African Centre for Statistics

United Nations Economic Commission for AfricaUnited Nations Economic Commission for Africa

Production and Use of Production and Use of Administrative Data and Administrative Data and Sub National Level Data Sub National Level Data for MDG Monitoring in for MDG Monitoring in Africa: Challenges and Africa: Challenges and

OpportunitiesOpportunitiesWorkshop on MDG Monitoring 5-8 May 2008, Kampala, Uganda

Dimitri Sanga, Ph.D.Dimitri Sanga, Ph.D.Senior StatisticianSenior Statistician

Outline Background Data Sources for MDG

Monitoring Use of Administrative Data

Sources for MDG Monitoring The Need for MDG Data at

the Sub National Level The Way Forward

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BackgroundBackground

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MDG Monitoring Monitoring and evaluation of

progress made towards the achievement of the MDGs is data intensive

They require data from various sources produced using different tools

The choice of the source depends on the availability of the data and the indicator

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Data sources for MDG monitoring

The main sources of data for MDG monitoring include:Household surveysCensusesAdministrative records: Health,

education statisticsCivil and vital registration

systems: birth, deaths, marriages, divorces…

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Data sources for MDG monitoring (2)

Different indicators require different type of data

Sometimes, multiple types of data could shed light on a single MDG indicator

Thus, the need for making a choice of data source

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Example 1: Mortality Data on mortality (infant, child and

maternal) can be obtained from:Vital registration systemsHousehold sample surveys

In most developing countries:Registration of births and deaths is

incompleteUnderestimation of mortality ratesHousehold sample surveys are the commonly-

used data source to estimate mortalitySince mortality is a relatively rare event: need

for large surveys to capture enough deaths to obtain reliable estimates of mortality

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Example 2: Education Many countries use administrative

data (data from school registers) to calculate primary or secondary enrollment rates

Enrollment rates based on administrative data overstate those based on HS:Administrative data report on the number of

children enrolled at the beginning of the school year

HS data typically report school attendance data (Does your child currently attend school?)

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Advantages of administrative data

sources Reduction of response burden as the NSO would have access to the data provided by the system

Provide data on small areas and targeted population groups

Coverage at relatively low cost as compared to other sources

Possibility to link with other data sources and to produce new type of data and statistics

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Use of Use of Administrative Administrative

Data Sources for Data Sources for MDG MonitoringMDG Monitoring

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Administrative data Data produced in countries on the basis

of some administrative processes Compiled in the course of routine

operations of government ministries and institutions

Units and variables defined according to :Administrative actsRulesRegulations

Definitions adopted in the administrative data may differ from the needs of the official statistics

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Vital and civil registration systems

Vital and civil registration systems (VCRS): Record the occurrence and

characteristics of vital events: birth, death and causes of death, marriage, etc.

Based on laws, regulations and other legal requirements

If complete, VCRS are source of reliable continuous flow of vital statistics

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Vital and civil registration systems (2)

VCRS provide accurate measures of vital events and population change over the time

VCRS have to be complete and accurate to provide accurate and reliable data as alternative to censuses and surveys

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Vital and civil registration systems in Africa (3)

In most African countries VCRS are under developed

Problems hampering their development include:InfrastructureOrganization and management

of the registration processCapacity constraintsLegal framework

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Example 1: Deaths coverage*

Deaths coverage in SSA is much below average

Concentration of the system in urban areas explains partially this low coverage

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Country Year Estimated coverage

(%)

Seychelles 1998

99

Mauritius 2000

90

South Africa

1996

67

Kenya 2001

60

Zimbabwe 1995

40

Ghana 2001

25

Botswana 1998

25

Zambia 2000

16

Mozambique

2000

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*Report on the WHO workshop on Minimum data Set on Ageing in Sub Saharan Africa, 2003

Rates computed using WHO life tables estimates for deaths at national level as denominators

Example 2: Births registration*

Birth registration coverage is below 50% in many countries

Some exceptions: birth registration coverage of over 90% (Mauritius, Egypt, Libya, Tunisia…)

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Country Level of registration (%)

Algeria 90 +

Egypt 90 +

Libya 90 +

Mauritius 90 +

Gabon 70-89

Burundi 50-69

Gambia 50-69

Botswana 30-49

Cameroon 30-49

Chad 30-49

Ghana 30-49

Kenya 30-49 *UNICEF, Deficient Birth Registration Systems in Developing Countries, Population Development Review, Vol. 24, No 3, 1998

Some good practices: South Africa

Launch of a joint vital registration infrastructure initiative

Collaboration: Department of HealthDepartment of Home AffairsStatsSA

Significantly improved coverage of all births and deaths

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Some good practices: Mauritius

One of the well developed civil and vital registration systems in Africa

Civil Status Division: collection of vital statistics and transmission to the NSO

Entirely computerized system with a civil status database

Complete coverage of vital events

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Some good practices: Other countries

Some countries with high coverage and completeness of birth and death registration: Tunisia and Egypt

Countries developing their civil and vital registration systems: SudanEthiopiaBotswana

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Challenges of using administrative data

sources Availability of data limited only to

variables covered by registers Some restrictions on definitions of

units and variables Vulnerability to changes in legislation

and administrative practices Data are usually compiled by people

who lack skills in handling data Provide information on the sections of

the population accessing some facilities and not on those without access

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Challenges of using administrative data

sources (2) Numbers may be inflated in some

areas Primary purpose is NOT data

collection Data are collected by different

authorities using their own definitions, classifications, methodologies and time frames

Institutional constraints: inadequate support in terms of funds, equipment, personnel and skills

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Opportunities offered by the use of administrative

data sources Opportunities include:

Improvement in Management Information Systems (MIS) adopted by many sectors especially health and education

Advances in ICT that enable data capture, processing, archiving, transfer…

Enhanced collaboration between line ministries and the NSO

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Administrative data Enable the possibility to reduce the

burden on respondent Provide better and more detailed

picture of the society Require a good knowledge of their

content for proper use for statistical purposes

Some pre requisites for further development of register-based statistics include:Strong legal basesClear and effective confidentiality rulesAwareness of every employeePublic trust

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The Need for Sub The Need for Sub National Data for National Data for MDG MonitoringMDG Monitoring

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MDGs monitoring: at which level?

Reporting and monitoring MDGs at the national level is a good start

The Millennium Declaration is about improving the conditions of people in member states

There is a need to monitor MDGs at the sub-national level

But this is feasible only if data at lower levels are readily available

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Advantages Data at lower levels of

disaggregation:Allow for targeted socioeconomic

policy decision-making and programme formulation

Allow planners and policy makers to be able to identify:

That some locales require more support for educational programmes

Others require disproportionate investment in HIV treatment or malaria abatement

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The MDG Mapper A tool developed by the UNECA for

dynamic mapping of comparative progress by African countries towards achieving the MDGs

Uses the official UNSD database Tool presents countries that have:

Required trend to meet the goalsCurrent trendProgress at current rates: on/off target ?

Assessment made at national level and sub national where data exists

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The Mapper at the national level

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A Map will be inserted here!

Net enrolment rates in primary education, both sexes

The Mapper at the sub national level

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A Map will be inserted here!

http://geoinfo.uneca.org/mdg/

National vs Sub National Storylines

30Source: Ghana Statistical Services, 2007. Poverty line: 2,884.7 new cedis per year

Incidence of poverty in Ghana by area

4.4 3.5

9.2

27.2

49.351.7

3.5 2.3

6.9

22.5

58.7

28.5

0

10

20

30

40

50

60

Accra Urban forest Rural coastal Rural forest Ruralsavannah

Ghana

Areas

%

1990/91 2005/06

Increasing needs for data at the sub national

level Policy makers who have participated in training on the use of the Mapper:Recognized the importance of such a tool for

policy decision making: e.g. on which indicator the country should concentrate (off target?)

Insisted on the need to use such a tool at the sub national level: variability across states, regions, provinces, districts

Global (national) trends hide variability at state, region, province… levels

Therefore, the need to make available sub national data and use them with the Mapper

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Some good practices Ethiopia and Ghana: sub national

data used for the MDG presentation at the ECOSOC meeting in Geneva

Other countries:South AfricaZambia

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Challenges Most administrative data (Health,

Education, Access to Water, Sanitation…) and Census data can be disaggregated at lower levels

For data from a HS, the survey needs to be large enough to yield reliable estimates at lower levels

Increased cost of obtaining the information both in terms of human and financial resources

For this reason: few HS provide data at the sub national level

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Opportunities Opportunities include:

Increased demand for data at lower levels

Geographical Information Systems (GIS) technology (poverty mapping)

Collaboration between Central Statistical Offices and sub national statistical institutions

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Conclusions Sub national data disaggregation

needs adequate sample sizes in HSs

Disaggregation to sub national levels needs corresponding responsibilities

Need to use MDG process to support strengthening of disaggregation opportunities

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The Way ForwardThe Way Forward

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Administrative data Assessment of the use of

administrative data by African countries: challenges, constraints

Organize workshops and expert group meetings on the use of administrative data in African countries

Capacity building in terms of training and technical support

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Sub national data production

Organization of a seminar of the need for the production of sub national information for MDG monitoring: end of June 2008

Paris21 task team on the production of sub national data

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Thank Thank you!you!

African Centre for StatisticsAfrican Centre for Statistics

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