Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain,...

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Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan Kendro (MSUK) House 05, Road 08, Mohammadia Housing Society, Mohammadpur, Dhaka 1207 IMPROVING THE TARGETING EFFECTIVENESS OF SOCIAL SAFETY NETS IN BANGLADESH Presented at Workshop on Research to Inform Food and Nutrition Security Policies Ruposhi Bangla Hotel Dhaka: 3 July, 2013

Transcript of Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain,...

Page 1: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Principal InvestigatorAbul Barkat

Co-InvestigatorsSubhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman &

Faisal Mohammad Ahamed

Manob Sakti Unnayan Kendro (MSUK)House 05, Road 08, Mohammadia Housing Society,

Mohammadpur, Dhaka 1207

IMPROVING THE TARGETING EFFECTIVENESS OF SOCIAL SAFETY NETS IN BANGLADESH

Presented at

Workshop onResearch to Inform Food and Nutrition Security Policies

Ruposhi Bangla Hotel

Dhaka: 3 July, 2013

Page 2: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Background and Objectives

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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 increasingOften 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)

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This research was expected to: Provide a comprehensive review of SSNP targeting mechanism &

errors that will enable GoB to 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

Background and Objectives … contd..

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Major Findings based on Secondary Analysis of HIES 2010

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• 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 HIES 2010 and SSNP in Bangladesh

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The HIES 2010 and SSNP in Bangladesh

Programme Types

Total public spending on SSNP (FY 2012-13)

Budgetary allocations (for HIES-2010 Programmes)

Total Amount (in billion Taka)

Pension Amount (in billion Taka)

Amount without Pension (in

billion Taka)

% Total Amount

% without Pension

Social Protection Programmes

169.4 45.2 124.2 59.6 81.3

Social Empowerment Programmes

58.2 0 58.2 42.9 42.9

Total SSNP Budget

227.6 45.2 182.4 55.4 69.1

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

Page 7: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

SSNP Beneficiary Targeting 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

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.

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SSNP Targeting of Beneficiary

Inclusion Criteria Exclusion Criteria

Priority CriteriaEssential Criteria

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

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Poverty, Income, Expenditure and Social Safety Net

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Poverty HCR and SSNP benefit flow

Division% of HH receiving SSNP Benefit

(Survey Year 2010)Incidence of poverty (HCR) by

CBN Method (HIES 2010)Total Rural Urban Total Rural Urban

National 24.6 30.1 9.4 31.5 35.2 21.3Barisal 34.4 37.2 20.7 39.4 39.2 39.9Chittagong 20.0 24.5 7.4 26.2 31.0 11.8Dhaka 18.9 27.8 6.0 30.5 38.8 18.0Khulna 37.3 43.3 16.7 32.1 31.0 35.8Rajshahi 20.7 22.9 10.2 35.7 36.6 30.7Rangpur 33.7 35.1 23.7 46.2 47.2 37.0Sylhet 23.5 26.1 10.5 28.1 30.5 15.0

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

Regional disparity (improper allocation of resources) !!!

Page 10: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

% distribution of beneficiary and non-beneficiary HHs by income deciles and residence (rural-urban)

Household Income Deciles

SSN beneficiary households (%) Non-beneficiary households (%)

National Rural Urban National Rural Urban

Lower 5% 7.0 7.3 5.7 4.4 5.7 2.4

Decile-1 13.3 6.9 9.8 8.9 12.0 4.5

Decile-2 11.7 12.5 8.8 9.5 11.3 7.0

Decile-3 12.0 13.3 7.0 9.3 10.9 7.1

Decile-4 11.9 12.3 10.2 9.4 9.5 9.1

Decile-5 12.0 11.6 13.7 9.4 10.0 8.4

Decile-6 10.3 9.6 13.0 9.9 9.6 10.3

Decile-7 10.0 9.6 11.5 10.0 10.0 10.0

Decile-8 8.2 7.8 9.9 10.6 9.5 12.2

Decile-9 6.0 5.2 9.1 11.3 9.3 14.2

Decile-10 4.6 2.8 7.0 11.8 8.1 17.1

Top 5% 1.6 1.1 3.4 6.1 3.9 9.3

Total 100.0 100.0 100.0 100.0 100.0 100.0

N 2,989 2,374 615 9,251 5,466 3,785 10

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% distribution of beneficiary and non-beneficiary HHs by income deciles and residence (rural-urban)

Household Income Deciles

SSN beneficiary households (%) Non-beneficiary households (%)

National Rural Urban National Rural Urban

Lowest 5%

7.0 7.3 5.7 4.4 5.7 2.4

Bottom 4 deciles

48.9 45.0 35.8 37.1 43.7 27.7

Middle 3 deciles

32.3 30.8 38.2 29.3 29.6 28.7

Top 3 deciles

18.8 15.8 26.0 33.7 26.9 43.5

Top 5% 1.6 1.1 3.4 6.1 3.9 9.3

Total 100.0 100.0 100.0 100.0 100.0 100.0

N 2,989 2,374 615 9,251 5,466 3,78511

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% distribution of beneficiary HH of major SSNPs by income deciles

Major Safety Net Programmes (HIES

2010)

Household Income Deciles (HIES 2010)

L5% D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 T5%

Old Age Allowance 16.3 26.2 11.1 10.8 10.2 10.0 8.8 8.8 6.3 4.7 3.2 0.9

Allowances for the Widowed, Deserted and Destitute Women

16.8 21.4 14.3 12.6 10.9 12.6 10.5 8.4 5.5 2.1 1.7 0.4

General Relief Activities 6.0 13.6 10.9 12.8 14.7 12.5 12.1 11.3 6.8 3.4 1.9 0.0

Agriculture Rehabilitation 3.3 8.4 11.7 9.0 9.0 11.5 9.5 13.4 9.7 10.4 7.3 2.6

Vulnerable Group Feeding (VGF) 2.5 12.3 12.3 13.1 15.6 9.0 17.2 11.5 7.4 1.6 0.0 0.0

Gratuitous Relief (GR)- Non-cash 3.2 9.3 13.4 15.0 14.2 16.6 11.5 7.9 8.3 2.2 1.6 0.2

Stipend for Primary Students 3.3 8.9 13.7 12.9 13.7 12.4 10.0 9.2 7.4 6.0 6.0 2.0

Secondary and Higher Secondary Stipend 3.1 6.5 7.3 8.5 10.8 9.2 12.7 8.5 12.3 13.9 10.4 5.0

Only programmes with more than 100 beneficiary households in the HIES 2010 considered.12

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% distribution of beneficiary HH of major SSNPs by income deciles

Major Safety Net Programmes (HIES

2010)

Household Income Deciles (HIES 2010)

Lowest 5%

Bottom 4 deciles Middle 3 deciles Top 3 decilesTop 5%

Old Age Allowance 16.3 58.3 27.5 14.2 0.9

Allowances for the Widowed, Deserted and Destitute Women

16.8 59.2 31.5 9.3 0.4

General Relief Activities 6.0 52.0 35.9 12.1 0.0

Agriculture Rehabilitation 3.3 38.1 34.5 27.4 2.6

Vulnerable Group Feeding (VGF) 2.5 54.3 36.7 9.0 0.0

Gratuitous Relief (GR)- Non-cash 3.2 51.9 36 12.1 0.2

Stipend for Primary Students 3.3 48.2 32.4 19.4 2.0

Secondary and Higher Secondary Stipend 3.1 33.1 30.3 36.6 5.0

Only programmes with more than 100 beneficiary households in the HIES 2010 considered.13

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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:

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All Rural Urban

40.5 40.2 41.6

24.0 25.020.0

Below Upper Poverty Line Below Lower Poverty Line

SSNP beneficiary HHs below Poverty Lines (HIES, 2010)

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Barisal

Chittagong

Dhaka

Khulna

Rajshahi

Rangpur

Sylhet

National

44.2

31.7

30.4

46.3

19.7

41.1

29.2

34.3

% distribution of HHs below UPL receiving SSNP benefit (HIES, 2010)

Poverty and receipt of SSNP benefit

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Per capita expenditure of poor HHs and SSN beneficiary HHs

Are these non-poor households borderline poor?

Per capita expenditure of SSNP beneficiary HHs

Per capita expenditure of poor (UPL)

Per capita expenditure of poor (LPL)

1931

1200 1056

2573

14581133

1997

12461064

Rural Urban All

Page 17: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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

Benefit amount included in income Benefit amount deducted from income

40.5% 42.6%

20.4%26.6%

Poverty Status Below UPL Poverty Status Below LPL

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Poverty status of beneficiary household (without the benefit amount) by shifted Upper poverty line

10% above 20% above 30% above 40% above 50% above

50.7%59.3%

66.2%72.0%

76.7%Upper Poverty Line Shifted

% of Poor HH

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% of benefit received by beneficiary households

Income Decile 1 Income Decile 10 Combining Lowest 4 deciles

16.4%

6.8%

49.0%

18.4%

6.7%

51.0%

All ProgrammesExcluding the Stipend Programmes

Page 20: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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• 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.

% of food expenditure in consumption expenditure

Income Decile 1 Income Decile 10

All HH

92.2

44.7

78.8

% HH spending more than half of its consumption expenditure in food

Page 21: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% of food expenditure in consumption expenditure by different type of Household

All HH SSNP Beneficiary HH Below UPL HH Below LPL

78.887.2

95.2 96.0

% HHs spending more than half of its consumption expenditure in food consumption

Page 22: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Targeting errors in certain SSNPs using programme specific eligibility criteria (HIES 2010)

Programmes & Criteria Error Found (%)1 Old age allowance:

Minimum age criteria (male 65 years, female 62 years) 35.2 and 35.6Annual Income of beneficiary (less than Taka 3000) 99.5Beneficiary is from a landless household 19.4Beneficiary of other Public/NGO SSNP 12.4More than one beneficiary from the same Household 1.8

2 Allowance for the Widowed Deserted and DestituteFemale is a Widow/ Deserted by Husband /Destitute 25.2Annual income <12000 Tk. 32.4Beneficiary of other Public/NGO SSNP 6.3

3 General Relief ActivitiesHousehold Affected by Natural Disaster 84.9Household below Lower poverty Line (CBN) 76.6Landless/Less than 10 decimal of land 50.2

Note: Certain indicators are not available in the HIES

Page 23: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Programmes & Criteria Error Found (%)4 Vulnerable Group Feeding (VGF) programme

Landless/Having Less than .15 acres of land 36.9Female Household head 84.4Household affected by Natural Calamity 87.7Multiple Beneficiary from same Household 0.8Beneficiary of other Public/NGO SSNP 4.9

5 Gratuitous Relief-Non-cashHousehold Affected by Natural Disaster 88.9Annual income of Beneficiary <3000 Tk. 99.6Household below Lower poverty Line (CBN) 69.4Landless/Have Less than 10 decimal of land 45.6

6 Stipend for Secondary and Higher Secondary Female StudentsTotal monthly Household income<2500 Taka 95.4Landless/Owning less than .50 acres 44.6

Note: Certain indicators are not available in the HIES

Targeting errors in certain SSNPs using programme specific eligibility criteria (HIES 2010)

Page 24: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Inclusion Error and Exclusion Error from HIES 2010 considering Upper Poverty Line

Poor-bene-ficiary HH

9.9%

Non-poor-non-bene-ficiary HH

56.6%

Exclusion Er-ror

19.0%

Inclusion Error14.5%

Page 25: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Preliminary Findings based on Field Data

Page 26: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Field Survey

Coverage Number

Division 7

District 14

Upazila 14

Union 28

Village 28

Paurashava 8

Mahalla 8

Household (surveyed) 3,594

Page 27: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution Poverty status of the SSNP beneficiaries

Name of the Programme % of poor beneficiaries

Inclusion Error (%)

Old Age Allowance 66.8 33.2Allowances for the Widowed/Deserted/Destitute Women 77.7 22.3Gratuitous Relief (GR) Cash 80.0 20.0General Relief Activities 78.8 21.2Allowance for the Financially insolvent disables 43.7 56.3Cash for Work 62.5 37.5Agriculture Rehabilitation 33.3 66.7Vulnerable Group Development (VGD) 82.9 17.1Vulnerable Group Feeding (VGF) 76.4 23.6Gratuitous Relief (GR)/non-cash 88.8 11.2100 days ES/EGP for Hardcore poor 95.7 4.3Stipend for Primary Students 65.1 34.9Stipend for Higher Secondary Level Students 38.2 61.8Total 69.1 30.9

Page 28: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of SSNP beneficiaries by asset deciles

Name of the ProgrammeAsset deciles

Total

D1 D2 D3 D4 D5 D6 D7 D8 D9 D10Old Age Allowance 15.0 10.7 15.0 8.6 9.9 13.7 8.2 8.6 7.3 3.0 100.0Allowances for the Widow, Deserted, Destitute Women 19.9 11.0 14.0 8.8 10.3 12.5 8.1 5.9 5.9 3.7 100.0

Gratuitous Relief (GR) Cash 26.7 13.3 13.3 20.0 6.7 0.0 6.7 6.7 0.0 6.7 100.0General Relief Activities 13.2 10.4 3.8 23.6 13.2 16.0 9.4 4.7 4.7 0.9 100.0Allowance for the financially insolvent disabled 23.8 4.8 9.5 14.3 4.8 4.8 19.0 14.3 4.8 0.0 100.0

Cash for Work 28.6 7.1 14.3 7.1 7.1 14.3 0.0 14.3 7.1 0.0 100.0Agriculture Rehabilitation 0.0 0.0 10.0 10.0 20.0 5.0 35.0 5.0 5.0 10.0 100.0Vulnerable Group Development (VGD) 19.5 12.2 12.2 19.5 12.2 9.8 7.3 0.0 7.3 0.0 100.0

Vulnerable Group Feeding (VGF) 14.4 13.8 19.4 8.0 11.6 11.2 9.0 6.0 6.0 0.8 100.0Gratuitous Relief (GR)/non-cash 17.4 24.3 3.5 23.5 1.7 17.4 2.6 4.3 1.7 3.5 100.0100 days ES/EGP for Hardcore poor 22.2 11.1 33.3 0.0 18.5 7.4 3.7 0.0 3.7 0.0 100.0

Stipend for Primary Students 11.6 10.9 12.4 14.7 10.5 10.5 9.3 9.0 7.1 4.1 100.0Stipend for Higher Secondary Level Students 3.9 2.9 5.9 9.3 8.3 14.2 11.8 17.6 17.2 8.8 100.0

Total 13.3 11.4 13.1 12.4 10.2 11.9 9.0 8.2 7.2 3.3 100.0

Page 29: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of SSNP beneficiaries by asset deciles

Name of the ProgrammeAsset deciles

TotalBottom 4 deciles Middle 3 deciles Top 3 deciles

Old Age Allowance 49.3 31.8 18.9 100.0Allowances for the Widow, Deserted, Destitute Women 53.7 30.9 15.5 100.0

Gratuitous Relief (GR) Cash 73.3 13.4 13.4 100.0General Relief Activities 51 38.6 10.3 100.0Allowance for the financially insolvent disabled 52.4 28.6 19.1 100.0

Cash for Work 57.1 21.4 21.4 100.0Agriculture Rehabilitation 20 60 20 100.0Vulnerable Group Development (VGD) 63.4 29.3 7.3 100.0

Vulnerable Group Feeding (VGF) 55.6 31.8 12.8 100.0Gratuitous Relief (GR)/non-cash 68.7 21.7 9.5 100.0100 days ES/EGP for Hardcore poor 66.6 29.6 3.7 100.0

Stipend for Primary Students 49.6 30.3 20.2 100.0Stipend for Higher Secondary Level Students 22 34.3 43.6 100.0

Total 50.2 31.1 18.7 100.0

Page 30: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Decile 10

Decile 9

Decile 8

Decile 7

Decile 6

Decile 5

Decile 4

Decile 3

Decile 2

Decile 1

18.5

34.4

38.4

47.8

48.4

50.6

57.1

56.6

56

59.1

81.5

65.6

61.6

52.2

51.6

49.4

42.9

43.4

44

40.9

Non-beneficiary HH Beneficiary HH

% distribution of SSN beneficiary HHs and non-beneficiary HHs by asset deciles

Page 31: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Inclusion error and exclusion error (considering only poverty)

HH typePoverty_

Status

Beneficiary HH

Non-beneficiary

HHTotal

Poor 32.6 26.4 59.0

Non-poor 14.2 26.8 41.0

Total 46.8 53.2 100.0

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

Page 32: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Poor-bene-ficiary HH

32.6%

Non-poor-non-bene-ficiary HH

26.8%

Exclusion Er-ror

26.4%

Inclusion Er-ror

14.2%

Inclusion and exclusion error from the field data considering poverty

Page 33: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of reason for not applying for SSNP benefit

Reason PercentNot fit for that programme 49.1Fit for the programme but did not apply 33.2Due to shortness of budget 10.2Did not know how to apply 6.9Other 0.5Total 100.0

Page 34: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of reason for not receiving SSNP benefit (after applying)Reason PercentBudget limitation (according to selectors) 33.2Selection was not proper 31.0Couldn’t provide Bribe 20.2No political exposure 14.9Other .7Total 100.0• 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)

Page 35: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Sixth Five Year Plan(FY2011-FY2015)

Page 36: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

Page 37: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

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Concluding Observations and Recommendations

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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.

Page 40: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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RecommendationsSocial 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

Page 41: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

Page 42: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Thank You

Page 43: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Backup Slides

Page 44: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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ProgrammesBeneficiaries (Nationally)

Beneficiaries in the HIES 2010

Old Age Allowance 2475000 558Allowances for the Widowed, Deserted and Destitute Women

920000 238

Allowances for the Financially Insolvent Disabled 286000 32Maternity allowance programme for the Poor Lactating Mothers

88000 4

Honorarium for Insolvent Freedom Fighters 150000 16Honorarium for Injured Freedom Fighters 8000 14Gratuitous Relief (GR)- Cash 8000000 54General Relief Activities 500000 265Allowances for Distressed Cultural Personalities/Activists 1000 0Food Assistance in CTG-Hill Tracts Area 714000 (Man Month) 14Stipend for Disabled Students 19000 9Grants for the Schools of disabled 12000 0Cash for Work 3810000 (Man Month) 16Housing Support 100000 5Agriculture Rehabilitation 2500000 546Open Market Sales (OMS) 13800000 (Man Month) 6

HIES (2010) and SSNP

Page 45: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Programmes Beneficiaries (Nationally)Beneficiaries in the HIES

2010Vulnerable Group Development (VGD) 8833000 10Vulnerable Group Feeding (VGF) 12222000 (Man Month) 122Test Relief (TR) Food 3905000 (Man Month) 132Gratuitous Relief (GR)- Non-cash 8000000 (Man Month) 494Food For Work (FFW) 3810000 (Man Month) 4100 days Employment Scheme/ Employment Generation Programme for the Hardcore Poor

4200000 20

Stipend for Primary Students 7800000 599School Feeding Programme 315000 6Stipend for Dropout Students 350000 34Stipend and Access Increase for Secondary and Higher Secondary Level Students (including Proposed Secondary Education Stipend Project)

3600000 260

Maternal Health Voucher Allowance 180000 5Rural Employment Opportunity for Public Asset

25000 2

Char Livelihood Programmes 55000 9Rural Employment and Rural Maintenance Programme

46000 5

Total (Beneficiary Households) --- 2989

HIES (2010) and SSNP

Page 46: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% HHs below UPL received SSNP benefit

% HHs below LPL received SSNP benefit

34.2

37.7

Status of poor HHS getting SSNP benefit (HIES 2010)

Page 47: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Targeting/Eligibility CriteriaNo. Beneficiaries

included in the HIES-2010

No. of beneficiary not satisfying the

criteria

% of Error

Inclusion Criteria (Essential)Age >65 years (Male) 276 97 35.2Age >62 years (Female) 292 104 35.6Annual income of Beneficiary <3000 Tk. 558 555 99.5Beneficiary from a Landless HH 558 108 19.4Beneficiary is Physically Infirm - - -Beneficiary is handicapped - - -Exclusion CriteriaBeneficiary is a Government Service Holder - - -Beneficiary is a Pension Recipient - - -Beneficiary is a VGD Card Holder Women 558 0 0.0Beneficiary of other Public/NGO SSNP 558 69 12.4More than one beneficiary from the same Household

558 10 1.8

Beneficiary is a Day laborer/Maidservant/Vagrant - - -** Certain indicators are not available in the HIES

Targeting Efficiency of Old Age Allowance

Performance assessment using programme specific variables

Page 48: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Targeting Efficiency of Widow Allowance

48

Targeting/Eligibility Criteria

No. Beneficiaries

included in the HIES-2010

No. of beneficiary

not satisfying the criteria

% of Error

Inclusion Criteria (Essential)Female is a Widow/Husband’s Deserted/Distitute 238 60 25.2

Annual income <12,000 Tk 238 77 32.4Exclusion CriteriaBeneficiary is a Government Service Holder - - -

Beneficiary is a Pension Recipient - - -Beneficiary is a VGD Card Holder Women 238 0 0.0

Beneficiary of other Public/NGO SSNP 238 15 6.3** Certain indicators are not available in the HIES

Performance assessment using programme specific variables

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Targeting Efficiency of Targeting Efficiency of General Relief Activities

Targeting/Eligibility Criteria

No. Beneficiary household

included in the HIES-2010

No. of beneficiary not satisfying the

criteria

% of Error

Household Affected by Natural Disaster 265 225 84.9

Household below Lower poverty Line (CBN) 265 203 76.6

Landless/Less than 10 decimal of land 265 133 50.2

Performance assessment using programme specific variables

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Targeting Efficiency of Vulnerable Group Feeding (VGF)

Targeting/Eligibility/Exclusion Criteria

No. Beneficiary household

included in the HIES-2010

No. of beneficiary not satisfying the

criteria

% of Error

Inclusion Criteria (Essential)The recipient is a Day laborer 122 - -Landless/Having Less than 0.15 acres of land 122 45 36.9

Female Household head 122 103 84.4Household affected by Natural Calamity 122 107 87.7

Exclusion CriteriaMultiple Beneficiary from same Household 122 1 0.8

Beneficiary of other Public/NGO SSNP 122 6 4.9

** Certain indicators are not available in the HIES

Performance assessment using programme specific variables

Page 51: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Targeting Efficiency of Gratuitous Relief-Non-cash

Targeting/Eligibility Criteria

No. Beneficiary household

included in the HIES-2010

No. of beneficiary not satisfying the

criteria

% of Error

Household Affected by Natural Disaster 494 439 88.9

Annual income of Beneficiary <3000 Tk. 494 492 99.6

Household below Lower poverty Line (CBN) 494 343 69.4

Landless/Have Less than 10 decimal of land 494 225 45.6

Performance assessment using programme specific variables

Page 52: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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

Targeting/Eligibility Criteria

No. Beneficiary household

included in the HIES-2010

No. of beneficiary not satisfying the

criteria

% of Error

Total monthly Household income<2500 Taka 260 248 95.4

Landless/Owning less than .50 acres 260 116 44.6Household headed by person with disabilities or incapable to earn 260

HH Head is a Wage Laborer or Rickshaw Puller 260

** Certain indicators are not available in the HIES

Performance assessment using programme specific variables

Page 53: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Divisions% of beneficiary HHS below

UPL% of beneficiary HHS

below LPLBarisal 43.6 26.4Chittagong 36.8 18.1Dhaka 41.8 24.4Khulna 42.9 21.1Rajshahi 31.9 18.5Rangpur 47.8 32.2Sylhet 33.1 25.8Total 40.5 23.4(All SSNPs) 40.5 24.0

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

Poverty and SSNP beneficiary HHs (except 2 stipend)

Page 54: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Cause of Not being Included in a Programme

Frequency PercentCumulative

PercentBeneficiary Recipients (individual) 3,508 6.3 6.3Not Applicable (HH members age <5 years) 5,630 10.1 16.4Did not know about the programme 2,045 3.7 20.1Not eligible for the programme 29,939 53.9 74.0Eligible for the programme but did not apply 1,853 3.3 77.3Due to budget constraints 1,769 3.2 80.5Selection was not proper 9,975 17.9 98.5No programme in this area 861 1.5 100Total 55,580 100

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

Reported reasons for exclusion

Page 55: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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No. of benefits received by HHs

Frequency PercentCumulative

Percent

1 2,555 85.5 85.5

2 366 12.2 97.7

3 55 1.8 99.6

4 9 0.3 99.9

5 4 0.1 100

Total Beneficiary HHs 2,989 100

Status of multiple beneficiary recipient Households in HIES 2010

Multiple beneficiary recipient

Page 56: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Key Research questions by Broad Scopes

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Scope 1: Targeting of Social Safety Nets in Bangladesh1. What are the main characteristics of the targeting process (targeting

mechanism) of selected public safety net programmes (SSNP) in Bangladesh?

2. How effective is the targeting performance (outreach to the poorest) of the major public SSNPs?

3. What targeting mechanisms are adopted in the large NGO safety net programmes of the country?

Scope 2: Inclusion and Exclusion Errors1. Who are the excluded households from public SSNPs (in relation to

poverty, location, gender and age of head, dependency ratio, and data permitting, food security and nutrition status)?

2. What are public SSNPs that the food-insecure households access?

3. What are the inclusion errors of public safety net programmes?4. What are the factors accounting for errors in different regions, programs

and targeting methodologies?

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

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Scope 3: Addressing Errors 1. What are the challenges faced by major SSNPs to address inclusion

and exclusion errors in Bangladesh and in the South Asia region?2. What are the good practices in certain SSNPs that can be used to

address inclusion and exclusion errors in Bangladesh and in the South Asia region for major safety net programmes?

3. What are complementarities between geographical, household-level and community-based targeting of SSNPs?

4. What potential roles can information technology play to improve targeting outcomes?

5. What roles can grievances and accountability measures play to improve targeting outcomes given existing administrative and political capacities?

6. What are the effective/successful mechanisms adopted by NGO programs that can be adjusted/scaled-up to government-run programmes?

Key Research questions by Broad Scopes

Page 58: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Scope 4: Effective Targeting in Bangladesh

1. What are the options for improving the effectiveness of targeting, in particular decreasing exclusion errors, in Bangladesh?

2. What are the institutional issues of coordination between programmes at the local level and line ministries at the central level?

3. What is the relevance and feasibility of a nationwide targeting/identification system of SSNPs, with a potential road map?

Key Research questions by Broad Scopes

Page 59: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Average duration of SSNP benefit receiving for major regular SSNPs

Programme NameAverage

Duration (month)Average

Duration (year)

Old age allowance 45.6 3.8

Allowance for Widowed, Deserted and Destitute Women

44.6 3.7

Stipend for Secondary and Higher Secondary Level Students

25.4 2.1

Stipend for Primary Students 25 2.1

Honorarium for Freedom Fighters* 53.5 4.5

Allowances for the Financially Insolvent Disabled

44.6 3.7

*Aggregating the ‘Honorarium for Injured Freedom Fighters’ and ‘Honorarium for Insolvent Freedom Fighters’ together

Note: The HIES 2010 survey ended in January 2011. These duration estimates are made as of January 2011.

The HIES did not ask the households whether any member received SSNP benefit in the lifetime. It only focused the current situation. The proposed survey may consider this issue.

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HH size and residence (rural-urban)

HH Size National Rural Urban

All size 24.4 30.3 14.0

1-2 26.6 33.6 12.9

3-4 20.6 27.3 10.2

5-6 28.1 32.9 18.8

7-8 28.6 32.8 19.6

9-10 20.3 24.5 12.7

11+ 22.7 25.0 17.1

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Age of HH head & residence (rural-urban)

Age of Head of HH National Rural Urban

All Age 24.4 30.3 14.0

<=29 17.4 21.4 9.6

30-39 22.1 28.3 11.5

40-49 25.4 32.2 14.7

50-59 24.6 30.4 15.0

60+ 30.0 35.0 18.3

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Gender, Marital Status, religion and residence (rural-urban)

HH Characteristics

HHs receiving SSNP (%) N=2989

National Rural Urban

National 24.4 30.3 14.0Gender of Household Head

Male 24.3 30.3 13.8Female 25.3 30.2 14.9

Marital Status (of household Head)Married 23.5 29.2 13.6

Unmarried 27.3 34.3 14.6Widowed/divorced 33.0 39.8 18.0

ReligionMuslim 24.0 29.6 14.2

Non-Muslim 27.2 34.8 12.2

Page 63: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Beneficiary HHs by land ownership and residence

Size of Land Holding (acres)

HHs receiving SSNP (%) N=2,989

National Rural Urban

All size 24.4 30.3 14.0

No Land 17.9 33.1 9.7

<0.05 19.2 26.5 11.9

0.05-0.49 25.7 31.7 15.0

0.50-1.49 29.7 31.8 18.8

1.50-2.49 32.1 31.6 35.6

2.50-7.49 29.2 29.8 25.0

7.50+ 20.6 20.7 20.0

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Programme Name Landless15 Decimals and

Less (not landless)15> Decimals but <

50 Decimals50 Decimals

and moreN

Stipend for Primary Students

4.1 49.5 18.7 27.6 630

Old age Allowance 6.7 59.2 17.4 16.7 568

Agriculture Rehabilitation 1.4 20.5 20.0 58.0 560

Gratuitous Relief 6.0 64.2 14.3 15.5 503

General Relief Activities 11.9 59.7 17.3 11.2 278

Stipend for Secondary Female Student

3.2 34.5 16.6 45.7 278

Widowed Allowance 8.0 60.1 16.8 15.1 238

VGF 12.2 59.4 10.6 17.9 123

Beneficiary HHs by land ownership categories

Page 65: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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.

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Page 66: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Demographic Characteristics

Chi-Square Scores

SSNP beneficiary status

Poverty Status based on UPL

Poverty Status based on LPL

Urban-Rural 405.9 82.4 151.0

Household Size 87.6 415.6 327.9

Land Ownership 103.4 316.1 225.3

Age of HH Head 83.6 117.9 78.6

Sex of HH Head 0.9 25.1 6.6

Marital Status of HH Head

50.5 6.3 10.9

Religious Status of HH 3. 390 3.7 5.7

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Chi-Square scores for categories of different demographic characteristics

Page 67: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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ProgrammesLiteracy Status N

Literate IlliterateStipend for Primary Students 54.3 45.7 630Old age Allowance 13.6 86.4 568Agriculture Rehabilitation 44.1 55.9 560Gratuitous Relief 28.6 71.4 503General Relief Activities 33.1 66.9 278Stipend for Secondary Female Student 99.6 0.4 278Widowed Allowance 13.9 86.1 238VGF 28.5 71.5 123

SSNP beneficiaries and their literacy status

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Housing and Sanitation Condition of SSNP beneficiary HHs

Material of Wall F % Material of Roof F %

Brick/cement 368 12.3 Concrete (brick/cement/rod)

97 3.2

C.I. Sheet/wood 1210 40.5 C.I. Sheet/wood 2505 83.8Mud brick 622 20.8 Mud/tally/wood 112 3.7Hemp/hay/bamboo 767 25.7 Hemp/hay/bamboo 235 7.9Other 22 0.7 Other 40 1.3Total 2989 100 Total 2989 100

Latrine type Frequency PercentSanitary 342 11.4Pacca latrine (water seal) 377 12.6Pacca latrine (pit) 490 16.4Kacha latrine (perm) 894 29.9Kacha latrine (temp) 719 24.1Other 167 5.6Total 2989 100

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HH electrification status of SSNP beneficiaries

Electricity & Cell Phone F %

SSNP beneficiary HHs with electricity in their house 1164 38.9

Beneficiary HHs have cell phone 1525 51.1

N 2989 100.0

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

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Incidence of poverty (HCR) by CBN method by division (HIES 2010 and 2005)

Poverty Line and Division

2010 2005Total Rural Urban Total Rural Urban

Using the Upper Poverty LineNational 31.5 35.2 21.3 40.0 43.8 28.4Barisal 39.4 39.2 39.9 52.0 54.1 40.4Chittagong 26.2 31.0 11.8 34.0 36.0 27.8Dhaka 30.5 38.8 18.0 32.0 39.0 20.2Khulna 32.1 31.0 35.8 45.7 46.5 43.2Rajshahi (Former) 35.7 36.6 30.7 51.2 52.3 45.2Rajshahi (New) 29.8 30.0 29.0 - - -Rangpur 46.2 47.2 37.0 - - -Sylhet 28.1 30.5 15.0 33.8 36.1 18.6

Page 71: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Per Capita monthly expenditure of the poor by residence and divisions (Taka)

Division

Per Capita expenditure of the PoorUsing Lower Poverty Line Using Upper Poverty Line

Total Rural Urban Total Rural Urban

2010

National 1064.9 1056.0 1133.4 1245.8 1200.0 1457.7

Barisal 1044.7 1031.4 1119.9 1176.0 1140.9 1348.8

Chittagong 1174.5 1169.8 1231.9 1381.8 1361.7 1540.6

Dhaka 1071.3 1060.2 1174.8 1290.9 1192.6 1610.2

Khulna 1018.1 984.1 1124.3 1212.6 1170.0 1337.5

Rajshahi 1041.1 1034.8 1074.3 1205.2 1186.8 1280.7

Rangpur 1027.1 1019.7 1109.3 1150.2 1140.8 1247.8

Sylhet 1049.4 1051.0 1013.2 1117.0 1102.6 1276.9

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Page 72: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

% distribution of beneficiary and non-beneficiary HHs by consumption expenditure deciles and residence (rural-urban)

Expenditure Deciles

SSN beneficiary households (%) Non-beneficiary households (%)

National Rural Urban National Rural Urban

Lower 5% 8.8 9.6 5.9 3.8 5.0 1.9

Decile-1 15.0 16.6 8.8 8.4 10.9 4.8

Decile-2 12.4 12.7 11.1 9.2 10.8 7.0

Decile-3 11.2 12.0 8.3 9.6 11.0 7.6

Decile-4 11.6 11.8 10.7 9.5 10.8 7.6

Decile-5 11.4 11.5 10.7 9.6 10.4 8.3

Decile-6 10.5 10.9 9.3 9.8 10.5 8.9

Decile-7 9.1 9.2 8.9 10.3 10.0 10.7

Decile-8 7.7 6.9 10.7 10.8 10.1 11.7

Decile-9 6.5 5.2 11.4 11.1 8.8 14.6

Decile-10 4.7 3.3 10.1 11.7 6.8 18.8

Top 5% 1.9 1.1 5.0 6.0 3.2 10.0

Total/Deciles 100.0 100.0 100.0 100.0 100.0 100.0

N 2,989 2,374 615 9,251 5,466 3,785

Page 73: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

% distribution of beneficiary and non-beneficiary HHs by consumption expenditure deciles and residence (rural-urban)

Expenditure Deciles

SSN beneficiary HHs (%) Non-beneficiary HHs (%)

National Rural Urban National Rural Urban

Lower 5% 8.8 9.6 5.9 3.8 5.0 1.9

Bottom 4 deciles

50.2 53.1 38.9 36.7 43.5 27

Middle 3 deciles

30.9 31.5 28.9 29.7 30.8 27.9

Top 3 deciles

18.9 15.4 32.2 33.6 25.7 45.1

Top 5% 1.9 1.1 5.0 6.0 3.2 10.0

Total 100.0 100.0 100.0 100.0 100.0 100.0

N 2,989 2,374 615 9,251 5,466 3,785

Page 74: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of beneficiary HHs of major SSNPs by consumption expenditure deciles

Major Safety Net Programmes (HIES 2010)

Household Income Deciles (HIES 2010)

L5%

D1D2

D3

D4

D5

D6

D7

D8

D9

D10

T5%

Old Age Allowance 20.3 28.3 12.2 7.5 10.0 10.6 10.4 7.9 4.7 6.1 1.4 0.9

Allowances for the Widowed, Deserted and Destitute Women

16.8 26.1 17.7 13.0 8.0 9.7 8.8 6.3 5.9 2.9 1.7 0.4

General Relief Activities 10.2 14.7 10.2 12.5 10.2 15.1 10.2 9.8 7.9 5.7 3.8 1.1

Agriculture Rehabilitation 1.8 6.8 7.7 9.7 11.4 12.1 12.3 10.6 11.7 9.2 8.6 3.5

Vulnerable Group Feeding (VGF) 6.6 14.8 18.0 10.7 16.4 10.7 11.5 10.7 6.6 0.8 0.0 0.0

Gratuitous Relief (GR)- Non-cash 9.1 16.8 15.8 14.6 13.0 12.4 9.5 6.7 5.9 4.3 1.2 0.6

Stipend for Primary Students 2.2 7.9 15.2 12.2 14.5 10.9 10.5 10.4 8.7 6.0 3.8 1.7

Secondary and Higher Secondary Stipend 1.2 3.5 5.8 7.3 10.8 8.1 10.0 13.9 11.5 15.0 14.2 5.0

Only programmes with more than 100 beneficiary households in the HIES 2010 considered. 74

Page 75: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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% distribution of beneficiary HHs of major SSNPs by consumption expenditure deciles

Major Safety Net Programmes (HIES 2010)

Household Income Deciles (HIES 2010)

L5%

Bottom 4 deciles

Middle 3 deciles

Top 3 deciles

T5%

Old Age Allowance 20.3 58.0 29.8 12.2 0.9

Allowances for the Widowed, Deserted and Destitute Women

16.8 68.4 21.1 10.5 0.4

General Relief Activities 10.2 47.6 35 17.4 1.1

Agriculture Rehabilitation 1.8 35.6 34.9 29.5 3.5

Vulnerable Group Feeding (VGF) 6.6 59.9 32.7 7.4 0.0

Gratuitous Relief (GR)- Non-cash 9.1 60.1 28.5 11.4 0.6

Stipend for Primary Students 2.2 49.8 34.4 15.8 1.7

Secondary and Higher Secondary Stipend 1.2 27.4 41.9 30.7 5.0

Only programmes with more than 100 beneficiary households in the HIES 2010 considered. 75

Page 76: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

Page 77: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Grosh, Coady and Hoddinott performance index by programme (HIES 2010)

Name of the Programme

Grosh, Coady and Hoddinott performance index

Income deciles

Consumption expenditure deciles

Old Age Allowance 1.5 1.5Allowances for the Widowed, Deserted and Destitute Women

1.5 1.7

General Relief Activities 1.3 1.2Agriculture Rehabilitation 1.0 0.9Vulnerable Group Feeding (VGF) 1.4 1.5Gratuitous Relief (GR)- Non-cash 1.3 1.5Stipend for Primary Students 1.2 1.2Secondary and Higher Secondary Stipend

0.8 0.7

Aggregating All Programmes (HIES 2010)

1.2 1.3

Page 78: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Performance index by programme (Field Survey)

Name of the Programme

Grosh, Coady and Hoddinott

performance index 

Performance indicator for the poor households

Old Age Allowance 1.2 1.2

Widow Allowances 1.3 1.3

Gratuitous Relief (GR) Cash 1.8 1.3

General Relief Activities 1.3 1.3

Allowance for the insolvent disabled 1.3 1.0

Cash for Work 1.4 1.3

Agriculture Rehabilitation 0.5 0.8

Vulnerable Group Development (VGD) 1.6 1.4

Vulnerable Group Feeding (VGF) 1.4 1.3

Gratuitous Relief (GR)/non-cash 1.7 1.5

100 days ES/EGP for Hardcore poor 1.7 1.5

Stipend for Primary Students 1.2 1.2

Stipend for Higher Secondary Students 0.6 0.7

Total 1.3 1.2

Page 79: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Name of the ProgrammeDeciles

IncomeConsumption expenditure

wealth

+Old Age Allowance 1.5 1.5 1.2Allowances for the Widowed 1.5 1.6 1.3General Relief Activities 1.3 1.2 1.3Agriculture Rehabilitation 1.0 0.9 0.5Vulnerable Group Feeding (VGF) 1.3 1.5 1.4Gratuitous Relief (GR)- Non-cash 1.3 1.5 1.8Stipend for Primary Students 1.2 1.2 1.2Secondary and Higher Secondary Stipend 0.8 0.7 0.6

Page 80: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Background and Objectives … contd..

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Recent studies identified 4 potential sources of targeting errors:

1. Mismatch of geographical allocations of resources & poverty rates

2. Use of improper targetting indicators

3. Even if design of SSN targeting mechanism is sound, political economy & implementation issues at local level overrides it

4. 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.

Page 81: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Methodology and Data Sources …contd…

81

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.

Page 82: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

SSNP beneficiary households below Poverty Lines in the CBN Method (by division and rural urban)

Divisions Location Below Upper Poverty Line Below Lower Poverty Line

NationalTotal 40.5 24.0

Rural 40.2 25.1

Urban 41.6 20.0

BarisalTotal 47.3 31.1

Rural 43.9 30.0

Urban 61.3 35.5

ChittagongTotal 36.2 19.4

Rural 36.8 19.5

Urban 33.8 18.8

DhakaTotal 41.8 24.4

Rural 42.3 26.9

Urban 40.1 16.6

KhulnaTotal 41.2 20.3

Rural 39.5 20.6

Urban 48.3 19.3

RajshahiTotal 30.5 17.9

Rural 28.6 17.9

Urban 37.7 18.0

RangpurTotal 47.8 32.0

Rural 50.3 34.2

Urban 38.9 24.4

SylhetTotal 31.4 24.7

Rural 33.5 27.8

Urban 14.3 0.0

Page 83: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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:

The HIES 2010 and SSNP in Bangladesh

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:

Individual/Household level information available in the HIES 2010Age, sex, marital status, religion/ethnicity, education and literacy, disability, illness and injury, home, housing and basic service (water, sanitation and electricity), land ownership, asset description

Earning status, employment status, income, economic activity (including agricultural, livestock, fisheries etc), calamity and disaster, loan and remittance, household food and non-food consumption

Page 84: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

Page 85: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

% distribution of SSNP beneficiary HHs (8 major SSNPs) by CBN poverty status, HIES 2010

Programme NameHIES Sample

Household

Beneficiaries below UPL

Beneficiaries below LPL

Frequency % Frequency %

Old Age Allowance 558 255 45.7 155 27.8

Allowances for the Widowed, Deserted and Destitute Women

238 110 46.2 60 25.2

General Relief Activities 265 108 40.8 62 23.4

Agriculture Rehabilitation 546 148 26.4 78 13.9Vulnerable Group Feeding (VGF)

122 53 43.4 27 22.1

Gratuitous Relief (GR)- Non-cash

494 246 49.8 151 30.6

Stipend for Primary Students

599 306 51.6 201 33.6

Secondary and Higher Secondary Stipend

260 73 28.1 42 16.2

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Page 86: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Distribution of HHs by number of SSNP beneficiaries

No. of benefits received by HHs Frequency Percent

1 1,255 74.72 356 21.23 65 3.94 5 0.3

Total 1,681 100.0

Page 87: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

Methodology and Data Sources

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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.

Page 88: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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SSNP Beneficiary HHs and land ownership statusLand ownership category Frequency PercentLandless 190 6.4<15 decimals but not landless 1,541 51.615-49 decimals 452 15.150 decimals and more 806 27.0Total 2,989 100.0

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

Programme Name50 decimals

and more (%) Programme Name50 decimals and

more (%)

General Relief Activities 11.2 VGF 17.9

Widowed Allowance 15.1 Stipend for Primary Students 27.6

Gratuitous Relief 15.5 Stipend for Secondary Female Student 45.7

Old age Allowance 16.7 Agriculture Rehabilitation 58.0

Page 89: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Respondent TypeLiteracy Status

NLiterate Illiterate

All respondent of HIES 58.8 41.2 47,323SSNP beneficiary Respondent 38.9 61.1 3,475SSNP Non-beneficiary, below UPL* 43.7 56.3 12,786Below UPL, all respondent 42.4 57.6 14,237Below LPL, all respondent 37.6 62.4 7,748*Defined as eligible Non-beneficiary of SSNP**This table is prepared for individuals. If a household is considered poor then all the members within that HH are considered as poor.***A person aged 7 years and above and who is able to write a letter is considered as literate in the HIES

Poverty, SSNP beneficiaries and literacy status

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),

Literacy status of beneficiaries of individual programmes (% literate):

Page 90: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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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.

Page 91: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Are these non-poor households borderline poor?

(Tk.)

Per capita expenditure of SSNP beneficiary HHs

Lowest LPL (Khulna Rural)

Highest LPL (Ctg Urban)

Lowest UPL (Sylhet Rural)

Highest UPL (Dhaka SMA)

1997

1192

1495

1311

2038

Different poverty lines and per capita monthly expenditure of SSNP beneficiary households (HIES 2010)

Page 92: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Poverty and SSNP benefit

Total households surveyed 3,594 (100%)

Poor households 2,182 (60.7%)

SSN beneficiary households 1,681 (46.8%)

Total Individuals surveyed 15,977

Individual SSN beneficiaries 2,182

Eligible Individual SSN non-beneficiaries

3,182

Page 93: Principal Investigator Abul Barkat Co-Investigators Subhash Kumar Sen Gupta, Abdullah Al Hussain, Matiur Rahman & Faisal Mohammad Ahamed Manob Sakti Unnayan.

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Distribution of SSN beneficiaries by programmeName of the Programme Number of beneficiariesOld Age Allowance 233Allowances for the Widowed/Deserted/Destitute Women 136Honorarium for Insolvent Freedom Fighters 3Honorarium for Injured Freedom Fighters 1Gratuitous Relief (GR) Cash 15General Relief Activities 106Allowance for the Financially insolvent disables 21Cash for Work 14Agriculture Rehabilitation 20Vulnerable Group Development (VGD) 41Vulnerable Group Feeding (VGF) 501Gratuitous Relief (GR)/non-cash 115Food For Work (FFW) 1100 days ES/EGP for Hardcore poor 27Stipend for Primary Students 734Stipend for Higher Secondary Level Students 204Maternity Allowance for the poor Lactating Mothers 5Other 5Total 2,182