1

Principal Investigator

Dr. Ismat Ara Begum Department of Agricultural Economics

BAU, Mymensingh-2202

SOCIAL SAFETY NETS AND PRODUCTIVE OUTCOMES: EVIDENCE AND IMPLICATIONS FOR BANGLADESH

Draft Results Prepared for Presentation at NFPCSP-FAO Workshop

3-4 July, 2013; Dhaka, Bangladesh

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Research Team

Prof. Dr. Shaheen AkterCo-Investigator

Prof. Noor Md. Rahmatullah Co-Investigator

Dr. Mohammad Jahangir AlamCo-Investigator

Dr. M. Sayeedul HaqueResearch Assistant

Md. Mojammel Haque Research Assistant

Ferdoushi BegumResearch Assistant

Social safety net programs (SSNPs) are non-contributory transfer programs designed & implemented for the poor & the vulnerable groups

These groups are always a concern to the Bangladesh govt.

One of the main agenda of govt. is reduction of poverty.

Like many other developing countries, SSNPs can play a vital role to reduce poverty in Bangladesh.

Safety net spending is around 15% of the Bangladesh govt. expenditure and 24.57 % HHs received benefit from SSNPs in 2010

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Introduction

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31.5 % of households in the country live in poverty

So, it remains unclear whether SSNPs only prevent entry into poverty or promoting exit from poverty or both

Studies investigated ONLY targeting, delivery mechanism, operational performance, alternative design etc., of SSNPs

However, evidence about the productive outcome impacts at household and community levels is scarce

This research will contribute to understand –

Whether selected SSNPs are generating productive outcomes & are contributing to households’ exit from poverty and food insecurity

What constraints or enabling factors are mediating these outcomes

To document potential productive impacts of selected public safety nets at the household and community levels and the possible incentive framework behind those results at the two levels

To identify successful examples of government and NGO safety net interventions which foster productive outcomes

To draw implications for the design and implementation of SSN in Bangladesh and for complementarities among government agencies interventions

Objectives

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Impact

GoalFood Security

Poverty reductionCredit accessibility

Risk coping Preventing school drop-out

Community Level

•Goods and labour markets

•Multiplier effects in local economy

•Creation of community level assets/ infrastructure

•Gender inequalities

Household Level•Labor allocation (farm vs off farm, adults vs children)•Asset accumulation/protection•Change in use of inputs and techniques in crop production•Consumption/food security•Human capital accumulation•Investments•Risk coping strategies

Mechanism

Pathways

Income effectProductivity effectPurchasing power effect

Alleviation of liquidity constraints

Certainty & predictability of income

Promoting child education Optimal intrahousehold

resource allocation

Poor and Vulnerable People

Intervention

Social Safety net Programs Cash/Kind /Training

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Household levelHypothesis:SSN interventions either cash or kind (conditional, unconditional, public works) may facilitate significant changes in income generating activities, labour allocation, accumulation of productive assets & productive investments of beneficiary household than non-beneficiary households.

Research QuestionsWhat are the productive outcomes of selected public safety nets at the household level?

MethodologyFor estimating impact we used propensity score matching (PSM) We used HIES 2010 as a single cross section for identifying the treatment & control groups

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HypothesisThe community will benefit economically from social safety nets interventions through local goods & labour markets and multiplier effects

Research QuestionWhat are the productive outcomes of SSNP at the community level?

Local goods (buying-selling activities, prices etc.)Labour markets (new employment, employ. diversification, wages

etc)Multiplier effects (investment, employment, economic growth)

Local Economy Level

MethodologyHIES community dataset, FGD (30) and KII(20)

The study is designed to conduct into three phases

Phase 1 → Literature review & assess the productive impacts of selected SSNs at household level in Bangladesh (HIES data and Impact results)

Phase 2 → presents the impact at community level and recent evidence and documents on the productive outcomes of the safety nets in Bangladesh and other countries (Field survey, literature review,)

Phase 3 → Deals with the issues of enhancing the productive outcomes of the SSNPs (Impact results, SSN-IMPACT matrix & FGDs and KIIs results)

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Study Phasing

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For estimating productive outcomes we considered -

Interventions with an explicit income-generation component

Old age allowance Allowances for the widowed, destitute and deserted women Agriculture rehabilitation A combination of

Cash for work, VGD, food for work & 100 days scheme

Interventions with no explicit income-generation component

Stipend for primary students Stipend for secondary and higher secondary/female students

Phase 1: Literature review, estimating productive outcomes at household level

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Table1 : Number of beneficiary households of the selected SSNPs in HIES 2010Program group

Selected SSNPs Selection Criteria Beneficiary HHs

% of ben.HHs

1 Old Age Allowance (OAA) Extreme poor by income threshold and age restriction (65+ male and 62+ female) 485 27.0

2 Allowance for the Widowed, Deserted and Destitute (AWDD)

Bangladeshi, widow, divorced, deserted women, wealth less, homeless and landless 203 11.3

3 Combined program (CFW, VGD, FFW, EGP 100 days)

Poor based on different criteria41 2.3

4 Agriculture Rehabilitation Poor farmers and fishers 446 24.95 Stipend for Primary Students Students from poor households

with attendance 85% 444 24.76 Stipend for Secondary & Higher

Secondary/Female StudentFemale students having attendance 75% and marks 45% 176 9.8

Total 1795 100

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Table2: Measurable productive outcome indicators at household level

Outcomes Indicator Measurable indicator

Imputed from 2010 HIES

Labour allocation

Relative ( farm , non-farm, male, female, self) employment

Average working hours per day per worker

Calculating daily male and female hours in farm , non-farm activities

Income generating activities

Total no. of activities involved, Total (farm, non-farm)income,

Number of total activities per household per active member

Calculate total number of activities, Calculating total income (farm, non-farm)

Investments Own land per person, Real expenditure on tools, animals, family enterprises, durable goods & housing improvement per household

per person/household

Calculate own land , hhs expenditure

Shock and coping mechanism

Asset sold ,Insurance, migration, school drop-out

Dummy variable: 1 and 0

Shock and coping mechanism

Consumption Per capita Calculating Sum of per capita value of food and non-food expenditure.

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n

i

Ci

Ti YY

nI

1

)(1

For estimating impact we used propensity score matching (PSM)

We used HIES 2010 as a single cross section for identifying the treatment & control groups

Mathematically, average impact of program could be expressed as follows (Rubin 1974, Ravallion 2008):

Methodology (2)

YiC → outcome for household i when it is not exposed to the safety net

program

YiT → outcome for household i when it is exposed to the program

Impact of the program I= YiT- Yi

C

IMPACT OF OLD AGE ALLOWANCE ON PRODUCTIVE OUTCOMES

Sample size was 4325 including 485 treated households. Various indicators were chosen in the areas of labor

allocation, income generating activities, investment and shock coping strategies.

All indicators produced insignificant average treatment effect on the treated (ATT) based on Nearest Neighbor Matching (NNM).

OAA is making positive contribution to labor allocation to non-farm activities and helping to investment more in agricultural assets. Access to credit may also be rising due to OAA.

The results are not statistically significant, it is not possible to make firm conclusions.

Outcome indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

ATT t value

Working hour per day 11.00 11.05 -0.04 -0.06Number of non-farm activities 1.54 1.50 0.04 0.29Self-employed at non-farm (av. number) 0.34 0.31 0.03 0.57Self-employed at farm (av. number) 0.42 0.49 -0.07 -1.16Annual salary received from non-farm (Tk)

12585.39 17965.65 -5380.26 -1.11

Value of agricultural assets 5315.67 2132.21 3183.46 0.82Spending in fertilizer (Tk/farm) 569.36 738.08 -168.72 -1.2Total credit 5787.84 5621.65 166.19 0.07Land purchased 0.01 0.01 0.00 -0.46Purchased agricultural tools 3732.19 49.32 3682.87 1.09Expenditure on non- food items 39998.82 40378.83 -380.01 -0.07Annual expenses on durable goods (Tk) 6076.52 3082.35 2994.18 1.3Annual income from crop production (Tk) 9266.94 12111.51 -2844.56 -0.81Annual Food Expenditure (Tk) 364806.02 391234.07 -26428.05 -1.25

Table3 : Impact of Old Age Allowance on productive outcomes in Bangladesh

In Bangladesh OAA receivers are one of the most income vulnerable groups and the amount received is extremely inadequate. This may reflect in the results.

IMPACT OF AGRICULTURE REHABILITATION PROGRAM ON PRODUCTIVE OUTCOMES

Analysis is based on 4286 households of which 446 are beneficiaries of ARP.

ATT was significant for income generating activities (farm and non-farm), labor allocation (farm and non-farm self-employment), and investment (agricultural assets, inputs).

Farm activities increased by 0.37 units per household due to intervention. At the same time non-farm activity declined by 0.72 units.

One of the areas of reduction of labor unit is day laborer in non-farm sector. This indicates that farmers may save time by involving in higher paid farming than day laborer activities in non-farm sector.

Access to credit is reducing for the safety net and they might be depleting some assets during shock (results are not statistically significant for credit and asset sold due to shock variables).

Indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

Difference /ATT

t value

Number of farm activities 0.94 0.57 0.37 7.75Number of non-farm activities 1.16 1.71 -0.56 -4.27Day laborer in non-farm activities 0.12 0.22 -0.10 -3.35Self- employed at farm activities 1.46 0.78 0.68 9.74Self-employed at non-farm (av. number) 0.34 0.47 -0.13 -2.04Annual salary received from non-farm (Tk) 16915.92 25635.58 -8719.66 -1.59Income from livestock production 8213.77 5988.32 2225.45 1.86Value of agricultural assets (Tk) 15969.10 6195.55 9773.56 3.37Spending in fertilizer (Tk/farm) 4135.11 1911.02 2224.08 5.02Total credit 8911.43 10648.65 -1737.22 -0.42Distress sell (asset sold) 0.06 0.03 0.02 1.64Land purchased (yes=1) 0.06 0.04 0.02 1.25Agricultural tools purchased 1049.13 553.39 495.73 0.68Annual expenses on durable goods (Tk) 6279.18 6232.49 46.69 0.03Annual income from crop production (Tk) 54771.11 26231.54 28539.58 5.85Income from vegetables production 6147.78 5005.38 1142.40 0.73Annual Food Expenditure (Tk) 510080.11 494596.49 15483.62 0.77

Table 4: Impact of Agriculture Rehabilitation Program on productive outcomes

ARP is a promising means of safety net for the marginal and small farmers. This type of safety net for farming communities could contribute more to productive outcomes.

IMPACT OF AWDD ON PRODUCTIVE OUTCOMES

The sample size was 4043 households of which 203 are beneficiaries of AWDD.

The beneficiaries in this program worked less hours, but involved more in non-farm activities due to program.

AWDD is making positive contribution to labor allocation in non-farm activities & self employment in non-farm sectors.

AWDD is helping to spend more in food and health. Access to credit may also be rising due to AWDD.

As these results are not statistically significant, it is not possible to make firm conclusions.

Indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

Difference /ATT

t value

Working hour per day 10.53 10.98 -0.45 -0.54Number of non-farm activities 1.46 1.26 0.20 1.19Self-employed at non-farm (av. number) 0.29 0.27 0.02 0.26Annual salary received from non-farm (Tk) 9384.93 15255.58 -5870.66 -1.17Annual income from livestock (Tk) 2208.19 4612.41 -2404.23 -2.32Value of agricultural assets 705.02 4141.13 -3436.11 -2.72Spending in fertilizer (Tk/farm) 773.06 1024.82 -251.76 -1.02Total credit 4936.21 4534.48 401.72 0.27Land purchased (yes=1) 0.00 0.03 -0.02 -1.9Non-food expenses (Tk) 33468.16 36404.03 -2935.87 -1.21Annual expenses on durable goods (Tk) 2416.01 3541.38 -1125.37 -1.05Annual Food Expenditure (Tk) 346637.13 341914.00 4723.13 0.23Annual Health Expenditure (Tk) 600.4 353.8 246.7 1.58

Table 5: Impact of AWDD on productive outcomes in Bangladesh, 2010

IMPACT OF PRIMARY SCHOOL STIPEND ON PRODUCTIVE OUTCOMES

Analysis is based on 4284 households of which 444 are beneficiaries of SPE.

The ATT was significant for non-farm income generating activities, labor allocation in non-farm wage labor, and annual non-food expenses.

Thus safety net in primary education program is playing very little role on short term impact on productive outcome.

We haven't examined here the impact on enrollment, dropout, attendance etc. because they are well documented in the literature confirming positive roles.

So there is no doubt that the program has been playing useful role in human capital development and that may be the reason for significant impact on non-farm activities.

Indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

Difference /ATT

t value

Number of farm activities 0.60 0.66 -0.06 -0.93Number of non-farm activities 1.74 1.46 0.28 2.19Day-laborer in non-farm activities 0.31 0.19 0.12 3.81Self-employed at farm activities 0.61 0.63 -0.02 -0.26Self-employed at non-farm (av. number) 0.55 0.55 0.00 0.07Annual salary received from non-farm (Tk) 11100.54 9085.60 2014.94 0.83Income from livestock production 5459.95 4538.69 921.26 0.55Value of agricultural assets (Tk) 6053.90 5101.76 952.14 0.39Spending in fertilizer (Tk/farm) 962.22 1493.66 -531.44 -0.87Total credit 11616.67 14874.77 -3258.11 -0.35Agricultural tools purchased 1046.58 809.03 237.55 0.29Annual non-food expenses (Tk) 42798.61 50449.31 -7650.71 -2.11Annual expenses on durable goods (Tk) 3397.31 5119.98 -1722.67 -1.54Annual income from crop production (Tk) 15712.61 15688.14 24.47 0.01Income from vegetables production 2918.06 2862.63 55.43 0.05Annual Food Expenditure (Tk) 45168.60 47910.19 -27424.59 -1.53Annual Education Expenditure (Tk) 4509.41 4981.19 -471.79 -0.76Annual Health Expenditure (Tk.) 824.58 556.24 268.35 1.72

Table 6: Impact of Primary school stipend on productive outcomes in Bangladesh, 2010

IMPACT OF SSHE PROGRAM ON PRODUCTIVE OUTCOMES

Analysis is based on 4016 households of which 176 are beneficiaries of SSHE.

The ATT was significant only for non-farm self-employment and investment in agricultural asset.

Non-farm self-employment increased and at the same time value of agricultural assets decreased.

Health expenditure is significant at 10 percent level and is rising due to program.

Thus safety net in secondary education program is playing very little role on short term impact on productive outcome.

Indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

Difference /ATT

t value

Number of non-farm activities 1.99 1.76 0.23 1.07day_lab_non-farm 0.17 0.15 0.02 0.4self_emp_Farm 0.67 0.59 0.08 0.77Self-employed at non-farm (av. number) 0.68 0.34 0.34 3.59Annual salary received from non-farm (Tk) 42445.60 32772.68 9672.92 0.99Income from livestock production 6636.42 7032.15 -395.73 -0.2Value of agricultural assets (Tk) 4621.59 11844.66 -7223.07 -2.28Spending in fertilizer (Tk/farm) 1877.87 2028.89 -151.02 -0.3Total credit 25295.45 57354.55 -32059.09 -1.53Agricultural tools purchased 108.41 105.63 2.78 0.04Annual non-food expenses (Tk) 60158.66 73398.46 -13239.80 -1.46Annual expenses on durable goods (Tk) 11901.73 6063.86 5837.86 0.98Annual income from crop production (Tk) 21391.54 27222.22 -5830.68 -1.06income_veg 4679.35 4084.61 594.73 0.31Annual Food Expenditure (Tk) 58062.93 56558.52 15046.41 0.34Annual Education Expenditure (Tk) 13472.40 10671.86 2800.54 1.41Annual Health Expenditure (Tk) 981.98 458.84 523.15 1.95

Table7 : Impact of SSHE Program on productive outcomes in Bangladesh

IMPACT OF COMBINED PROGRAM

Analysis is based on 3881 households of which 41 are beneficiaries of combined program

A combination of Cash for work, VGD, food for work & 100 days

Employment scheme The ATT was not significant for any of the indicators.

Outcome indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

ATT t value

Working hour per day 13.41 9.34 4.07 0.80Number of non-farm activities 1.85 0.54 1.32 1.07Self-employed at non-farm (av. number) 0.39 0.05 0.34 1.05Self-employed at farm (av. number) 0.54 0.24 0.29 0.68Annual salary received from non-farm (TK) 12722.00 3963.41 8758.59 0.76Value of agricultural assets 991.22 380.49 610.73 0.67Spending in fertilizer (Tk/farm) 675.12 643.29 31.83 0.03Total credit 8560.98 4536.59 4024.39 1.03Land purchased 0 0 0Purchased agricultural tools 65.12 219.51 -154.39 -0.34Expenditure on non- food items 31392.15 35744.54 -4352.39 -0.44Annual expenses on durable goods (TK) 1702.93 731.71 971.22 0.38Annual income from crop production (TK) 7767.56 11063.41 -3295.85 -0.17Annual Food Expenditure (TK) 37761.90 47745.22 -9983.32 -0.21

Table8 : Impact of combined SSNPs on productive outcomes in Bangladesh

The combined program has only 41 beneficiary households in the sample and so one must consider the result with caution.

IMPACT OF ALL SELECTED SSNPS ON PRODUCTIVE OUTCOMES

Analysis is based on 5635 households of which 1795 are beneficiaries of all selected SSNPs.

ATT was significant for income generating activities (farm), labor allocation (farm self-employment), and investment (agricultural inputs).

Selected safety net programs are promising means for the vulnerable groups.

Access to credit is reducing for the safety net.

Outcome indicators Beneficiary households(Treatment)

Non-beneficiary households

(Control)

ATT t value

Working hour per day 12.08 12.76 -0.68 -1.93Number of non-farm activities 1.54 1.58 -0.04 -0.55Self-employed at non-farm (av. number) 0.42 0.41 0.01 0.23Self-employed at farm (av. number) 0.75 0.62 0.13 3.45Annual salary received from non-farm (Tk) 15863.08 14456.95 1406.12 0.64Value of agricultural assets 7457.05 4595.38 2861.67 1.88Spending in fertilizer (Tk/farm) 1706.26 1236.86 469.40 3.42Total credit 9885.49 11152.42 -1266.94 -0.38Land purchased 0.03 0.03 0.00 0.08Purchased agricultural tools 1549.23 565.30 983.94 1.01Expenditure on non- food items 44334.09 45673.57 -1339.48 -0.62Annual expenses on durable goods (Tk) 5521.45 4810.17 711.29 0.69Annual income from crop production (Tk) 23186.56 17803.47 5383.09 3.51Annual Food Expenditure (Tk) 44179.04 46190.47 -2011.43 -1.61

Table9 : Impact of all selected SSNPs on productive outcomes in Bangladesh

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In conclusion, We have found that OAA and AWDD are making positive contribution to some productive outcomes but as these results are not found statistically significant in our study, therefore it is not possible to make firm conclusions. Safety net in primary and secondary education program are also playing very little role on short term impact on productive outcome. Analysis suggests that ARP is a promising means of safety net for the marginal and small farmers. ATT of ARP produced significant effects on income generating activities (farm and non-farm), labor allocation (farm and non-farm self-employment), and investment (agricultural assets, inputs)

PHASE 2: FGD FINDINGS:UTILIZATION OF SSNP SUPPORTS & HOUSEHOLD

INCOME

Consumption and health were main heads on which beneficiaries spent major share of their received SSNP supports followed by household items, school cost, agricultural inputs, savings and investment.

About 50% of the beneficiaries of OAA spent their full receipt on purchase of medicine.

SNP supports were also spent on repayment of credit. A very few of the beneficiaries were found to spend their SSNP

supports on investment purposes. Purchasing poultry birds & goats; agricultural inputs; housing

improvements and human capital (school fees) were major heads of investment by the SSNP beneficiaries.

HOUSEHOLD INCOME

About 87, 5 and 8 percent of FGD participants stated that their household income was increased, decreased and no changed respectively.

High price of daily essentials compelled the participants to work hard for more hours.

Increased wage rate gives them more earning from same working hours. In addition, engagement of part time works by the women and children of the households also helped them to raise their household income.

LABOUR MARKETS

Many of the male and female beneficiaries were found to allocate their labour from farm to non-farm activities.

Many female beneficiaries of AWDD had to hire out of labour in non-farm activities, particularly for repairing/ reconstructing of their living houses.

Non-farm labour wages increased higher than farm wages both for men and women

GOODS MARKETS Changes in selling of farm/non-farm products to the

local/village markets were observed by the most of the participant beneficiaries

Non-beneficiary FGD participants opined that SSN supports are offering very few new market opportunities for all people in the locality.

All of the beneficiary and non-beneficiary participants claimed that price of daily essentials increased very much.

Almost all of the beneficiary and non-beneficiary participants argued that SSN supports did not affect general price level at all in the study areas.

COPING MECHANISMS AND MULTIPLIER EFFECTS

The FGD participants were experienced several shocks last year such as price hikes, illness or accident of the earning members and death of income earners.

Consumption reduction, sales of household durables, employing children, borrowing from neighbours were major coping mechanisms during shock.

Almost all of the beneficiaries preferred for SSN supports as risk resilience and coping.

All of the beneficiary and non-beneficiary participants thought that the community is benefited from SSN supports.

Construction and repair of roads, dike, and bridge with SSN supports are found in rural areas. On the contrary, no such evidence was observed in urban areas.

GENDER INEQUALITY

Most of the beneficiary and non-beneficiary were found to take decision jointly.

In few cases male were found to dominate in decision making. They thought that women have no intellectual ability and experience.

RECOMMENDATIONS AND ADJUSTMENT In conclusion, in most of the cases we did not find any direct

causality between SSNPs and productive outcome . Specific SSNPs designed for particular group of affected/

needy/vulnerable people. However, OAA was preferred by majority of the FGD

participants. Because, it is available for both male and female.

All the beneficiaries & non-beneficiaries urged to expand the existing SSNPs covering more people with higher amount.

Biasness, nepotism and bribing to be provided in availing SSNs are major problem as mentioned by most of the non-beneficiaries.

1)What are the successful examples of government & NGOs safety nets interventions which foster productive outcomes?

2)What are the recommendations for adjustment and actions?

3)What would be the alternative coordination/ integration mechanism at the local and central level?

Research Questions

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Phase 2: Enhancing the productive outcomes of the SSN

For RQ (1)

International as well as regional programs similar to interventions has been reviewed Particularly we aim to identify productive roles of widely cited safety net programs. Program-impact matrix on the process of developed

Productive outcome

SSNPs supported /SSNPs reviewed

Name of SSNPs

Avail nutrition/food security/child health, Satisfy consumption

21/30 VGD, IGVGD, FFW, FFE, RMP, FFA, FSVGD, VGF, TUP, Old age pension, PES, AWDD, CFW, PDS, ICDS, MDM, SSA (Old Age Benefit), Progresa, Social Pension (BPC), Bolsa Familia, RPS, DECT, SCT, CT-OVC,

Increase income/Savings

19/30 FFW, FSVGD, RMP, IGVGD, FFA, Old age pension, TUP, PES, FSSP, EGS, Zakat, Ushr, EOBI, SSA (Old Age Benefit), Progresa, RPS, DECT, SCT, PSNP, CT-OVC,

Create Asset (livestock/poultry) 11/30 VGD, IGVGD, TUP, RMP, PES, Progresa, RPS, SCT,

Increase school enrolment and reduce dropout

14/30 VGD, FFE, TUP, FSSP, Ushr, Shamurdhi, Social Pension (BPC), Bolsa Familia, RPS, DECT, SCT, CT-OVC,

Enhance agricultural investment/Productivity/Land ownership

10/30 IGVGD, TUP, EGS, Shamurdhi, Progresa, RPS, SCT,

Ease access to credit 10/30 IGVGD, TUP, AWDD, EGS, Social Pension (BPC), RPS, SCT, CT-OVC,

Increase risk bearing ability/coping

7/30 VGD, PES, CFW, EGS, Progresa, RPS,

Initiate new business 4/30 VGD, Progresa, DECT, Empower women 2/30 AWDD

Table: Household Level Productive Outcomes of SSNPs

DETERMINATION OF RELATIVE STRENGTH AND WEAKNESS OF SSPS

Out of 30 studies, 19 studies covering 25 SSNs in South Asia & around the world and rest 11 Studies covering 12 SSNs in Bangladesh.

Entire studies were conducted over last 20 years. Each study covered at least a single SSNP, However some studies

covered several SSNPs. Each of the studies revealed one to several productive outcome

indicators to measure the direct and indirect impact of SSNPs. Reviewing all of the productive outcome indicators of all studies,

most common 8 outcomes at household level, those directly affect by SSNPs were chosen to determine the relative strength and weakness of SSPs in our study.

PROGRAM-WISE IMPACT OF SSNPS IN BANGLADESH

PROGRAM-WISE IMPACT OF SSNPS IN SOUTH ASIA (EXCLUDES BANGLADESH)

PROGRAM-WISE IMPACT OF SSNPS IN THE WORLD (EXCLUDES SOUTH ASIA)

STRENGTH & WEAKNESS Relative strength or weakness of a particular SSN were categories according

to the numbers of outcomes (out of 8 indicator outcomes) positively affected by that SSN.

Strong (*****) to weak (*) were calculated based upon the following scale 0 > 10 = *; 11 to 24% =** 25 to 49 = ***; 50 to 74 = ****; 75 to 100= *****

The concept of this rate of evidence or scale is adopted from Harold Alderman and Ruslan Yemtsov (2012), and Grosh et al. (2008).

However, This is, of course, highly subjective and relative, but this is precisely our aim here to identify the successful example of SSNPs.

TABL

E: P

ROD

UCT

IVE

OU

TCO

MES

OF

SSN

PS:

STRE

NG

TH A

ND

WEA

KNES

SES

OF

WO

RLD

WID

E PR

OG

RAM

S

44