Non rep year 2 standard 6 /Non rep year 1 standard 5) * (Non rep year 2standard 7 / Non rep year 1 standard 6) *(Non rep year 2 standard 8 / Non rep year 1standard 7)
These survival rate calculations are usuallydone at different points in time to try to assesswhat has been the evolution Full time seriesperspective of survival for a cycle is calculatedby dividing the non repeaters in the last gradeof the cycle in year ‘X’ by the non repeaters inthe first grade of the cycle in year ‘X minuslength of cycle for the average student’ (underideal circumstances this would be ‘X minus thenumber of grades in cycle’; however, becausean average student might repeat one or moretimes before reaching the end of the cycle thetime frame can be increased for to make up forthat and to ensure it is the same cohort ofpupils that is considered)
The Quasi-time-series method has twoadvantages in the case of Malawi. First, theresult is not ‘spoiled’ by the effect of the FreePrimary Enrollment policy, seen it only usesdata from two subsequent years, which canboth be years that come after the policy wasintroduced, and thus are in the same situationin relation to the effect of the FPE policy. The
cross-sectional method and the full time seriesmethod on the other hand are both influencedby the effect of the FPE policy. Second, oppo-site to the cross-sectional method, the quasi-time-series method also abides by the rule thatfor survival it is best to compare the samecohort of students over time, instead of twodifferent cohorts at one point in time. Thesemi-time series method follows this rule for 6separate cohorts.
26. These are generally considered a moreaccurate measures.
27. Since repetition rates are only availablefrom household surveys in 2000 and 2002, itwas decided to use repeater numbers as indi-cated in Basic Education Statistics to ensuregreater consistency between the results from awide range of years. The fact that the repeti-tion rate seems to be significantly underesti-mated in the EMIS data matters to the absolutelevels of the results, but not to the relative dif-ferences between the two periods.
28. The larger than 8 year interval is toadjust for primary graduate repetition.
29. The method compares the non-repeatersin grade x in 1998/99 with the non-repeaters ingrade x+1 in 1999/00. For each of the 8grades, both sides of this grade by grade com-parison are always either affected by the FPEpolicy (up to standard 5 in 1998/99, up tostandard 6 in 1999/00) or not yet (beyondstandard 5 in 1998/99, and beyond standard 6in 1999/00)
30. For secondary education always the esti-mated enrollment numbers (through extrapo-lation) are used as found in the Basic Educa-tion Statistics 2000.
31. Non-repeaters in the correspondinggrade divided by the population group at theofficial age for the grade (standard 1 intakerate = non-repeaters stand 1 / children age 6 inthe population)
32. For secondary education always the esti-mated enrollment numbers (through extrapo-lation) are used as found in the Basic Educa-tion Statistics 2000.
176 Cost, Financing and School Effectiveness of Education in Malawi
33. In total 92 schools were not includedbecause they had negative numbers for enroll-ment minus repeaters in one of the grades, orbecause they listed no enrollment in standard1.
34. Ministry of Labour and VocationalTraining, 2002.
35. The averages are based only on data forcountries with per capita GNP below $1,000in 1993.
36. Some of this cost includes a non-recur-ring cost of providing storage cabinets for thebooks.
37. There are many examples of districtmanagers authorizing teacher transfers on theproduction of marriage certificates. This sys-tem is considered open to fraudulent transferpractices.
38. Measured by ‘possessions in the home’.39. The scenario in Annex 3 builds on the
assumption that there will be no change incoverage (no change in enrollment rates) or inthe ratio of the number of pupils to the num-ber of teachers. Thus it describes the system asit was in 1998 and its evolution with or with-out the impact of HIV/AIDS. The 1997 figuresfor total population and school-age populationare based on the 1997 Malawi census. Theschool-age population covers the age group 6to 15 years old, or grades 1 to 10 (lower andupper primary education and lower secondaryeducation); the teacher stock is based on34,000 lower primary teachers, 4,000 upperprimary teachers, and 2,000 lower secondaryteachers, as registered in 1997.
40. Esme Chipo Kadzamira, Dixie Maluwa-Banda, Augustine Kamlongera, Nicola Swain-son, September 2001, Centre for educationalresearch and Training (CERT), Malawi.
41. Kadzamira et al., 2001.42. Does not include Mzuzu university43. Does not include Mzuzu university44. For key indicators in the model the
assumption is made that the system movesfrom the current situation to the target value(by the target year) in a linear manner. The
assumptions used in the model (with baselinedata for 2001) are the best that could beobtained in the time-frame available and withthe assistance received. It is clear that improve-ments by MoEST staff can be made if moreprecise data is available.
45. The capital expenditure (with classroomand other construction as main cost drivers)has not been included at this point. It would berelatively easy to include this later in the model
46. 5 % repetition for standard 1–7, 10%repetition for standard 8; 5% dropout, admis-sion rate 100
47. Average rep rate in primary of 25.8%,average dropout 8.2%, admission rate 132%(according to the Ed Data 2002 household sur-vey)
48. In this case the timing reflects a minormodification from the PIF target year 2012.
49. Very similar to what is found in EconReport 2003 for 2001/02.
50. Taken from Econ Report 2003 as aver-age for last 6 years.
51. Recurrent expenditure before debtamortization minus interests on debt andminus pensions & gratuities.
52. From the Economic Report 2003: for2000/01 actual results in 14.1% of GDP ofcorresponding year, for 2001/02 actual it is18.1% of GDP, for 2002/03 revised it is 11.8%of GDP, and for 2003/04 estimate it is 9.7% ofGDP. The serious difference that still existsbetween the discretionary recurrent govern-ment budget and the total recurrent govern-ment budget is largely a result of interest pay-ments and debt amortization on domestic debt,not on international debt. For 2002/03(revised) the discretionary budget is 18,434million MK vs. a total budget of 39,755 mil-lion MK, and for 2003/04 (estimate) it is16,882 million MK vs. 41,375 million MK.This means that the current level of discre-tionary recurrent budget, as a percentage ofGDP, will not be able to increase much more asa result of further HIPC debt relief, but only as
Annexes 177
a result of the government’s ability to reduce itsdomestic debt burden.
53. For both MoEST and the subvented edu-cation organizations (including universities)‘actuals’ are taken from “Consolidated Annualappropriation accounts for the financial yearended 30 June 2001”.
54. There is actually a HIPC trigger for edu-cation requiring the share of recurrent educa-tion expenditure (including universities andother subvented organizations) of at least 23%of the discretionary recurrent budget.
55. This is deemed a prudent scenario, sincedeath and retirement together, for 2001, wereless than 3%, but partial numbers from thedivisions for 2003 seem to put attrition due todeath at a significantly higher rate of 3–4%. Assuch, another 3% for resignations and to makeup for the higher attrition due to deaths wasseen by the group as probably quite acceptable.(EMIS 2001 captured 907 teachers who passedaway out of a total stock of 53000. EMIS 2001also shows 7059 out of 53000 teachersbetween age 45 and 80, meaning on averageabout 700 per year at most could retire overthe next decade.)
56. Public and private57. The number of qualified teachers
expected is a result of the output of the teachertraining scenario that is used and of the expect-ed attrition (assumes all qualified teachers workin public primary schools, not in private ones)
58. The number of unqualified teachersexpected is the difference between the totalnumber of teachers expected and the expectednumber of qualified teachers.
59. The total number of teachers expectedin public primary schools is a result of a grad-ual expected transition from the current 77:1pupil:stream ratio to 60:1 at the end of theperiod, while at the same time, theteacher:stream ratio is set to increase from 0.8at present to 1 at the end of the period.
60. PRSP uses 5%, PIF uses 10% on p.30,Nat Strat teacher training has projections with10% and with 5%. Attrition as a result of
deaths is lower than in the case of primaryschool teachers according to the study “Impactof HIV/AIDS on HR in the Malawi public sec-tor”. On the other hand, the qualified teachers(in particular with a science background)might resign quicker to find other type of workin the private sector. In addition, secondaryteachers often switch from public to privateschools—especially when they can take theiroptional retirement after 20 years of service.However, since secondary enrollment for bothprivate and public schools is reflected here, thiseffect does not mean extra attrition for theteaching body.
61. Public and private62. The number of qualified teachers
expected is a result of the output of the teachertraining scenario that is used here and of theexpected attrition. This need for qualifiedteachers is based upon expected enrollment inboth public and private schools, since teachersfor private schools—if qualified—will alsohave to come from the same teacher traininginstitutions. Of course the teacher remunera-tion cost only reflect those teachers teaching inpublic schools.
63. The number of unqualified teachersexpected is the difference between the totalnumber of teachers expected and the expectednumber of qualified teachers.
64. The total number of teachers expectedin public and private schools is a result of agradual transition from the current 36:1pupil:teacher ratio to 40:1 by 2007, and of theexpected total student enrollment.
65. This is the average for the secondary sys-tem as a whole, i.e. including public and pri-vate schools.
66. The sources of information for the cur-rent teacher remuneration calculation wereMoEST Payroll 2002 and the Teacher SalaryScale. The number of qualified teachers was:PT4: 23255, PT3: 6513, PT2: 2232, PT1:1197, and the average yearly salary packagefor PT4: 62256, PT3: 130440, PT2: 183780,PT1: 183396. The sum of the products of
178 Cost, Financing and School Effectiveness of Education in Malawi
average yearly salary and number of teachersfor each grade gives an estimate of total quali-fied teacher remuneration per year. The aver-age qualified teacher salary of 88171 (totalremuneration/total qual teachers) divided bythe 2002 Malawi GDP per Capita of 15915results in the average qualified teacher’s salarybeing 5.5 times GDP/Capita.
67. This result was obtained using totalOCT salary for TT including allowances(K3853pm*12=46236pa) and the 2002 percapita GDP of US$207.5 (1$=76.7).
68. Not readily available for 2001. Howev-er, according to PER it was fluctuating between4 and 8% in the period 94/95 to 98/99
69. From 1994/95 till 1999/00 roughly 85to 90% of recurrent primary spending was onteacher salaries (source PER)
70. Data used from PPPI at end of 2002 onthe number of secondary teachers in each leveland the total salary package for each level, thetotal average salary (including allowances) was150000 to 175000. Using the 2002 GDP/capof 15915 (Econ Report 2003), this meansbetween 9.5 and 10.9 times GDP/cap.
71. between 1994/95 and 1998/99 PE wasroughly 40 to 60% of secondary budgetaccording to PER.
72. =(0.2/(1–0.2))* recurrent cost of allother levels.
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