SOUTH ASIA REGION

A WORLD BANK DOCUMENT

PREM WORKING PAPER SERIES

The findings, interpretations, and conclusions expressed in this paper are entirely those of the author(s) and should not be attributed in any manner to the

Food Assistance Programs in Bangladesh

Rinku Murgai and Salman ZaidiMay 2004Report No. SASPR-2A

World Bank, to its affiliated organizations, or to members of its Board of Executive Directors or the countries they represent.

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FOOD ASSISTANCE PROGRAMS IN BANGLADESH

Rinku Murgai and Salman Zaidi1

1 Poverty Reduction and Economic Management Unit, South Asia Region, The World Bank. Contact information: rmurgai@worldbank.org, szaidi5@worldbank.org. This paper was prepared as a background paper for the Bangladesh Poverty Assessment. We would like to thank Sharmila Haq for excellent research assistance. Kalanidhi Subbarao, Robert Hynderik, Nasir Farid, Carlo del Ninno, Paul Dorosh, Ahmed Akhter, and participants of the Bangladesh Poverty Assessment workshops and the World Bank Rural Policy Thematic Group provided useful comments and suggestions.

About the SASPR Working Paper

The purpose of the SASPR Working Paper Series is to provide a quick outlet for sharing more broadly research/analysis of issues related to development in South Asia. Although the primary source of such research/analysis in SASPR staff, other contributors are most welcome to use this outlet for rapid publication of their research that is relevant to South Asia’s development. The papers are informal in nature and basically represent views/analysis of the concerned author(s). All papers submitted for publication are sent for an outside review to assure quality. I provide only a very light editorial touch. For enquiries about submission of papers for publication in the series or for copies of published papers, please contact Naomi Dass (telephone number 202-458-0335).

Sadiq Ahmed Sector Director South Asia Poverty Reduction and Economic Management World Bank, Washington D.C.

TABLE OF CONTENTS

1. INTRODUCTION ......................................................................................................................... 1

2. PROGRAM OBJECTIVES AND DESCRIPTION........................................................................3

2.1 FOOD-FOR-WORK PROGRAMS AND TEST RELIEF ............................................................................................... 3 2.2 FOOD-FOR-EDUCATION PROGRAM........................................................................................................................ 5 2.3 VULNERABLE GROUP DEVELOPMENT................................................................................................................... 5 2.4 VULNERABLE GROUP FEEDING AND GRATUITOUS RELIEF.............................................................................. 6 2.5 RURAL MAINTENANCE PROGRAM........................................................................................................................... 7

3. SCOPE FOR BETTER REGIONAL TARGETING? ...................................................................8

4. TARGETING BENEFICIARIES ..................................................................................................9

4.1 AVERAGE PARTICIPATION RATES, TARGETING ACCURACY, AND INCIDENCE: ............................................ 9 4.2 MARGINAL INCIDENCE: .......................................................................................................................................... 13

5. ESTIMATES OF LEAKAGE FROM THE SYSTEM.................................................................. 15

6. ASSESSMENT OF THE DEVELOPMENTAL IMPACT.......................................................... 18

7. CONCLUDING OBSERVATIONS:............................................................................................ 21

BIBLIOGRAPHY ................................................................................................................................. 25

List of Tables TABLE 1. ALLOCATIONS TO THE PROGRAMS 1999-2000 ................................................................................................. 3 TABLE 2. AVERAGE PARTICIPATION RATES & ODDS OF PARTICIPATION ................................................................ 10 TABLE 3. VARIOUS MEASURES OF TARGETING ACCURACY.......................................................................................... 11 TABLE 4. AVERAGE PARTICIPATION RATES, ODDS OF PARTICIPATION, AND DISTRIBUTION.............................. 12 TABLE 5. AVERAGE TRANSFERS RECEIVED BY PROGRAM PARTICIPANTS ................................................................ 13 TABLE 6. MARGINAL ODDS OF PARTICIPATION............................................................................................................. 14 TABLE 7. COVERAGE RATES: 2000 HIES COMMUNITY QUESTIONNAIRE FINDINGS............................................. 15 TABLE 8. COVERAGE RATES: 2000 HIES HOUSEHOLD QUESTIONNAIRE FINDINGS ............................................ 16 TABLE 9. PROGRAM OUTLAYS VS. SURVEY ESTIMATES................................................................................................. 17 TABLE 10. VARIATION IN UNIT VALUES AND PER CAPITA CONSUMPTION OF RICE AND WHEAT...................... 19 TABLE 11. ANNUAL OFF-TAKE OF FOOD GRAINS FROM PFDS: NON-MONETIZED CHANNEL .......................... 24 List of Figures FIGURE 1. ALLOCATIONS TO FOOD ASSISTANCE PROGRAMS (IN METRIC TONS) .............................................. 1

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Food Assistance Programs in Bangladesh

Abstract: Bangladesh boasts a wide array of targeted food assistance programs that strive to achieve a number of important developmental objectives. Findings from the 2000 Household Income and Expenditure Survey (HIES) as well as other studies carried out in recent years suggest that these programs are reasonably well-targeted towards the poor. However, any definitive conclusions about the “pro-poor” nature of spending on these programs are clouded by the survey findings which suggest that a large share of total resources devoted to these programs disappear before reaching their intended beneficiaries. If these “unaccounted-for” benefits are in fact appropriated by the non-poor, the incidence of spending on these programs would actually be pro-rich. Of the total volume of food grains channeled through the food assistance programs in 1999-00, 31 percent was allocated to programs that had an explicit human capital development objective (FFE, VGD), while 47 percent was allocated to public works programs producing productive physical assets (FFW). Continued emphasis on the developmental aspect of these programs rather than transfer or relief function alone, plus greater efforts to improve monitoring systems to reduce leakage from the system and to channel a higher share of resources to regions with greater need of assistance are likely to yield high dividends. Exploring options aimed at reducing transfer costs per unit of benefit transferred through the programs as well as promoting greater transparency and flexibility through more cash-based transfers merits serious consideration.

Introduction

1. In a low-income country like Bangladesh, mobilizing sufficient resources to ensure adequate food intake for all is a daunting undertaking. Fortunately, the country has one of the largest systems of targeted food transfer programs in the world, testament to the commitment of successive governments in Bangladesh to the cause of food security and to ensuring that scarcities such as the disastrous famine of 1974 never occur again. Since 1993-94, over 1 million metric tons of food grains have been allocated to these programs each year (Figure 1 and Table A1).

Figure 1. Allocations to Food Assistance Programs (in metric tons)

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0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

FY91 FY92 FY93 FY94 FY95 FY96 FY97 FY98 FY99 FY00 FY01

FFW FFE VGD VGF TR GR Other

2. All these programs are supplied by the non-sale (“non-monetized”) arm of the Government’s Public Food Distribution System (PFDS), one of the largest distribution systems of its kind in the world. There has been a welcome improvement in targeting, with some poorly targeted subsidized PFDS ration channels cut back in recent years and others abolished. Almost 80 percent of the total food grains channeled through the PFDS are now directed towards these programs compared with 30 percent in the early 1980s.2 In fiscal year 1999, in response to the floods that hit Bangladesh, the food provided by these programs was increased to about 1.8 million tons. At a conservative estimate this is a transfer of more than US$300 million, a substantial sum by any standard. Aggregate resource transfers under the targeted food assistance programs—not counting grain storage and distribution costs, the associated administrative expenses of the concerned line agencies, etc.—was more than 120 percent of the government’s recurrent expenditure on Primary Education, or nearly 80 percent of the entire budget of the Ministry of Health and Family Welfare during that year. Hence a closer examination, both of how effective these programs are in reaching their intended beneficiaries as well as of their development impact, is very important from a policy perspective. 3. As Bangladesh has a wide array of targeted food assistance programs, each with its own specific objectives and target populations, Section 2 begins by providing a brief description of the main programs currently in operation in the country, outlines the main objectives of each program and its implementation arrangements, as well as lists the criteria and the process followed for selecting beneficiaries. Given the program objectives and selection criteria, Section 3 examines the issue of whether there is scope for further improvement in allocation of resources across different regions. In Section 4, data from the 2000 Household Income and Expenditure Survey (HIES) are used to assess the targeting effectiveness of three of the food assistance programs: the Vulnerable Group Development, the Vulnerable Group Feeding, and the Food for Education Program. In addition to average participation rates, this section also presents estimates of the marginal incidence of each program – i.e. the impact at the margin of an expansion or contraction in the scale of the program. The question of how pro-poor is the spending on these programs is intimately linked to what share of the budgeted food grains actually reaches beneficiaries. Therefore, in Section 5, we attempt to quantify the extent of leakage of resources from the system. Finally, as redistributing

2 The remaining 20 percent passes through the so-called “monetized” channels of the PFDS: Essential Priorities (EP: subsidized food grain sales to members of the armed and paramilitary forces, hospital and jail inmates), Other Priorities (OP: subsidized sales to workers of government institutions, fire and civil defense departments), and Open Market Sales (OMS: sales in the open market to stabilize domestic prices). For details on the various PFDS monetized channels, see del Ninno and Dorosh (1998).

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resources to the poor is only one of the many objectives of these programs, in Section 6 we summarize some of the key findings of other studies assessing the developmental impact of these programs. Section 7 concludes by summarizing the main findings, and outlining select areas where further analytic work could potentially yield high dividends.

Program Objectives and Description 4. The intention of all food assistance programs in Bangladesh is to help the poor. However, while some aim simply at the relief of immediate distress, others have development objectives, including rural infrastructure development, boosting primary school enrollment rates, and human capital development (Table 1).

5. Although relief provision remains an important objective, most targeted food programs have gradually shifted in emphasis from relief to development.3 Thus overall allocations to programs such as the Vulnerable Group Development and Food-for Education program as a share of aggregate program outlays have been increasing steadily over the nineties. In the sections that follow, we start first with a brief description of each of the main food assistance programs currently operating in Bangladesh.

Table 1. Allocations to the Programs 1999-2000

Program Main objective Program Off-take

in 1999-2000 (metric tons)

Food for Work Employment generation for the poor, mainly in the dry season Development and maintenance of rural infrastructure

754,818

Food for Education

Promote primary school enrollments and attendance, reduce drop-outs and improve quality of education

285,973

Vulnerable Group Development

Assistance to disadvantaged women in rural areas; training in market-based income generating activities, functional education

216,675

Vulnerable Group Feeding

Food grain distribution to needy families in periods of distress

149,138

Test Relief Employment generation for the poor, mainly in the rainy season (similar to FFW except with lighter labor requirements)

124,508

Gratuitous Relief Disaster relief: grain distribution according to perceived need 20,324 Other 57,690 Total: 1999-2000: 1,609,126 Source: Various program documents. Source for program off-takes reported in Table A1.

2.1 Food-for-Work Programs and Test Relief

3 This is in line with the one of the main recommendations of the 1988 joint task force of the Government and aid donors on strengthening institutions for food-assisted development (SIFAD).

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6. Food-for-Work is not so much a single program as an umbrella of different programs and projects carried out by a number of line ministries in collaboration with various donors. Over the years, donor support to the FFW has declined somewhat, but the overall size of the program has continued to rise steadily. Of the overall allocation of around 750,000 metric tons for the FFW in 1999-2000, about 60 percent was provided by the Government. While different FFW programs have different methods of implementation and beneficiary selection, all share the basic objectives of developing rural infrastructure and providing employment to the poor in rural areas. Their work on infrastructure includes activities such as planting trees, digging canals, building embankments, developing ponds, and building and maintaining katcha roads and roads connecting growth centers. 7. The Government runs several FFW programs without donor support, such as the Rural Infrastructure Reform program implemented by the Ministry of Disaster Management and Relief. The main donor supported FFW programs are the Rural Development (RD) program supported by World Food Program (WFP), bilateral donors, and the Government, and the Integrated Food for Development (IFFD, changed to the cash-for-work Integrated Food Security Program in 2000) project funded by food assistance from USAID through PL-480 Title 2 allocations to CARE. The RD program supports forestry, water, roads, and fisheries projects which are implemented by the Forest Department, Water Development Board, Local Government Engineering Department (LGED), and Fisheries Department, respectively. LGED is the government line ministry responsible for implementation of the IFFD. In keeping with the trends towards increased emphasis on building human capital and community assets, WFP has been integrating the RD program with a new Integrated Food Security (IFS) program. Food-for-work activities that aim to build community infrastructure are being combined with food-for-training activities that focus on improving nutrition and enhancing income-generation capabilities. 8. On-site work for FFW projects is mainly carried out between January and April. Some programs, rather than giving intermittent employment to anyone who applies, give longer-term employment. For instance, for routine canal maintenance under the RD program, poor women receive food or cash transfers for an extended period, and are also trained in income generating activities, nutrition and health awareness. 9. The Test Relief program—though in most respects very similar to other FFW projects implemented by the Ministry of Disaster Management and Relief—is carried out during the rainy season between July and November. As heavy earth work is usually not feasible during this period, this program is confined mainly to maintenance of schools, mosques, madrashas, and other such activities which have much lighter labor requirements. 10. While the exact formula used to determine allocation of resources across regions depends on the particular FFW program concerned, in programs funded by the Government, by and large, resources are allocated to the different districts, thanas, and unions according to population only. For instance, in the case of the FFW component which is responsible for construction and repair of unpaved roads and is implemented by the Ministry of Disaster Management and Relief, food is allocated to the unions according to population, with each union thus getting, on average, about 27 tons of food grain from the Ministry’s annual allocation of 120,000 metric tons last year. Beneficiaries are selected through a self-targeting mechanism as individuals can choose whether or not to participate. The program is theoretically available to everyone, but relatively low wages and labor requirements are set in a way as to discourage the non-poor from participating. 11. On each project there is a Project Implementation Committee (PIC) comprising about 7 to 9 community “notables” and headed by the chairman of the union parishad. Officially, the committee is the main implementing authority for the project, for which all members of the committee work voluntarily. It is entrusted with assessing project priority, feasibility, and benefits, as well as with

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maintaining a list of the beneficiaries employed on the project. Allocations for each project are made on a notional basis, assuming that 1000 cu. ft. of earth work requires 50 kilograms of wheat, and that workers will be paid a wage rate of 5-6 kilograms per day worked. Within each thana, the Project Implementation Officer (PIO) acts as the main liaison between the PIC and the Government. 2.2 Food-for-Education Program 12. The Food-for-Education (FFE) program was started by the Government on a pilot basis in July 1993, but expanded rapidly and to become the second-largest food-assistance program in the country. It is basically an “in-kind” stipend program that links food transfers to poor households to primary school enrollment of their children in order to achieve four objectives: increased school enrollment, better school attendance, lower drop-out rates and higher quality of primary education.4Households with a child in primary school receive 15 kilograms of wheat or 12 kilograms of rice a month (those with two or more children get 20 kilograms of wheat or 16 kilograms of rice), provided the children attend at least 85 percent of their classes and the family sends all children of primary school age to school. The overall allocation to the program of 285,000 metric tons in 1999-2000, funded entirely from the Government’s own resources, covered an estimated 2.1 million households. 13. The FFE program is implemented mainly in rural areas by the Government’s Primary and Mass Education Division, with the assistance of the Directorate of Primary Education, Ministry of Education. At the field level, Thana Nirbahi Officers (TNOs) and Thana Education Officers (TEOs) implement the program with the assistance of School Managing Committees (SMCs). At district level, Deputy Commissioners and the District Primary Education Officers supervise and monitor the program. The FFE covers all rural thanas and 1 city corporation in Bangladesh. 14. There are two stages of targeting. First, in each thana, the Thana Education Committee (comprising the TNO, TEO, representatives of local head teachers, local education specialists, and elites) recommends one or more unions deemed to be economically backward and to have low literacy rates for inclusion in the program. Based on the thana recommendations, the Deputy Commissioner, in consultation with the Minister in charge of the district, makes the final decision. In 2000-2001, 1254 unions (out of approximately 4,500 in the country) were covered by the program. Within each selected union, all government, registered non-government, satellite, and low-cost primary schools as well as one independent madrasha are eligible for the program. However, in order to provide incentives for improving the quality of primary education, schools are required to meet prescribed minimum standards on attendance, pass rates, and exam schedules in order to participate. 15. Second, School Management Committees, in consultation with the Compulsory Primary Education Ward Committee, draw up a list of beneficiaries for the program. No more than 40 percent of the roll at any school may be included. The Government defines the criteria to include (i) distressed female-headed families (widows, divorcees, those separated from their husbands); (ii) day-laborers; (iii) low-income tradesmen (such as fishermen, potters, blacksmiths, weavers and cobblers) and (iv) households that are functionally landless (owning less than 0.5 acres). In addition, in order to be eligible for the FFE, the household should not currently be included in the VGD, RMP, or any other such targeted food assistance program. 2.3 Vulnerable Group Development

16. Started in 1975 as Vulnerable Group Feeding, this program was renamed as it evolved from providing relief to increasing beneficiaries’ self-reliance. The program, implemented by the

4 Since July 2002, FFE has been changed to a cash stipend program.

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Government with support from WFP and a number of bilateral donors, comprises three subprojects (i) Union Parishad (UP) VGD (ii) Women’s Training Centers (WTC) and (iii) Group Leaders and Extension Workers, of which the first is by far the largest.5 The projects are exclusively for the benefit of poor disadvantaged women, who receive 30 kilograms of wheat per month and training for 18 months if they have complied with a compulsory cash savings of 25 Tk. per month. In the cycle that started in July 1999, approximately 492,000 women participated, with an allocation of 184,000 metric tons of food grains. 17. The training is different in the different subprojects. In the UPVGD, during 1999-00, about 85 percent of the women were organized in groups and provided with a package of development services (primarily from the Bangladesh Rural Advancement Committee) comprising: awareness building on social and health issues, functional literacy and numeracy, training in income generating skills, participation in savings schemes and access to credit to start up new income-generating ventures. The WTC trains women for one year in marketable skills on courses operated by the Department of Women’s Affairs under the Ministry of Women’s and Children’s Affairs and several NGOs. The Group Leaders and Extension Workers program helps organize VGD women in groups, and helps them access extension services (and credit) in areas where the regular package of development services is not available. 18. VGD is implemented by the Directorate of Relief and Rehabilitation under the coordinating authority of the Department of Women’s Affairs in the Ministry of Women’s and Children’s Affairs (MWCA). There are two steps in the selection of cardholders. The national VGD committee (under the chairperson of the MWCA) distributes cards across the 461 rural thanas. The higher a thana’s food insecurity rating by the Government and WFP, the greater the share of cards it gets. A minimum of 30 women are then selected from each union by union and thana-level local committees according to selection criteria which include functionally landless women, women with extremely low or no family income, women who are day laborers, and women who lack productive assets.6Preference is given to female heads of households (widowed, separated, deserted, divorced or with disabled husbands) and to women who are physically fit to train. Women who receive assistance from other programs or have participated in the VGD in an earlier cycle cannot be selected for the VGD. 2.4 Vulnerable Group Feeding and Gratuitous Relief 19. Vulnerable Group Feeding (VGF), designed to provide one or more months of food rations to a selected number of households in a period of distress, is implemented by the Directorate of Relief under the Ministry of Disaster Management and Relief. Resources are allocated to the program by the Ministry of Finance when thought necessary. VGF started as a small program in the mid-1990s in response to a drought, but it was rapidly expanded, with supplementary food aid from WFP, to provide relief assistance after the 1998 floods.7 Over 460 thousand metric tons of food grains were distributed across 51 flood-affected districts, making VGF the second largest food-assistance program that year. 20. Under the program, food is distributed only among thanas that are affected by disaster. Among the selected thanas, two-thirds of the food is distributed according to population and the remaining one-third is allotted to thanas rated as having very high or high food insecurity on the

5 The Institutional Feeding component was phased out in 1988. 6 The number of women selected varies from union to union, but in general a minimum number of cards is allocated to areas in which development package services are provided to ensure that such operations are economically viable. 7 While the program received substantial assistance from WFP for the flood relief effort in 1998, in other years it has been funded mainly by the Government.

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Government/WFP resource allocation map for food-assisted development.8 Within thanas, the households to receive food are selected by local communities. Each UP chairman sends a list of potential beneficiaries (compiled from recommendations of ward members, with 50 percent of the beneficiaries taken from female ward member lists) to a thana-level committee including the TNO, UP chairmen, and other local government officials, which makes the final selection. Government selection criteria are defined to include: (i) households in which the head earns less than 300 Tk in a normal month; (ii) households with no agricultural land or productive assets; and (iii) households headed by day-laborers. Priority is given to households that have been physically dislocated by the disaster and to female-headed households. 21. Each household on the list is issued a ration card to receive food for a few months. The Ministry decides how much they receive and for how long, depending on the extent of the disaster. In practice, it is not always possible to restrict food distribution to selected households when other needy households are also present at the UP center at the time of distribution. In such cases, the distributors sometimes have to reduce the amount given to each card holder in order to increase the total number of beneficiaries.

22. Gratuitous Relief (GR), designed to provide emergency relief to disaster victims, is also implemented by the Directorate of Relief under the Ministry of Disaster Management and Relief. While GR is a relatively small program, it is the main way in which the Government provides immediate, short-term relief to disaster areas. Union Disaster Committees (UDCs), comprising the Union Parishad Chairman, local elites, and local government officials, collect information on the number of households affected and the extent of the disaster. This information is compiled at the thana-level by the TNO, and relayed to the Ministry by the District Deputy Commissioners. Based on these reports, the Ministry determines the type of assistance (cash, food, blankets, building materials, and so on), geographic allocations, and beneficiary entitlements. The UDC selects the households to receive assistance. 2.5 Rural Maintenance Program 23. The Rural Maintenance Program (RMP), while similar to FFW programs, is smaller than most (50,000 metric tons of wheat equivalent per year) and differs in one important respect: it pays wages in cash, not in kind. It is implemented by local government institutions (Union Parishads, under the Local Government Division of the Ministry of Local Government, Rural Development, and Cooperatives) with the assistance of CARE-Bangladesh. Financial support comes from the proceeds of monetized wheat aid from CIDA and from the Government’s own resources. Originally started in 1983 as a pilot project with the dual objective of maintaining rural earthen roads as well as providing employment and training to destitute women, RMP has now been extended to approximately 4,100 union councils throughout Bangladesh.9 In each union, 20 kilometers of rural roads that have been built with funds from the IFFD-FFW program are maintained by a roads maintenance association (RMA) comprising 10 women from each union council. The association is responsible as a group for maintaining a given stretch of road every fortnight, with the quality of the work monitored by a member of the union parishad. 24. In each union, the union parishad, in collaboration with a Project Implementation Committee (comprising village members) is responsible for overseeing the beneficiary selection process. The

8 In the months following the 1998 flood, the number of cards allocated to different thanas was decided using the classification by the Water Board. Thanas that were severely affected by the flood received 1,000 cards per union, those moderately affected 700 cards, those normally affected 500 cards, and those not affected at all 300 cards (del Ninno and Roy, June 1999). 9 Excluded unions are in the Chittagong Hill Tracts, swamp lowlands (no roads to maintain), as well as a few unions where other similar programs already exist.

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women in each RMA are selected by lot from a list of 50 eligible women in the union; the criteria for determining eligibility include being divorced, separated, or otherwise destitute; in addition, the women must be between 18 and 35 years of age, and should be physically fit enough to do the work. Participating women are enrolled in a four-year program of work and training during which they receive 43 Tk. per day as wages, nearly one-fourth percent of which is automatically retained in an escrow savings account on their behalf. During the last year of the project cycle, women receive more intensive training in basic business management to maximize potential returns to savings following their eventual graduation from the project.10

Scope for Better Regional Targeting? 25. Of the various government programs described above, only the VGD and RD programs – and to a limited extent the FFE – attempt regional targeting. In the case of the FFE, allocations of resources to the various thanas are made in proportion to their population.11 However, within each thana, 2 to 3 unions that are economically backward and have a low literacy rate are selected for the program. In the case of the VGD and RD programs, allocations to each thana are made on the basis of the Resource Allocation Map developed jointly in 1995 by WFP and the Planning Commission. The thanas are classified as having very high, high, moderate or low food insecurity, using a composite index based on the following criteria: (i) incidence of natural disasters, (ii) food-grain deficit/surplus, (iii) agricultural wage rate, (iv) proportion of households not owning land, (v) proportion of unemployed persons, (vi) proportion of widowed, divorced, and separated women, and (vii) proportion of literate women. Data for deriving this composite index are obtained from a variety of sources, including the 1991 Population Census, data from the Disaster Management Bureau, and the Agriculture Statistics wing of the BBS. 26. While there clearly is scope for improving upon the proxy criteria used under this system to identify regions with higher poverty, the VGD and RD are amongst the few programs that at least attempt to target resources explicitly towards regions with greater need. Analyzing targeting performance for the FFE, Galasso and Ravallion (2000) find that most of the overall pro-poor targeting performance was due to pro-poor targeting within villages. Geographic targeting, across unions, contributed less to overall targeting performance than intra-village targeting. Therefore, they conclude that the Government’s desire to assure broad geographic coverage of the program constrains considerably overall targeting effectiveness of the program. 27. Because of constraints of political economy or otherwise, most other programs are nation-wide in coverage, with little or no effort directed to target regions with higher concentration of the poor. However, as the World Bank’s Poverty Assessment (1997) for Bangladesh and a number of other studies (e.g., Ravallion and Wodon, 1997) have shown, poverty in Bangladesh varies quite considerably from one region to another. Thus, a priori, there appears to be considerable scope for improvement as far as more “poverty or need-focused” allocation of resources across regions is concerned. Consider, for example, the Food-for-Education program: if one of the main objectives of this program is indeed to offer incentives to parents to send their children to school, the striking variation in school enrollment rates across different parts of the country suggests that the program could be made much more effective if more resources were directed to the areas with lowest enrollment. Similarly, data from the 2000 HIES shows that there is considerable variation in living

10 Since 1999, the training component has been expanded. RMP women now work on road maintenance and receive training for all 4 years (on aspects of group dynamics, gender awareness, numeracy, basic business management), and for the 5th year (after graduation) receive support, if needed, from CARE. 11 Based on an interview with a program administrator.

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standards across the country, which could more explicitly be taken into account when making allocations for some of the other programs. 28. The Research Department at the World Bank (see Hentschel, et al., 2000, Elbers et al, 2000) has been developing a technique that combines household survey and census data to estimate consumption-based welfare indicators for small geographic areas such as districts and thanas —i.e., a poverty map. A poverty map can highlight statistically reliable differences in local poverty levels at a high resolution that is not possible to gauge with national level statistics. Currently, poverty maps using this method are used in countries including Nicaragua, Panama, and Guatemala for targeting transfers to poor areas. Since Bangladesh has recently completed both a census exercise and a nationally representative household survey, there could be high payoffs to developing a poverty map for the purposes of improving geographic targeting of food-assistance or other such targeted programs.

Targeting Beneficiaries 29. The 2000 HIES data allow us to examine the targeting effectiveness of three of the food assistance programs: Vulnerable Group Development (VGD), Vulnerable Group Feeding (VGF), and Food-for-Education (FFE). We use two related approaches to assess targeting outcomes: First, we estimate average participation rates and the incidence of food transfers for each program. Average participation rates indicate the fraction of the population that benefits from the program, and show how large the program is so that we can infer whether the program is big enough to have an impact on reducing poverty. Incidence measures the division of total benefits across the expenditure distribution, which allows us to examine the extent to which program benefits accrue to the poor versus the non-poor. Second, we estimate the marginal incidence of each program. While average participation rates are a useful first approximation of the distribution of program benefits, they are not necessarily a reliable guide for the incidence of a change in aggregate spending. Marginal incidence analysis allows us to examine whether the expansion or contraction of a program is likely to disproportionately benefit or hurt the poor. 30. Before turning to a discussion of targeting performance, we briefly describe the data used for the analysis. The 2000 HIES is a nationally representative survey that was administered to a random sample of 7440 households from urban and rural areas. The household questionnaire contains extensive information on household expenditures, which we use to construct per capita consumption expenditure (including imputed values of consumption in kind) for each household. Per capita expenditures, normalized for cost of living differences across regions, form the basis of welfare rankings in the analysis that follows. The household questionnaire also identifies beneficiaries of the VGD, VGF, and FFE programs. Each household is asked how much food (either wheat or rice) they received from each of these programs over the last 12 months since the date of the interview. In addition, a detailed community survey was administered for each primary sampling unit (PSU) within rural areas. The PSU corresponds roughly to one or more villages that lie within a single union. The community survey contains information on whether these programs were operative in the PSU at the time of the survey. 4.1 Average Participation Rates, Targeting Accuracy, and Incidence: 31. Table 2 reports quintile-specific average participation rates and average odds of participation, by program, for the rural sample. Quintiles have been defined over the distribution of per capita expenditures (corrected for differences in cost-of-living across regions) within rural areas, with equal

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numbers of individuals in each. The average participation rate is the percentage of the population in the quintile who benefit from the program. The average odds of participation is given by the ratio of the quintile-specific average participation rate to the overall average. 32. Overall participation rates in each of the three programs were very low, ranging between 3 – 5 percent of the rural population. Given the low coverage, while the programs may be extremely important for the beneficiaries themselves, it is unlikely that any one of these could be expected to have a significant impact on overall poverty reduction. Table 2 also reports the joint coverage of the three programs. While each program serves only a small part of the poor population, joint coverage rates are higher. Approximately 10 percent of the population received assistance from at least one of the three programs in the 12 month period. The limited overlap in coverage by the three programs (only 7 percent of the beneficiaries received transfers from more than one program) conforms with program targeting criteria for the VGD and FFE programs that restrict participation to those households that are not already assisted by other food-assistance programs.

Table 2. Average Participation Rates & Odds of Participation

Per Capita Consumption Quintile (1:lowest, 5:highest) Program 1 2 3 4 5 Overall

I. Average Participation Rates: VGD 8.5 7.0 3.9 2.8 2.1 4.9 VGF 4.9 4.0 3.2 1.9 1.3 3.1 FFE 5.3 4.0 1.3 2.0 1.1 2.8 Overall 17.7 13.4 7.5 6.6 3.9 9.8

II. Average Odds of Participation: VGD 1.75 1.44 0.80 0.58 0.43 1.00 VGF 1.59 1.30 1.05 0.62 0.44 1.00 FFE 1.92 1.45 0.49 0.74 0.40 1.00 Overall 1.81 1.37 0.77 0.67 0.40 1.00

Source: 2000 Household Income and Expenditure Survey. Rural sample only. 33. All three programs are targeted towards the lower quintiles, with participation rates declining as expenditure per person increases. Overall, the odds of the poorest quintile participating in at least one of the three programs is 1.81, versus 0.40 for the richest quintile. In other words, the poor are nearly 5 times more likely to participate in the food assistance programs than people in the richest quintile. FFE is slightly better targeted to the poor than the VGD and VGF: the odds of the poorest and richest quintiles participating in FFE are 1.92 and 0.4, respectively. 34. While participation rates for the entire rural population are indicative of the extent to which the safety net program can reduce rural poverty, population-wide coverage rates present a distorted picture of the targeting effectiveness of a targeted program. All three of the programs are targeted

11

towards specific populations to attain different objectives. Below, we assess how successful the VGD and FFE programs are at reaching their intended beneficiaries. 35. The VGD and FFE programs use a two-step targeting mechanism whereby resources are concentrated within rural thanas to selected economically backward unions, and then targeted to households that satisfy the beneficiary targeting criteria (as described in Section 2) within the selected unions. We use the same criteria to define the sample of eligible households within PSUs that have the program. In the case of FFE, which by design is limited to households with children enrolled in primary school, we further restrict the target group sample to households that have at least one child currently enrolled in primary school. 36. Identifying the target population for the VGF program is more difficult. VGF transfers are allocated to areas that are affected by disasters (such as floods), and as such are not necessarily restricted to rural areas. Among those households affected by disaster, the program attempts to reach the poor, as identified by their income, assets, and principal occupation of the household head. Therefore, the target population of the program is the group of poor households that were affected by disasters for which VGF resources were mobilized during the past year. Since the HIES survey does not allow us to identify this specific group of poor disaster-affected households, we are unable to examine how effective the VGF program is in reaching its intended beneficiaries. 37. Table 3 reports various measures of targeting accuracy for the VGD and FFE programs. Under-coverage is defined as the share of the eligible population that is not covered by the program. Another way of looking at under-coverage is to compute exclusion (or type I) errors – the share of the population that is eligible, but does not receive benefits from the program (i.e. as a share of the total population). Complementary to the concepts of under-coverage and exclusion errors are leakage and inclusion errors respectively. Leakage is defined as the share of participants who are ineligible for the program. Inclusion (or type II) error is the share of the population that is ineligible for the program but still participates.

Table 3. Various Measures of Targeting Accuracy

Targeting Indicators VGD FFE

Under-coverage 91.2% 85.0% Exclusion Error 62.3% 33.8% Leakage 9.9% 30.4% Inclusion Error 0.7% 2.6%

Source: 2000 Household Income and Expenditure Survey.

38. There are two points of note. First, even among the eligible population, under-coverage is extremely high, with 85 percent and 91 percent of the target populations eligible for the FFE and VGD not included in the programs. Relatively high rates of exclusion errors show that, with the current targeting criteria, a large share of the population qualifies as being eligible. It would be worth investigating if finer targeting criteria that do not entail excessive screening costs, could be developed. Second, leakage is fairly low for the VGD program. However, 30 percent of the FFE beneficiaries do not meet any of the targeting criteria incorporated in the program design. Minimizing leakage must of course be balanced against the additional administrative and political costs of achieving better targeting. Yet, 30 percent leakage appears to be quite significant, especially in light of the vast share

12

of the eligible population that is currently not benefiting from the program.12 Moreover, it also does not account for leakage that arises from misappropriation of food resources; we return to this second source of leakage in the next section.

Table 4. Average Participation Rates, Odds of Participation, and Distribution of Eligible Population

Per Capita Consumption Quintile (1:lowest, 5:highest) Program 1 2 3 4 5 Overall

I. Distribution of Eligible Population: VGD 29.0 25.9 18.1 15.2 11.9 100 FFE 30.7 20.6 19.8 15.8 13.0 100

II. Average Participation Rates:

VGD 11.9 10.2 7.6 5.5 4.7 8.8 FFE 19.2 22.9 6.7 13.0 7.9 15.0

III. Average Odds of Participation:

VGD 1.35 1.16 0.86 0.63 0.53 1.00 FFE 1.28 1.52 0.45 0.86 0.52 1.00

Source: 2000 Household Income and Expenditure Survey.

39. While poverty reduction is not the principal objective of either the VGD or the FFE program, it is worth checking how well the targeting criteria work in channeling resources towards the poor. While the chosen targeting criteria (such as landlessness, day laborer occupational class etc) are correlated with low incomes, the correlation between the set of indicators and poverty is far from exact. This is confirmed in Table 4 which shows that while over 50 percent of the eligible population for both programs fall in the bottom two quintiles, approximately one-fourth of the population that meets the eligibility criteria actually falls in the richest two quintiles.13 Some of the non-poor can be expected to be program beneficiaries simply because the targeting criteria are an imperfect proxy for living standards. However, as Table 4 shows, even amongst the eligible population, the odds of participation in the bottom quintile are much higher than that for persons in the higher quintiles. Since participation rates are higher for the poor than the rich, the distribution of benefits (i.e. incidence) of these programs is likely to be correspondingly pro-poor as well. 40. To summarize, several factors underlie the pro-poor distribution of benefits. First, the targeting criteria narrow down the eligible population such that more than half the beneficiaries that would satisfy program requirements are from the bottom two-fifths of the population. Second, even amongst eligible beneficiaries, it appears that the local program administrators use additional means beyond the stated targeting criteria to identify the poor from amongst the eligible populations. Thus, even amongst the group of eligible beneficiaries, a person from the lowest quintile is about 2.5 times as likely to be selected for the program as an individual from the richest quintile. Finally, in the case of the FFE as was mentioned earlier, part of the reason the distribution is pro-poor is simply because poor households on average have a higher share of children of primary school-going age.

12 Other studies report similarly high estimates of leakage (e.g., 26 percent in a 1997 survey by BIDS and more recently, 21 percent in Ahmed and del Ninno, 2001). 13 The main underlying reason is that while land provides a good proxy for living standards of rural households, it remains an imperfect indicator (see also, Ravallion and Sen, 1994).

13

41. The assumption of constant subsidy rates that we make to infer a pro-poor distribution of benefits based on average participation rates across the welfare distribution is possibly a strong one. It pre-supposes that all program participants receive the same quantity of food transfers, and derive the same benefit per kilogram of rice or wheat received. It also assumes that other benefits (e.g., training received) and opportunity costs of program participation are similar for rich and poor beneficiaries. If the poor tend to receive transfers that are of higher value to them, or if their opportunity costs of participation are lower than those incurred by the rich, the actual incidence of benefits may be even more progressive than shown here. On the other hand, it could be that poor participants receive lower quantities than the rich on average, in which case the actual incidence of benefits would be less pro-poor than that shown earlier. 42. Using data on the quantity of food received by each household in the past 12 months, we can check if the amount of transfers received vary across the expenditure distribution. Because of data limitations, we are unable to measure all costs and benefits of program participation. A priori, transfers should be distributional neutral, as each beneficiary is entitled to a fixed allocation per month. In practice, evidence from other studies suggests that actual transfers may be different from entitlements. For example, in the case of the FFE, Ahmed and del Ninno (2001) find that 71 percent of FFE beneficiaries report receiving less than their entitlements, as private dealers responsible for distributing food were diverting grains to the black market. In other instances, the same study reports that dealers were withholding food grains from beneficiaries as payment for prior loans made to beneficiaries at high interest rates. 43. Table 5 reports average transfers of wheat and rice received by program beneficiaries. While transfers do indeed vary across expenditure quintiles, there does not appear to be any clear discernable pattern that would suggest that rich receive more than the poor.14 Since participation rates are decidedly pro-poor, accounting for differences in the quantity of transfers received still yields a pro-poor distribution of benefits. However, the table does suggest that average transfers received by beneficiaries in both the VGD and FFE programs are considerably smaller than their entitlements. We return to the implications of these findings for the two programs in Section 5 when estimating the extent of leakage from the system.

Table 5. Average Transfers Received by Program Participants

Wheat (kg/year) Rice (kg/year) Quintile VGD VGF FFE VGD VGF FFE

1 78.0 71.5 69.4 35.1 35.7 20.9 2 59.1 57.7 82.1 30.7 47.1 34.0 3 64.6 55.0 83.5 37.1 31.9 25.6 4 71.0 52.4 79.9 16.9 45.2 26.3 5 59.2 101.5 64.3 23.9 35.3 28.2

Overall 68.1 64.9 75.5 31.2 38.9 26.5

Source: 2000 Household Income and Expenditure Survey. 4.2 Marginal Incidence: 44. Average participation rates are a useful first approximation of the distribution of program benefits. However, they do not necessarily provide a reliable guide to the possible effects of a change

14 For FFE, transfers may differ on account of the number of children within the household that are enrolled in the program; the HIES survey only records the total FFE transfers received by a household, but does not provide information on the number of children for whom households are receiving transfers.

14

in aggregate spending on the program. For instance, it is possible that as the size of a program increases, the likelihood of detecting leakage to richer households may decline, with the result that the rich may now be more likely to participate and thus gain a disproportionately large share of the marginal benefits, even though their share of average benefits is low. Alternatively, if public spending tends to reach the rich before the poor, and there is some level of saturation in the transfers appropriated by the rich, then the poor may benefit more from an increase in spending beyond existing levels (Lanjouw and Ravallion, 1999, Wodon and Ajwad, 2000).

Table 6. Marginal Odds of Participation

Quintile VGD VGF FFE

Poorest 1.83 1.51 1.95 (17.42) (10.54) (19.38)

2nd 1.73 1.86 1.37 (17.30) (13.17) (12.61)

3rd 0.71 1.17 0.31 (7.57) (9.37) (2.64)

4th 0.58 0.54 0.55 (6.19) (4.46) (4.70)

Richest 0.55 0.41 0.30 (6.76) (3.63) (2.29)

Note: The table reports the coefficient estimates from quintile and program-specific linear probability models that relate the probability of household participation in the program to the average participation rate in the region. The numbers in parentheses are t-ratios.

45. Marginal incidence analysis asks how changes in spending on a program are likely to be distributed across different groups. In order to assess marginal incidence, we examine the effect of expanding the overall size of the program on the probability of participation by households in different quintiles of the expenditure distribution. In particular, for each program and expenditure quintile, we estimate a linear probability model that relates probability of participation in the program to the average participation rate in the region (including all quintiles). Regression coefficients therefore estimate the effect of a change in overall program size in the region on the probability of participation for individuals in different quintiles; these marginal odds of participation (MOP) are reported in Table 6.15

46. The MOP estimates suggest that at the margin, an expansion of all three programs would be decidedly pro-poor. Equivalently, scaling back the programs would reduce participation by the poor more than the rich. In addition, the MOP coefficients broadly confirm the conclusion from the average odds of participation (Table 2) that the food assistance programs tend to reach the poor, and that the FFE program performs best at reaching the poorest. The MOP for the poorest quintile is highest for FFE, while the VGD has the highest MOP for the richest quintile. Notably, for the FFE, the marginal odds of participation fall more steeply as one moves from the poorest to the richest quintile than do the average odds. Thus the average odds under-estimate how ‘pro-poor’ an increase in average spending on the FFE would be. However, as with the average odds calculation, it is important to note that the pro-poor distribution of marginal benefits for the FFE derives in part from the fact that the poor tend to have more children of primary school age.

15 The method we use is slightly different from the approach proposed in Lanjouw and Ravallion (1999). Because of the limited coverage of the three programs, rather than estimating marginal odds of participation by relating changes in district-level participation rates to overall participation rates, we relate the probability of participation at the household level to overall participation rates.

15

Estimates of Leakage From the System 47. Most estimates in Bangladesh of the total number of beneficiaries of the various food assistance programs have relied primarily on macro data on total disbursements in conjunction with entitlements per beneficiary under program guidelines to infer the total number of households benefiting from them. The 2000 Household Income and Expenditure Survey (HIES) provides an invaluable opportunity to estimate the number of beneficiaries of the various programs using data from two sources: (i) the community questionnaire that was administered in each of the rural PSUs where household interviews were carried out, and (ii) the household questionnaire that was administered to 7,440 households throughout the country. Data from both these surveys can be used to “blow-up” the number of households reported as participating in the programs, thus arriving at a rough estimate of the total number of program beneficiaries throughout the country. 48. +,(6�&RPPXQLW\�4XHVWLRQQDLUH� The 2000 HIES community survey was administered in a total of 252 rural communities throughout Bangladesh. The survey collected information on infrastructure, agricultural and employment practices, prices, etc. in rural areas in each of the villages where the household survey was administered. Information was also collected on whether the village concerned was covered under the Food-for-Work (FFW), Food-for-Education (FFE), Vulnerable Group Feeding (VGF), and Vulnerable Group Development (VGD) programs during the past 12 months. In addition, in villages where the program had been active during the past year, data was also collected on the total number of households in the village that participated in the program.

Table 7. Coverage Rates: 2000 HIES Community Questionnaire Findings

Program % households living

in a village where program was offered

Average participation

rates(program villages)

Estimated number

of beneficiary households

% of rural households

covered

(1) (2) (3) (4)

FFW 67.7% -- -- VGD 56.8% 0.051 562,344 2.9% VGF 63.3% 0.127 1,560,597 8.0% FFE 28.3% 0.267 1,466,834 7.5%

Source: 2000 Household Income and Expenditure Survey (HIES) Community Questionnaire

Note: Column 3 and 4 derived based on the 2001 Population Census’s estimate of 19.43 million households living in rural areas in Bangladesh. 49. Data from the HIES community survey show coverage rates to be quite high at the village level, ranging from 67.7 percent for the FFW to 28.3 percent for the FFE (Table 7, column 1). Data on number of participating households in each village where the program was active, in conjunction with the total number of households residing in the village, was then used to infer the average probability of being a beneficiary in program villages (column 2). These two estimates – namely the coverage rate and average participation rates within a covered village – were then used to estimate the

16

total number of beneficiary households covered by the program.16 The community survey data thus suggest that about 7.5 percent of all rural households participate in the FFE, an estimate that is not too far off from the official program estimate of approximately 10 percent coverage. Similarly, the 562,000 beneficiary estimate from the HIES community survey for the VGD is very close to the official estimates of 550,000 women covered in each 18-month VGD cycle. 50. +,(6�+RXVHKROG�4XHVWLRQQDLUH� The HIES household survey also collected information on receipts of food grains from the various programs during the past 12 months. While the community questionnaire was administered to a fairly large and representative group of village residents, it is likely that the information on number of beneficiaries was taken from official records maintained at the mauza or thana level. Thus, comparing the community questionnaire estimates with the information collected at the household-level provides a useful means to cross-check their validity and accuracy. On comparing these estimates, the HIES household survey’s findings with regard to the proportion of households receiving food grains from the various programs were found to be considerably lower than that reported by the community survey (Table 8). For instance, the proportion of households reporting having received food grains from the FFE was only about one-third that reported by the community survey (2.5% vs. 7.5%). Similarly, the proportion of households reporting receipts from the VGF was likewise also considerably lower than that indicated by the community questionnaire (3.2% vs. 8.0%).17

51. The HIES estimates of total number of households benefiting from the VGD program warrant further explanation as, at first sight, they appear to be higher even than the official program estimates. Amongst the possible reasons why this might be so is that in some cases (i) card-sharing (i.e. division of benefits amongst more than one household) is sometimes encouraged by UP officials in order to cover a larger number of poor women in their constituency, and (ii) some of the VGD allocations for each union are distributed to destitute women who come to the distribution center (IFADEP Journal, 1999). In addition, another reason the HIES may overstate the number of VGD beneficiaries compared to the program estimates is that the HIES survey, which took place between February 2000 and January 2001, could have picked up participants from two separate VGD cycles (see related discussion below).

Table 8. Coverage Rates: 2000 HIES Household Questionnaire Findings

Program % households in rural areas

reporting receipt of food grains from program in past 12 months

Estimated number of beneficiary households

(1) (2)

VGD 5.2% 1,043,645 VGF 3.2% 685,742 FFE 2.5% 506,947

Source: 2000 Household Income and Expenditure Survey (HIES) Household Questionnaire

52. Given that the HIES household questionnaire collected data not only on whether the household received any benefits from the program during the past 12 months, but also on how much food grain was received, these data can be used to estimate the total amount of food grains received through these programs by all households in the country. Estimates of aggregate household transfers

16 As the HIES questionnaire did not collect information on the number of households participating in the FFW scheme in each covered village, the total number of beneficiaries of this program could not be estimated. 17 Participation rates reported in this section differ from those reported earlier since these are calculated at the household-level, while the estimates discussed in Section 4.1 were calculated at the individual-level.

17

for the VGD, VGF, and FFE obtained by “blowing-up” the HIES data on household grain receipts are reported in Table 9.

Table 9. Program Outlays vs. Survey Estimates

Program 2000 HIES-based survey estimates

(metric tons)

95% Confidence Interval for

estimate

Program Off-take for FY 1999-2000

(metric tons)

Survey estimate as % of aggregate

program allocation (confidence (intervals)

(1) (2) (3) (4)

VGD 99,978 [72,894, 127,061] 216,675 [34%–59%] VGF 70,760 [44,251, 97,267] 149,138 [30%–65%] FFE 49,951 [27,192, 72,710] 285,973 [10%–25%]

Source: 2000 Household Income and Expenditure Survey (HIES) Household Questionnaire

Aggregate Program Off-take: Bangladesh Food Grain Digest, World Food Program, Dhaka, Bangladesh 53. Why are the survey estimates of aggregate transfers from the three programs so much lower than aggregate program off-take statistics? Part of the reason may be because the reference period for the survey (12 months preceding the date of the interview) does not exactly match the aggregate off-takes comparison year (1999-2000). However, this is unlikely to be an important factor in explaining the large discrepancy between the two sets of estimates, as program off-takes have been fairly constant over the period spanned by the survey recall period (February 1999 to January 2001). 54. In the case of the VGD, the main reason for the discrepancy is because the total amount reported by each recipient household in the survey is considerably lower (around 96 kg per annum) than what might be expected (around 180 kg per annum) given the program guidelines.18 By contrast, in the case of the VGF and FFE, the main reason for the discrepancy was because a much lower percentage of households reported benefiting from the program than might be expected given total program outlays. Each VGF household covered in the HIES reported receiving, on average, 103 kg through the program during the past 12 months preceding the survey. This figure does not appear to be too far off from what typical VGF entitlements are likely to be, given that the program is meant to provide only temporary relief during times of need. Similarly, each FFE household reported receiving, on average, 98.5 kg of food grains during the past year, not too far off from the expected 120 – 150 kg of food grain transfers.19

55. The survey-based estimates of leakage should be interpreted with caution, as other reasons could potentially explain why the survey reports such low coverage rates and receipts.20 However, studies of other transfer programs (e.g., Alderman 2001) find a closer correspondence between what households reported and what was authorized using the same methodology; therefore the finding of leakage is not built into the methodology. Any conclusion, overall, as to the “pro-poor” nature of spending on these programs based on the incidence analysis presented earlier must be balanced

18 Why, given that the program entitles each participant to 30 kg per month, or 360 kg per annum, do we expect each participant to report only 180 kg? A technical discussion of this is beyond the scope of this paper. However, roughly speaking, the reason is that each beneficiary household is as likely to be interviewed 10, 11, 12 months respectively into the VGD cycle as another household that has been part of the VGD cycle for 2, 1, or 0 months respectively. Thus, on average, each beneficiary household would be expected to report receiving 6 months equivalent of transfers during the 12 month preceding the interview date. 19 Assuming respectively 12 kg of rice or 15 kg of wheat per household for a 10 month period. 20 For instance, rather than due to misappropriation of resources, this could also be due to errors related to respondent misreporting, recall difficulties, and sampling errors.

18

against these findings that suggest that a large share of the total resources allocated to the programs fail to reach their intended beneficiaries. 56. Problems of leakage are not confined to Bangladesh alone, nor is leakage an inevitable outcome of such food distribution programs. Using a similar approach in the Indian context, Ahluwalia (1993) found that roughly a third of the food grains that were supplied in the Public Distribution System in India did not reach beneficiaries. Alderman (1988) found that approximately 69 percent of subsidized wheat released by the government in Pakistan to ration shops did not reach consumers. By contrast, however, Jayne et. al. (2000) found little evidence of leakage of food grains from the distribution system in Ethiopia. What is particularly worrisome in the Bangladeshi context is that similar calculations for the FFE program using the 1995-96 HES indicate substantially lower shortfall, indicating that problems of leakage have deteriorated with time. 21

Assessment of The Developmental Impact 57. While all the targeted food assistance programs in Bangladesh aim to help the poor, they vary considerably in their specific objectives, and consequently in their target populations, timing of transfers, and assistance packages. The objectives can be broadly classified into two types. First, programs such as the VGF and GR have a purely ‘relief’ objective, designed to provide assistance to poor households that have been physically dislocated or otherwise adversely affected by disasters. Second, programs such as the VGD and FFE help individuals graduate out of poverty by building human capital skills and income generation skills. This section summarize some of the key findings with regard to the development impact of Bangladesh’s food assistance programs drawing upon existing literature and analysis of the 2000 HIES data. 58. 'LVDVWHU�UHOLHI�DQG�VKRUW�WHUP�FRSLQJ�REMHFWLYHV� How effective a program is in providing short-term relief depends on how quickly resources can be mobilized in response to a disaster, and delivered to people who are adversely affected. The recent massive flood in 1998 provides a good context to examine the role played by the two main relief programs – GR and VGF – in assisting flood affected households. Studies by FMRSP-IFPRI suggest that while direct distribution through these programs was quite small, as compared to private imports, the programs played an invaluable role by targeting relief to those in need. Immediate short-term relief after the flood was mainly provided by the GR. The program was rapidly expanded (with some assistance from bilateral donors), and relief efforts began in August through provision of 20,400 metric tons of rice, and another 30,800 metric tons in September, to flood-affected thanas. Overall, more than 74,000 metric tons of wheat and rice were distributed in 1998-99. del Ninno and Dorosh (1999) found that this assistance was well targeted to flood-affected households. Only 11.4 percent of GR recipients were not directly exposed to floods. However, the amount of transfer provided to beneficiaries was small: on average, households received only 10 Tk per month (over a four-month period), which was much smaller than receipts from private transfers or other government and NGO programs during the same period. In addition, the program did not achieve widespread coverage: overall, 69 percent of flood-affected households did not receive GR transfers.

21 Carrying out a similar exercise with the 1995-96 HES data for the FFE (the only program for which data were collected in the household questionnaire), we find more than three times the number of beneficiaries (1.73 million children) and total food grain receipts (150,000 metric tons) as compared to the 2000 survey. Part of the reason why the estimates from the 2000 HIES are lower than those from the 1995-96 HES could be that, unlike the earlier survey where this information was collected at the child-level, the 2000 HIES only solicited this information at the household level. However, it is unlikely that this difference in the way the questions were administered could explain why there is such a large discrepancy between the two sets of estimates.

19

59. In contrast, the VGF program targeted resources to all areas (both flooded and non-flood affected areas) of the country. As a result, while it was not effectively targeted according to flood exposure, it was successful at reaching the poor. Approximately 25 percent of VGF recipients were not directly exposed to the flood but households in the three lowest expenditure quintiles received an estimated 75 percent of the food grains distributed though the program. VGF assistance was an important component of the total assistance (government, NGO, and private transfers) received by the poor: for the poorest quintile, VGF transfers constituted a substantial 35 percent of total transfers received (del Ninno and Dorosh, 1999; del Ninno and Roy, October 1999). 60. Another context in which programs aim to provide short-term relief is in response to seasonal variations in food prices and employment opportunities in rural areas. Traditionally, there have been two lean seasons in Bangladesh: the January—March period, and the September—October period that precedes the aman rice harvest. Precisely to help households cope with the first lean season, the FFW programs provide employment opportunities and wages in kind (wheat) during the first three to four months of the year. In an early study, Osmani and Chowdhury (1983) found that FFW wages did lead to an increase in food grain consumption among beneficiaries. 61. Over the last two decades, the stress of the first season has dissipated somewhat due to the rapid increase in boro rice and wheat cultivation, which have both dampened consumer price pressures and created employment opportunities (Dorosh and Haggblade, 1995). However, the second lean season is still believed to be acute, when food prices peak and employment opportunities are scarce. Table 10 examines temporal and regional variation in unit-values (expenditures divided by quantity) and per capita consumption of rice and wheat to assess the extent to which this pattern is borne out by the 2000 HIES data. 62. The regression coefficients in Columns (1) and (2) show that there is some seasonal variation in prices of rice and wheat, but there is no peak evident during the September to November months. On average, rice prices were highest between March and May, a result that is mainly driven by higher prices in March and April. Wheat prices were highest at the beginning of the year, following which they declined by 8 percent between March and May, and continued to decline through the year. In addition, while there is some seasonal variation, it is not as large as the variation in prices across divisions and sectors.

Table 10. Variation in Unit Values and Per Capita Consumption of Rice and Wheat

Divisions Prices (Tk./kg) Consumption (kg) & seasons Rice Wheat Rice Wheat Rice – Daily Labor

(1) (2) (3) (4) (5) Divisions

Barishal 0.003 -0.136 -0.071 -0.659 -0.083 (0.64)ns (11.69) (2.94) (7.21) (1.65)ns

Chittagong 0.009 -0.043 -0.179 -0.294 -0.196 (2.75) (5.21) (9.92) (4.55) (4.88)

Khulna -0.059 -0.104 0.050 -0.024 0.069 (14.37) (8.60) (2.33) (0.26)ns (1.44)ns

Rajshahi -0.068 -0.109 0.071 0.222 0.047 (20.69) (12.64) (3.96) (3.29) (1.36)ns

Sector Urban 0.075 0.084 -0.224 0.177 ---

(25.96) (13.22) (15.88) (3.55) --- Months

Mar-May 0.073 -0.080 0.033 0.333 -0.053 (20.99) (9.12) (1.77)ns (4.85) (1.40)ns

20

Jun-Aug -0.018 -0.071 0.015 0.298 -0.03 (5.20) (7.68) (0.82)ns (4.12) (0.80)ns

Sep-Nov -0.018 -0.059 0.008 0.230 -0.098 (5.39) (6.35) (0.46)ns (3.17) (2.67)

Notes: The tables reports coefficients from a regression of the logarithms of unit values and quantities on division, urban, and month dummies. The figures in brackets are absolute t-values. ns means not significantly different from zero. Dhaka division, Rural sector, and Dec-Feb months are omitted categories.

63. Could it be that even though prices do not show a peak during the second lean season, lack of earning opportunities limits food consumption during this period? The results in Table 10 suggest that rice consumption was stable throughout the year, with no significant temporal variation (Column 3). Wheat consumption was highest during the first lean season which is not surprising since it coincides with both the wheat harvest and high off-takes from the PFDS channels (mainly through FFW). The same patterns are true when we look at different quintiles separately; there are no peaks or troughs in per capita rice consumption even for the poorest households in Bangladesh.22 However, focusing on ‘vulnerable’ groups, shows that not all households are able to protect consumption from seasonal variation. In particular, daily wage laborers in rural areas are found to consume about 10 percent less rice in the September to November lean season, as compared to other months (Column 5). These households also have strong temporal variation in wheat consumption, unlike other occupational classes. 64. Taken together, the results in Table 10 are heartening to the extent that they suggest that households in Bangladesh are now better able, on average, to shield their consumption of the staple cereal from fluctuations in prices. At the same time, the results re-emphasize that targeted interventions—across regions, in particular months, and towards particularly vulnerable groups—can play an important role in helping the poor smooth out fluctuations in consumption. 65. 'HYHORSPHQW� 2EMHFWLYHV� FFE and VGD are the two main targeted food-assistance programs that have explicit development objectives. Previous evaluations of the FFE program suggest that the numbers of pupils enrolled at participating schools has increased (Ahmed and Billah, 1994; BIDS, 1997), but there is conflicting evidence on whether this is simply because pupils are transferring from non-FFE to FFE schools. Ravallion and Wodon (2000) using data from the 1995-96 HES found a significant and sizable impact of the program on school enrollments. By their estimates, the program increased the probability of going to school by a little over 20 percent for both boys and girls. Preliminary investigation of the 2000 HIES using the same approach as Ravallion and Wodon suggests that gains in enrollment have been sustained. However, among the sample of households that have children currently enrolled in school, participation in FFE has not had any significant impact on number of days enrolled children attended school. 66. Another recent study by Ahmed and del Ninno (2001) also examines the impact of FFE on a range of outcomes. It finds that enrollment and attendance rates are higher in FFE schools, and drop-out rates tend to be lower. However, FFE schools have higher student-to-teacher ratios and more crowded classrooms, as a result of which the quality of education is poorer. This points to the need to include complementary financial and technical assistance in order to ensure that student achievement also increases concurrently with higher enrollments. The study also finds that the recent switch to a system of distribution of food through private dealers has been far from satisfactory: beneficiaries now incur higher transaction costs in collecting food transfers and system leakage has worsened.

22 We plan to carry out this analysis with earlier HIES data sets to investigate the extent to which these findings are true for earlier years.

21

67. Evidence on the development impact of the VGD program is more limited. The few studies that have been done in general report that the program is targeted to the poor and is perceived to be fair at the local level (e.g. del Ninno, 1998; Sen, 2001). Comparing the socio-economic status of beneficiaries one year after the joining the program and two years after leaving the program—i.e. across a three-year interval—an evaluation conducted by WFP (1997) found that beneficiaries of the VGD program owned more assets (e.g., beds, tin-roofs, clothing), had more savings, and increased access to credit after the program. Importantly, the beneficiaries perceived improvements in their decision-making ability within the family, in the health of their family, and in incomes. However, it is interesting to note that study provides a mixed picture about whether these impacts are a result of the food transfer and savings components, or as a result of the training imparted. Comparing the performance of UPVGD and IGVGD beneficiaries (the former do not receive training as part of the VGD package) does not show any clearly discernable differences across the two groups of participants, though of-course this could also be due to the relatively small sample of the two types of beneficiaries.

Concluding Observations: 68. Continuing operation of such a large system of food transfers represents a big challenge for the Government of Bangladesh, particularly since the volume of international food aid received by the country has been declining in recent years. Projected total food aid to Bangladesh in 2000-01 (approximately 625,000 metric tons) has been amongst the lowest in 20 years. When resources are limited, it is all the more important to ensure that they are used to maximum effect—that they reach the people who need them most, and in a form that does the most good. 69. The food assistance programs have, by and large, done a good job of reaching the poor. More significantly, a number of recent studies suggest that some of these programs have also had a considerable developmental impact on the lives of their participants. This is of vital importance as, large as this might be, the aggregate resource transfer under these programs represents only a small share of total per capita consumption of beneficiaries, even for those in the bottom quintile of the income distribution. The gradual shift in emphasis from relief provision to more explicit development objectives during the nineties represents one of the most important advances in the evolution of these programs, and needs to be sustained to ensure that the program resources have the greatest impact on the long-term welfare of their intended beneficiaries. 70. However, any definitive conclusions about the “pro-poor” nature of these programs must take into account the fact that even though visible receipts of transfers are significantly pro-poor, a non-negligible share of resources allocated to these programs cannot be accounted for when using survey data to estimate total resource transfer to beneficiaries. Strengthening monitoring systems to reduce leakage from the system is likely to yield high dividends, as it would enable the Government to release additional resources to increase coverage. In addition, better monitoring systems could allow the government to compare performance across programs as well as across different regions. Program effectiveness could then be improved considerably by taking this information into account more explicitly when making its allocation decisions, for instance through rewarding good performance or penalizing misappropriation. 71. That the needs of the poor extend well beyond food transfers alone is now increasingly being recognized in Bangladesh, both in the context of design of effective relief operations as well as in the case of more long-term development oriented programs. For instance, the European Commission is planning to look closely at the RMP program as a model for making cash transfers as it shifts away

22

from food towards cash aid in the next 2000-02 food security cycle. There are a number of reasons why engaging on the cash vs. ink-kind transfers debate merits serious consideration: In a study of several targeted safety net programs, Ahmed et al. (1994) found that the RMP, the only cash-based transfer program, was the most cost-effective, requiring 1.2 Tk to transfer 1 Tk of benefits to a recipient household.23 This is in part because being a cash-for-work program, it does not entail costs of handling food grains. Leakage is also believed to be very low because of the unique wage payment system. Salaries for each RMA are paid by a bank transfer every two weeks directly into a maintenance crew bank account that is operated by the elected representative of the workers. Potential for leakage is minimized since certification by officials is not required to withdraw payments. 72. Second, in practice a number of food-based transfer programs operate in cash anyway, and have been subject to malpractice. In the case of the Food for Work program, some PICs hire labor contractors who in turn often sell the wheat or rice received so they can pay cash wages, and workers themselves sometimes end up selling part of the grain they receive to buy other goods and services (del Ninno and Dorosh, 2000). In some places, informal deductions are made from wages cover administrative costs and payments to members of the PIC for their time and effort. As a recent study of the FFE has reported (Akhter and del Ninno, 2001), the dealer-based system of food grain distribution is far from satisfactory: households participating in the program experience losses in their food grain entitlement due to dealer malpractice, as well as significant transaction costs and inconvenience in collecting their rations. Switching to a cash-based incentive system would eliminate the reliance on dealers as intermediaries. Similarly, in the case of the FFW, particularly if there are transaction costs to secondary sales of food grains by contractors and beneficiaries, there appears to be a strong case that the program should pay workers at least partly in cash rather than food. 73. Third, if the primary objective of the FFE program is to provide an incentive to children from poor households to attend school, there appears to be little reason why an equivalent cash transfer would not provide the same inducement.24 Similar arguments also hold for other programs. Cash-based transfers could also be used as incentives for destitute women in the case of the VGD, or to provide relief to VGF or GR beneficiaries. Indeed, one of the main findings of studies carried out during the 1998 flood to assess the impact of government and NGO interventions was that the needs of beneficiary households extended far beyond the need for emergency food assistance alone (e.g. del Ninno and Roy, 1999). 74. The debate on cash vs. food transfers is nicely encapsulated by Dorosh & Haggblade (1997):

“The case for in-kind distribution boils down to three notions: commodities may not be physically available, as in some droughts, even for households with purchasing power; in-kind rations can most effectively improve food consumption and nutritional welfare of the poor beneficiaries; and through the resulting demand creation, this increased consumption will tend to off-set potential price depressing effects of food aid supplies. Monetization, coupled with cash transfers to beneficiaries, offers a number of compensating benefits: improved welfare for recipients, who themselves identify their most pressing needs; reduced commodity handling costs, which increase funds available for development or expanded poverty-alleviation objectives; and reduced risk of agricultural disincentives due to control over the location and timing of commodity injections.”

Further empirical work could help considerably in shedding more light on this ongoing debate.

23 In comparison, the VGD and FFW had cost-effectiveness ratios of 1.4-1.5 and 1.8-2.4 respectively. 24 Indeed, this is the rationale behind the GOB Female Secondary School Stipend program, which provides a scholarship in cash to all girls in rural areas that attend secondary school.

23

75. First, examining more closely the extent to which food transfers to households actually improve nutrition would help shed more light on the merits of the argument cited frequently in favor of continuing food transfers. Data from the Child Nutrition Survey (CNS), which was carried out in conjunction with the 2000 HIES, could be used to analyze if, and to what extent, children in beneficiary households have better nutritional outcomes compared to those in similar non-participant households. 76. Second, there is a need to update estimates of transfer efficiency—i.e. the cost of transferring one taka of benefits to a recipient household—across different programs. Earlier estimates of cost-effectiveness of the various programs computed by the Working Group on Targeted Food Interventions are widely cited in the literature on safety nets in Bangladesh, indicating the considerable importance and interest in the subject.25 However, these estimates date back to the mid-nineties. Besides allowing a comparison of food versus cash assisted programs, cost-effectiveness calculations will also help in assessing the fiscal viability of scaling-up any of the programs currently in operation. 77. Third, investigating further the extent to which there may be transactions costs to secondary sales of food grains by contractors and program participants would help quantify part of the efficiency gains from switching to more cash-based transfers. In this context, soliciting views from local program administrators as well as the beneficiaries themselves (both men as well as women within the households) on the relative merits of cash vs. in-kind transfers would also help bring in a critical perspective that is currently missing in the ongoing debate.

25 Working Group on Targeted Food Interventions. 1994. Options for Targeting Food Interventions in Bangladesh. IFPRI, APD, BRAC, CARE, FPMU, INFS, and USAID.

24

Table 11. Annual Off-take of Food Grains from PFDS: Non-Monetized Channel

OVERALL FY91 FY92 FY93 FY94 FY95 FY96 FY97 FY98 FY99 FY00 FY01 FFW 462,895 540,585 368,619 425,307 500,223 469,219 458,316 469,070 697,599 754,818 611,000FFE 79,553 174,486 241,170 277,385 357,738 286,662 285,973 350,000VGD 224,616 230,733 131,862 166,924 183,901 173,210 179,775 198,150 205,826 216,675 184,000VGF 85,495 30,585 464,286 149,138 153,000TR 65,668 97,936 32,972 71,489 96,734 89,338 134,067 101,449 90,310 124,508 90,000GR 44,397 55,985 17,844 29,594 30,146 74,619 17,850 17,659 74,234 20,324 28,000

Other 65,951 72,433 79,828 99,574 60,423 49,190 54,955 57,690 61,954Total 883 925 617 845 1,065 1,147 1,128 1,224 1,874 1,609 1,478

(Total in ‘000 metric tons; all other figures in metric tons)

RICE: FY91 FY92 FY93 FY94 FY95 FY96 FY97 FY98 FY99 FY00 FY01 FFW 42,722 28,581 205,084 972 7,336 739 126,576 3,312 7,637 334,516 193,000FFE 216 6,024 3,897 209,625 71,039 59,636 112,058 150,000VGD 85,495 26,477 55,585 137 1,679 713 87,584 75,975 11,495 62,032 64,000VGF 85,495 24,167 168,318 126,475 132,000TR 33,718 3,751 30,339 546 5,085 1,357 121,423 14,683 37,017 62,374 40,000GR 31,689 31,974 10,912 12,552 3,807 33,955 16,598 8,532 65,844 7,562 24,000

Other 62,598 57,117 42,279 28,887 55,471 43,618 36,067 38,851 35,000Total 279 91 365 72 66 70 617 241 386 744 638

(Total in ‘000 metric tons; all other figures in metric tons)

WHEAT: FY91 FY92 FY93 FY94 FY95 FY96 FY97 FY98 FY99 FY00 FY01 FFW 420,173 512,004 163,535 424,335 492,887 468,480 331,740 465,758 689,962 420,302 418,000FFE 79,337 168,462 237,273 67,760 286,699 227,026 173,915 200,000VGD 139,121 204,256 76,277 166,787 182,222 172,497 92,191 122,175 194,331 154,643 120,000VGF 6,418 295,968 22,663 21,000TR 31,950 94,185 2,633 70,943 91,649 87,981 12,644 86,766 53,293 62,134 50,000GR 12,708 24,011 6,932 17,042 26,339 40,664 1,252 9,127 8,390 12,762 4,000

Other 3,353 15,316 37,549 70,687 4,952 5,572 18,888 18,839 26,954Total 604 834 253 774 999 1,078 511 983 1,488 865 840 (Total in ‘000 metric tons; all other figures in metric tons)

Source: MIS, DG Food and FPMU, Ministry of Food. FY01: Sept. Food Grain Digest, Table 1f.

25

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