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IMPROVING THE TARGETING EFFECTIVENESS OF SOCIAL SAFETY NETS IN BANGLADESH. Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan Kendro (MSUK)

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slide1

IMPROVING THE TARGETING EFFECTIVENESS OF SOCIAL SAFETY NETS IN BANGLADESH

Principal Investigator

AbulBarkat

Co-Investigators

Subhash Kumar Sen Gupta, Abdullah Al Hussain, MatiurRahman &

Faisal Mohammad Ahamed

ManobSaktiUnnayanKendro (MSUK)

House 05, Road 08, Mohammadia Housing Society,

Mohammadpur, Dhaka 1207

Presented at

Workshop on

Research to Inform Food and Nutrition Security Policies

RuposhiBangla Hotel

Dhaka: 3 July, 2013

slide2

Background and Objectives

  • Every 3rd household (31.5%; HIES 2010) live in poverty
  • Social safety net programmes (SSNP) have been mainstay of poverty alleviation strategy since independence
  • Currently, 24.6% HHs (Rural 30.1% & Urban 9.4%) receive SSNP benefit (HIES 2010), which was 13% in 2005
  • In FY 2012-13, Tk. 227.5 billion allocated under Social Protection & Empowerment (11.87% of the budget & equivalent to 2.18% of the GDP) (Social protection 75%; empowerment 25%)
  • Large amount of money spent on SSNP; number of beneficiaries increasing
  • Often questioned – whether most eligible persons receive SSNPs?
  • TARGETING ERROR (both inclusion and exclusion) is thought to be a serious drawback to reach the food insecure and the poor, in addition to capacity constraints (e.g., constrained budget)
slide3

Background and Objectives … contd..

  • This research was expected to:
  • Provide a comprehensive review of SSNP targeting mechanism & errors that will enable GoBto improve targeting so that it better reaches the food insecure and the poor
  • Contribute to achieve major national goals of National Food Policy (2006) & National Food Policy Plan of Action (2008-2015)
  • Objectives:
  • To identify extent of targeting errors in social safety nets by major programmes
  • To recommend ways to decrease inclusion & exclusion errors at the programme-level
  • To identify potential ways forward for building a SSN system in Bangladesh
slide5

The HIES 2010 and SSNP in Bangladesh

  • The HIES 2010 includes (Section 1 Part C) 30 socialsafety net programmes.
  • The respondent households (n=12,240) were asked 7 questions on safety net programmes.
slide6

The HIES 2010 and SSNP in Bangladesh

  • 55% of the SSNP budget spent on programmes listed in HIES 2010;
  • Pension constitute 20% of SSNP budget (Is ‘Pension’ SSNP?)
  • Considering the 30 programmes listed in the HIES is a perfect sample for generalizations about overall public safety net sector
slide7

SSNP Beneficiary Targeting

SSNP

Targeting of Beneficiary

Inclusion Criteria

Exclusion Criteria

Essential Criteria

Priority Criteria

The first research issue is identification of targeting errors which can be grouped as inclusion error—meaning inclusion of non-eligible & exclusion error—meaning exclusion of eligible persons

We have compiled all the eligibility (inclusion & exclusion) criteria for most of the selected public SSNPs from relevant documents of the respective programmes.

Poverty—the most essential targeting criteria

‘Poverty’/’extreme poverty’/’poor household’ is an essential criterion for all the SSNPs along with other criteria such as low income, landlessness, disability, gender, old age, maternity & other vulnerability etc.

slide9

Poverty HCR and SSNP benefit flow

Regional disparity (improper allocation of resources) !!!

  • Highest % of HHs (37.3%) received benefit from SSNPs in Khulna division. On the basis of poverty HCR, Khulna division ranks fourth
  • Poverty HCR is highest in Rangpur division (HCR 46.2% and 30.1% using the Upper and the Lower poverty lines respectively), on the basis of SNP beneficiaries, it ranks 3rd position with 33.7% beneficiary HHs
distribution of beneficiary and non beneficiary hhs by income deciles and residence rural urban
% distribution of beneficiary and non-beneficiary HHs by income deciles and residence (rural-urban)
distribution of beneficiary and non beneficiary hhs by income deciles and residence rural urban1
% distribution of beneficiary and non-beneficiary HHs by income deciles and residence (rural-urban)
slide14

Are the HHs getting SSNP poor?

  • SSNPs are meant for the poor. In Bangladesh, 24.6% HHs receive SSNP (where the poverty rate is 31.5%)
  • Given an ideal situation (i.e., safety net is for the poor), the above figures seem satisfactory. However, the situation is not as ideal as the figures appear. The reality is as below:

SSNP beneficiary HHs below Poverty Lines (HIES, 2010)

slide16

Are these non-poor households borderline poor?

Per capita expenditure of poor HHs and SSN beneficiary HHs

slide17

Poverty status of SSNP beneficiaries with and without SSNP benefit amount

  • Over 60% beneficiaries received ≤ Tk.100 from their respective SSNP in a month;33% received between Tk.100 and Tk.300, and only 4% received between Tk. 301 and Tk.500. What happens if the amount is deducted from the HH income?

If SSNP benefit is deducted from the income of the beneficiary households, poverty rate increases by only 2 percentage points

slide20

% of food expenditure in consumption expenditure

  • 79% of all households spend more than half of their consumption expenditure in food.
  • Rate is highest (92.2%) in lowest income decile.
  • Rate is lowest (44.7%) in top income decile.
  • Distribution by consumption expenditure deciles provide similar result.
slide31

Inclusion error and exclusion error

(considering only poverty)

According to this table, considering only poverty of the households, the inclusion error rate is 14.2% and exclusion error rate is 26.4%.

slide34

% distribution of reason for not receiving SSNP benefit (after applying)

  • 8.1% of the beneficiary HHs reported to have paid bribe in order to receive SSNP benefit
  • Of all the selected SSNPs; Old Age Allowance, Allowance for the Widow, Deserted and Destitute Women and Vulnerable Group Development beneficiaries reported to have paid more bribes
  • The average amount of bribe paid by the beneficiaries is 1074.1 taka (those who reported)
slide35

Sixth Five Year Plan

(FY2011-FY2015)

slide36

On leakage and targeting error in SSNP

in the Sixth Five Year Plan

The Sixth Five Year Plan of the country states coverage issues, targeting beneficiaries, leakages, and disparity in regional distribution etc as the key challenges of implementing SSNPs are. Some of the highlights are as follows:

  • While coverage is relatively low, a significant number of HHs gain access to multiple SSNPs. A quarter of HHs were receiving transfers from more than one SSNP.
  • Over 11% households were participating in at least two of the three programs – VGD, FFE and FFW. Coverage in urban areas remains low.
  • 27% VGD beneficiaries are not poor.
  • 11% participants of PESP meet none of the eligibility criteria; almost none of the beneficiaries meet at least three criteria. Almost 47% PESP beneficiaries are non-poor and incorrectly included in program.
  • All HHs within less-poor Upazila are denied assistance, including those with very high food insecurity.
slide37

On leakage and targeting error in SSNP

in the Sixth Five Year Plan…..contd.

  • Leakage in FFW program is 26%.
  • Leakage in female stipend programs 10%-12%.
  • About 20%-40% budgetary allocations for female secondary stipend program do not reach beneficiaries.
  • Leakages show a strong correlation with number of intermediaries in the transfer process.
  • HIES 2005 showed regional disparity in distribution of households receiving social protection benefits. Barisal and Rajshahi divisions, with the highest incidence of poverty, did not have the correspondingly higher number of social protection beneficiaries. In contrast, Sylhet Division, with the second lowest poverty incidence had the highest proportion of social protection recipients.
slide39

Concluding observations

  • Coverage & budgetary allocation in SSNP sector – increasing every year
  • Every 4th HH is covered by SSNP (HIES 2010)
  • The declining trend of poverty over the years at a rate of 1.7% justifies Government’s spending on SSNP.
  • No concrete evidence that government’s spending on SSNP is being received by the poor and hence poverty is declining.
  • Large number of beneficiary HHs of major SSNPs are not poor at least in terms of official measures of poverty.
  • However, it is also not true that the benefits are being captured by the elites since most beneficiaries are from the lower income deciles.
  • False prioritization (high inclusion error) exists.
slide40

Recommendations

  • Social safety nets and their scope should be defined clearly
  • An extreme poor database should be prepared for easy and error-free selection of beneficiaries. The process could start with a piloting using the poverty map.
  • Geographic targeting of SSNPs should follow the poverty map and it should be revised at least every five years.
  • Targeting criteria of the existing SSNPs should be revised using practical and easily measurable indicators.
  • Implementation of SSNPs should be supervised strictly to reduce political and personal nepotism, bribery and improper prioritizations
slide41

Recommendations

  • Coordination among Departments implementing SSNPs should be strengthened
  • Regular survey/research on coverage, targeting and impact of SSNPs should carry out
  • Awareness in mass media on safety net programmes and their eligibility is essential
  • Tangible vision and clear instructions on effective targeting of social safety net should be in the forthcoming National Social Protection strategy.
slide47

Performance assessment using

programme specific variables

Targeting Efficiency of Old Age Allowance

slide48

Performance assessment using

programme specific variables

Targeting Efficiency of Widow Allowance

slide49

Performance assessment using

programme specific variables

  • Targeting Efficiency of Targeting Efficiency of General Relief Activities
slide50

Performance assessment using

programme specific variables

  • Targeting Efficiency of Vulnerable Group Feeding (VGF)
slide51

Performance assessment using

programme specific variables

  • Targeting Efficiency of Gratuitous Relief-Non-cash
slide52

Performance assessment using

programme specific variables

  • Targeting Efficiency of Stipend for Secondary and Higher Secondary/ Female Student
slide53

Poverty and SSNP beneficiary HHs

(except 2 stipend)

Percentage distribution of the SSNP beneficiary HHs (except 2 stipend programmes) by poverty status in the CBN method, HIES 2010

slide54

Reported reasons for exclusion

Distribution of the reported reasons for not being included in major Public SSNPs

slide55

Multiple beneficiary recipient

  • Status of multiple beneficiary recipient Households in HIES 2010
slide56

Key Research questions by Broad Scopes

The 12 month long research project will make efforts to answer the following research questions at the end of the study:

chi square scores for categories of different demographic characteristics
Chi-Square scores for categories of different demographic characteristics
  • It is evident that there is statistically significant difference in the safety net receiving in the urban and rural areas at 1% level of significance. The different household size is also significant at 1% level of significance for safety net receiving as well as the land ownership categories and age of the head of the household. However, there is no statistically significant difference in the safety net receiving by the sex of the household head at 5% level of significance which is also true for religious identity of the household.
  • It is also found that there is statistically significant difference in the poverty status (both UPL and LPL) in urban and rural areas at 1% level of significance. The different household size is also significant at 1% level of significance for poverty status (both UPL and LPL) as well as the land ownership categories and age of the head of the household. There is no statistically significant difference in the poverty status (for LPL) by the sex of the household head at 5% level of significance which is also true for religious identity of the household.
hh electrification status of ssnp beneficiaries
HH electrification status of SSNP beneficiaries

Nationally 55.26% of the HHs has electricity connections (Rural 42.49%, Urban 90.10%

slide72
% distribution of beneficiary and non-beneficiary HHs by consumption expenditure deciles and residence (rural-urban)
slide73
% distribution of beneficiary and non-beneficiary HHs by consumption expenditure deciles and residence (rural-urban)
distribution of beneficiary hhs of major ssnps by consumption expenditure deciles
% distribution of beneficiary HHs of major SSNPs by consumption expenditure deciles

74

distribution of beneficiary hhs of major ssnps by consumption expenditure deciles1
% distribution of beneficiary HHs of major SSNPs by consumption expenditure deciles

75

estimating the monthly benefit amount received by ssnp beneficiaries
Estimating the Monthly benefit amount received by SSNP beneficiaries
  • Beneficiaries of Safety Net Programmes with Regular Monthly Allowance (in taka) are assumed to receive the fixed amount every month.
  • For the benefits that are given in kind, the money value is estimated.
  • In order to convert the kind benefits to equivalent money value, the per kg value of kind (rice, wheat etc.) is estimated from HIES 2010 data.
  • Benefit that are received once in a year, is divided by 12 to find out the average amount of benefit received in a month.
slide80

Background and Objectives … contd..

  • Recent studies identified 4 potential sources of targeting errors:
    • Mismatch of geographical allocations of resources & poverty rates
    • Use of improper targetting indicators
    • Even if design of SSN targeting mechanism is sound, political economy & implementation issues at local level overrides it
    • Institutional issues at central level foster overlaps and gaps in coverage

Such targeting errors reduce the resources available to support poorest & most food insecure households. Therefore, objective of Government’s spending on SSNPs not fulfilled effectively.

slide81

Methodology and Data Sources …contd…

  • From HIES 2010 data:Analysis made aggregating all beneficiary HHs of all 30 programmes (the term is “public safety net beneficiaries”) together & then for each of the 8 programmes with more than 100 sample HHs.
  • Recent studies conducted by other organizations/individuals: For the remaining programmes, we reviewed recent studies conducted by other organizations/individuals & used their findings.
  • Consultation with experts:For the purpose of drawing inferences on the remaining programmes, we consulted experts who have conducted research on safety net targeting or worked in relevant sectors.
  • Primary data collection:Even after the above three exercises, drawing inferences on some programmes was not possible. For those programmes a survey was conducted to obtain primary data from the beneficiary and eligible non-beneficiary HHs.
slide83

The HIES 2010 and SSNP in Bangladesh

The HIES (2010) includes (Section 1 Part C) 30 social safety net programmes. The respondent households (n=12,240) were asked 7 questions on safety net programmes. The questions covered:

  • Whether the household (any member of the household) has been included in any SSNP in the preceding 12 months
  • If “Yes”, which programme(s)
  • When s/he was included in the programme (month and year)
  • What benefit s/he is entitled to receive from the programme
  • What benefit (cash/kind) s/he has received
  • How much money s/he had to spend to be included in the programme
  • If “not included”, what was the reason for exclusion (both genuine and defects)
  • Other parts of HIES questionnaire include demographic & socioeconomic information of household and members. The broad variables/indicators are:
household demography and receipt of ssnp benefits
Household demography and receipt of SSNP benefits
  • Nationally, households with 7-8 and 5-6 members are ahead of other household sizes in terms of receipt of SSNP benefit. Respectively 29% and 28% of beneficiary households are of these sizes.
  • In rural areas, every 3rd beneficiary household consists of 1-2 members.
  • Nationally, 86% households are male headed & 14% female headed. Of SSNP beneficiary households, 85% male headed and 15% female headed.
  • A 30% household receive SSNP benefit where household head is more than 60 years old.
slide87

Methodology and Data Sources

As per ToR, Household Income and Expenditure Survey (HIES) was the major data source to investigate into targeting performance (inclusion and exclusion errors) of public SSNPs in general and by individual programmes in particular.

  • The methodology was designed assigning special emphasis on analysis of relevant HIES data.
  • Preliminary investigation revealed that out of 30 public SSNPs included in HIES 2010, more than 20 programmes have <100 samples (very negligible compared to their countrywide beneficiaries).
  • (e.g., only 4 beneficiary HHs of Maternity Allowance programme included in HIES whose national beneficiary is 88,000.)
  • To avoid representation problem, study methodology was redesigned in consultation with TAT members & other experts at FAO/NFPCSP.
ssnp beneficiary hhs and land ownership status
SSNP Beneficiary HHs and land ownership status
  • Landlessness or HHs with less than 15 decimal of land is an essential/priority criterion for SSNPs such as Old Age Allowance, Widow Allowance, Disability Allowance, VGD, VGF, Maternal Voucher Scheme, Employment Generation for Extreme Poor (former 100 Days EGP) etc
poverty ssnp beneficiaries and literacy status
Poverty, SSNP beneficiaries and literacy status
  • Literacy status of beneficiaries of individual programmes (% literate):
  • Old age Allowance (13. 6)
  • Widowed Allowance (13.9)
  • Housing Support (20)
  • Test Relief (25)
  • Allowance for Insolvent Disabled (28.1) VGF (28.5)
  • Cash for Work (29.4)
  • VGD (30)
  • Gratuitous Relief (36.4)
  • Open market sales (37.5)
  • Agriculture Rehabilitation (44.1),
housing sanitation electricity and availability of cell phone
Housing, sanitation, electricity and availability of cell phone
  • 21% have muddy wall and another 26% have walls made of hemp, hay, bamboo.
  • 4% have roof made of mud, tally and wood while only 3% have concrete made roof.
  • Very negligible number of beneficiary households of the programmes designed for the ultra poor or other vulnerable groups (e.g., old age allowance, widow allowance, disability allowance, VGD, VGF, GR, TR, FFW etc) have walls or roofs made of brick/cement.
  • Only 11% beneficiary households have sanitary latrines.
  • 39% beneficiary households have electricity connections at their residences. Nationally, 55% HHs have electricity connections (rural 42.5%, urban 90%
  • Regardless of programmes, more than half (51.1%) beneficiary households own cell phone. Nationally, 64% households have cell phone.
  • No data is available for individuals in the HIES.