Report No. 64620-TZ Tanzania Poverty, Growth, and Public Transfers Options for a National Productive Safety Net Program September 21, 2011 Human Development Department Social Protection Unit Africa Region Document of the World Bank GOVERNMENT FISCAL YEAR July 1 to June 31 CURRENCY EQUIVALENTS Currency Unit : Tanzanian Shilling (as of December, 2010) 1US$ : Tsh 1,500 WEIGHTS AND MEASURES Metric System ABBREVIATIONS AND ACRONYMS CCTs Conditional Cash Transfers CFSVA Comprehensive Food Security and Vulnerability Assessment CHF Community Health Fund DfID Department for International Development DoSW Department of Social Welfare FFA Food for Assets FFE Food for Education GDP Gross Domestic Product HBS Household Budget Survey HH Household MOEVT Ministry of Education and Vocational Training MVC Most Vulnerable Children NAIVS National Agricultural Input Voucher Scheme NCPA National Costed Plan of Action (for MVCs) NFRA National Food Reserve Agency NHIF National Health Insurance Fund NSSF National Social Security Fund PLWH People Living with HIV/AIDS PMT Proxy Means Testing PWP Public Works Program SCF Save the Children Fund SN Safety nets SSNs Social safety nets TASAF Tanzania Social Action Fund Tsh Tanzanian Shillings VG Vulnerable Group Program WFP World Food Program Vice President : Obiageli K. Ezekwesili Acting Country Director : Mercy Miyang Tembon Sector Director : Ritva S. Reinikka Sector Manager : Lynne D.Sherburne-Benz Task Team Leader : Anush Bezhanyan Principal Author : James Smith ACKNOWLEDGEMENTS This report was prepared by James Smith (Lead Consultant and Principal Author). Anush Bezhanyan was the Task Team Leader for the study. The team has benefited from peer-review and advice of members of Social Safety Net Global Expert Team (GET): Margaret Grosh (Advisor), Kalanidhi Subbarao (Consultant/Expert), and John Elder (Lead Social Protection Specialist). Ana Lukau (Program Assistant, AFTSP) has helped with formatting the report. Kokuteteta Mutumbei helped collect background information, Derick Moshi helped process the HBS data, and Rehema Mashayo (Team Assistant) provided essential organizational support in Dar es Salaam office. Valuable guidance and suggestions were provided by: Lynne D.Sherburne-Benz (Sector Manager, AFTSP), AFTSP John McIntire (Country Director for Tanzania); Louise Fox (Lead Economist), Waly Wane (Sr. Economist), Warren Benfield (Consultant), Ida Manjolo (Sr. Social Protection Specialist), Harold Alderman (Lead Economist), Shreena Patel (Consultant), Deiter Schelling (Consultant/Expert), Arun Joshi (Sr. Education Specialist), Madhur Gautam (Lead Economist), Dominic Haazen (Lead Health Specialist), Carlo del Ninno (Sr. Social Protection Specialist), Manuel Salazar (Sr. Social Protection Specialist), Berk Ozler (Sr. Economist), Azedine Ouerghi (Lead Social Protection Specialist) and Janneke Jorgensen (Nutrition Specialist). To prepare this report, the team worked closely with the government counterparts and Development Partners (particularly DFID, WFP, UNICEF, USAID and others). The study benefited immensely from discussions with Servacius Likwelile, Anna Mwasha, Amadeus Kamagenge, Joseph Shiyo, Jane Calder, Alejandro Grinspun, Gertrude Mapunda Kihunrwa, Jeanne Ndyetabura, Elizabeth Lema, Hans Hoogeven, Christina Popivanova, David Kali, John Kalage, Erasto Machume, Elisifa Kinasha, Dorcas Robinson, Ansgar Mushi, Mehjabeen Alarakhia, Smart Daniel, Flavian Bifandimu, Matthew Greenslade, Karen Johnson, and Emily Poskett. Particular thanks are due to Sheila Grudem, Phenny Kamanga, Juvenal Kisanga, Selemani Masala, Vera Mayer, Mussa Mgata, and Sesil Charles Latemba who gave unstintingly of their time to provide data and advice. Thanks are also due to Chiara Brunelli at WFP in Rome for her help with the CFSVA data. Preliminary results of the study were presented in Dar es Salaam in two workshops in Dar es Salaam in November 2010 and June 2011 and discussed with the government officials as well as to development partners and NGOs, and valuable comments were received from participants. There was consensus on the recommendations and strategic messages of the report. During the discussions in June 2011 a preliminary action plan for the development of a national social safety system in Tanzania was developed in close collaboration with the social protection thematic working group and is included in the report. TABLE OF CONTENT EXECUTIVE SUMMARY ............................................................................................................. i CHAPTER I: INTRODUCTION .................................................................................................... 1 CHAPTER II: POVERTY ANALYSIS FOR SAFETY NET TRANSFERS ................................ 4 2.1 Poverty and Ultra-Poverty in Tanzania ............................................................................ 4 2.2 Characteristics of the Poor and the Very Poor ................................................................. 6 2.3 Movements In and Out of Poverty; and the Impact of Shocks ........................................ 8 2.4 What Is Poverty? How Much Do the Poor Earn, and Where Does Their Money Go? .. 10 2.5 The Geographical Distribution of Poverty ..................................................................... 13 2.6 Food Insecurity and Vulnerability.................................................................................. 15 2.7 Nutrition ......................................................................................................................... 20 2.8 Poverty among the Most Vulnerable - Specific Groups of the Poor .............................. 21 2.9 Informal Safety Nets and Transfers ............................................................................... 25 CHAPTER III: EXISTING TRANSFER AND SAFETY NET PROGRAMS ............................ 27 3.1 Most Vulnerable Children (MVC) Program .................................................................. 27 3.2 Food Subsidies – The National Food Reserve Agency (NFRA) ................................... 30 3.3 School Feeding Program ................................................................................................ 32 3.4 Public Works Program (TASAF) ................................................................................... 35 3.5 Food-for-Work: The Food for Assets Creation Program (WFP) ................................... 38 3.6 National Agricultural Input Voucher Scheme (NAIVS) ................................................ 40 3.7 Vulnerable Group Program (TASAF) ............................................................................ 43 3.8 Formal Transfer Programs ............................................................................................. 45 3.9 Small and/or Innovative Programs ................................................................................. 47 3.10 Overview of Impact of Current Programs ...................................................................... 50 CHAPTER IV: FISCAL SPACE AND AFFORDABILTY: POTENTIAL OBJECTIVES AND SCALE OF A NATIONAL SAFETY NET STRATEGY ........................................................... 54 4.1 The Role of Safety Net Transfers in Tanzania’s Development Strategy ....................... 54 4.2 Estimating the Extent of the Need.................................................................................. 56 4.3 Fiscal Space and Affordability ...................................................................................... 59 CHAPTER V: INSTITUTIONAL AND POLITICAL-ECONOMY CONSIDERATIONS ....... 64 5.1 Administrative and Institutional Issues .......................................................................... 64 5.2 Political Economy and Targeting Concerns ................................................................... 65 CHAPTER VI: CONCLUSIONS AND RECOMMENDATIONS: OPTIONS FOR A NATIONAL SAFETY NET PROGRAM. ................................................................................... 71 REFERENCES .............................................................................................................................. 81 ANNEXES .................................................................................................................................... 89 ANNEX I: POVERTY ANALYSIS ............................................................................................. 90 ANNEX II: PROGRAMS ............................................................................................................. 95 ANNEX III: CROSS-COUNTRY EXPENDITURE ON SAFETY NETS.................................. 99 ANNEX IV: CONDITIONAL CASH TRANSFERS ................................................................ 100 ANNEX V: ESTIMATED COSTS AND COVERAGES FOR THREE NATIONAL SAFETY NET OPTIONS ........................................................................................................................... 102 List of Boxes Box 1: Safety Nets: Accelerating and Deepening Pro-Poor Growth .............................................. 2 Box 2: A Note on Poverty and Safety Nets in Zanzibar ............................................................... 26 Box 3: International Experience with School Feeding Programs ................................................. 34 Box 4: Some Experiences Worldwide with Public Works Programs ........................................... 38 Box 5: Global Experience with Conditional Cash Transfers ........................................................ 49 Box 6: Data, Monitoring, and Evaluation Concerns ..................................................................... 52 Box 7: Building Graduation into Safety Net Programs ................................................................ 59 Box 8: Using Existing Public Expenditure to Make Safety Net Transfers: Employment of the Poor on Road Maintenance ........................................................................................................... 62 Box 9: Common Targeting Systems ............................................................................................. 68 Box 10: The Ethiopia Productive Safety Net Program ................................................................. 73 Box 11: Some Options for Conditional Transfers and Human Capital Development in Tanzania. ....................................................................................................................................................... 77 Box 12: A Note on Data Sources .................................................................................................. 88 List of Tables Table 1: Approximate Numbers in Broad Poverty Groups 2007 ................................................... 6 Table 2: Some Basic Characteristics of the Poor In Tanzania 2007 ............................................... 6 Table 3: Housing Quality and Asset Ownership by Income Status 2007 ....................................... 7 Table 4: Landholding by Income Class in Rural Tanzania............................................................. 8 Table 5: Movements In and Out of Poverty Kilimanjaro and Ruvuma Panel Surveys 2003-2009 9 Table 6: Proportion of Households Reporting Shocks in Past Year – By Income Transition Group ......................................................................................................................................................... 9 Table 7: Impact of Drought and Recovery By Household Food Poverty Status .......................... 10 Table 8: The Definition of Poor: Levels of Poverty in Tanzania ................................................. 10 Table 9: Average Household Income By Income Class and Source ............................................ 12 Table 10: Consumption Patterns among the Poor, the Non-Poor, and the Poorest ...................... 12 Table 11: Use of Education and Health Services by Wealth Quintile 2007 ................................. 13 Table 12: The Regional Distribution of Poverty in Tanzania ....................................................... 14 Table 13: Net Buyers and Sellers of Maize .................................................................................. 18 Table 14: Estimated Increase in Prices of Some Basic Foodstuffs 2001-07 and 2007-09 ........... 19 Table 15: Child Malnutrition by Income Group ........................................................................... 21 Table 16: Estimated Numbers of Most Vulnerable Children 2010 .............................................. 22 Table 17: Estimated Consumption Gap Between Children Living in Households below 30% of the poverty line, and those living at about the Poverty Line ........................................................ 22 Table 18: Poverty Among the Elderly – Headcount Ratio by Age Group ................................... 23 Table 19: Poverty Rates in Households with Only Children and the Elderly .............................. 24 Table 20: Summary Data on Disabled Population 2008 (,000s) .................................................. 25 Table 21: Informal Transfers by Income Group (HBS, 2007)...................................................... 25 Table 22: Summary of Main Existing Transfer Programs in Tanzania ........................................ 27 Table 23: Costs, Financing, and Coverage of the MVC Program ................................................ 28 Table 24: Operations of The NFRA/SGR (Maize Distributed and Beneficiaries) ....................... 31 Table 25: Performance of Food-for-Education and Non-FFE Schools and Students ................... 33 Table 26: Costs & Cost-Effectiveness of the TASAF Public Works Program............................. 36 Table 27: Food for Asset Creation – Costs and Coverage ............................................................ 39 Table 28: Approximate Costs, and Benefits to Households of Inputs Voucher Scheme ............. 41 Table 29: Approximate Costs and Coverage of National Agricultural Input Voucher Scheme ... 42 Table 30: Summary Characteristics of the Formal Social Security Programs.............................. 45 Table 31: Summary of Coverage and Targeting of Existing Transfer Programs ......................... 51 Table 32: Some Evidence on Coverage and Inclusion and Exclusion Errors: % of Rural Households receiving Various Forms of Food and Non-food assistance (CFSVA 2010) ........... 52 Table 33: How Much Is Needed: Illustrative Costs of Some National Safety Net Objectives .... 60 Table 34: Broad Options for a Safety Net Strategy for Tanzania ................................................. 76 Table 35: Approximate Current Annual Financing of Transfer Programs in Tanzania ............... 79 List of Figures Figure 1: Distribution of income in Tanzania ................................................................................. 4 Figure 2: Differences in Average per capita Consumption among the Poor .................................. 5 Figure 3: Household Size and Poverty Incidence ........................................................................... 7 Figure 4: The Impact of Economic Growth on Consumption by Poverty Class .......................... 11 Figure 5: Caloric Consumption by Wealth Quintile ..................................................................... 15 Figure 6: % of Households with Food Reserves Remaining from Previous Harvest – By Month17 Figure 7: Seasonal Movements in Maize Prices 2001-2007......................................................... 18 Figure 8: Seasonality in Labour Use & Livelihood Activities ..................................................... 19 EXECUTIVE SUMMARY 1. Objectives: This report explores the role safety nets and transfers can play in reducing poverty more rapidly in Tanzania. It presents the potential need and costs, to inform a debate of options. The report reviews existing programs, and provides recommendations for an action plan to strengthen the current system and develop a more unified national program, one which will have a greater impact on poverty levels at reasonable cost, in line with the Government’s poverty reduction strategy, known by the Swahili acronym MKUKUTA). 2. Definition of safety net transfers for purposes of this study. The report looks at transfers to the poor, including public works employment, subsidies, food distribution programs, cash and in-kind transfers, vouchers, and exemptions: it does not look at formal pensions, insurance, income-generating schemes, or credit programs. 3. Main Findings and Conclusions of the Report x Tanzania has achieved impressive economic growth, but without the hoped-for accompanying decline in poverty. Productive safety nets can accelerate poverty-reduction – by increasing immediate consumption while at the same time enabling the poor to participate more actively in the growth process, and helping them escape inter- generational poverty traps. x Productive safety net programs have proven effective in reducing poverty levels in recent years in Brazil, Mexico, Ethiopia, and other countries. These are programs that either employ large numbers of the poor at a low wage rate for a few months each year, or make small monthly payments to the poorest families in return for ensuring their children attend school, health, or nutrition programs. x Given the large numbers of poor, and limited resources, it is essential that safety net interventions in Tanzania be well-targeted and efficiently organized. They can only be afforded if they simultaneously contribute to other objectives, such as longer-term economic growth or human capital formation. x Significant amounts are already being spent on transfer programs in Tanzania, but the impact is limited. Existing programs cover only a small portion of the poor, suffer from overlap, duplication, and leakage, and in many cases do not achieve longer term poverty- reduction objectives. x Safety net programs can contribute significantly more to poverty reduction in Tanzania. The report recommends moving to a unified national program, consisting of two main programs: a large-scale national pubic works employment scheme for the able-bodied poor; and a program of small but regular cash transfers to those unable to fend for themselves (such as child-headed households, the destitute elderly, disabled and orphans i who do not live with families), with payments linked to other interventions to improve their nutrition, education, and productivity. Such a program might cost about US$ 150 million annually, or 0.3% of GDP, about the same as is currently being spent on transfer programs. x Tanzania currently faces a unique opportunity: many of the existing programs are in the process of redesign within the next year; this restructuring can be used to improve the impact of existing efforts, and at the same time lay the base for the move to a more unified, effective national system. Poverty Analysis for Transfers and Safety Nets 4. Tanzania faces the same dilemma as many low-income countries: there are many poor, resources are scarce, and it is difficult to determine who should benefit from safety net programs. About 33% of the population (some 13 million people) live below the Basic Needs poverty line (equivalent to about $1 a day), and 16% below the Food Poverty Line. 5. Large numbers of Tanzanians live close to the poverty line – making it difficult to distinguish potential beneficiaries from the poor as a whole. However the incomes of the poorest 10% of the population are substantially lower than those of the poor in general, suggesting there is a group of ‘ultra-poor’ who should benefit from social transfers. The problem is that it is difficult to identify these people using administrative systems. 6. In an environment in which there is not good data on people’s incomes, other means have to be used to determine who should benefit from safety net programs. There is not much difference in ownership of basic assets, land, or housing conditions, among the bottom 60% of the population, so it is difficult to use these attributes to identify the very poor, or to design proxy means tests to select beneficiaries. The implication is that in general programs need to be self- targeting (for example by offering employment on public works only at a low wage rate); or use community-based targeting, under which village committees use local knowledge to identify who is most vulnerable. 7. Eighty three percent of the poor live in rural areas, and the proportion of the population living below the food poverty line is almost three times higher in rural areas than it is in Dar Es Salaam, confirming that while there are certainly urban poor living in abject conditions, deep poverty in Tanzania remains very much a rural phenomenon, and the focus of safety net strategy needs to be primarily rural-based. 8. The poorest households tend to be subsistence farmers and day laborers; they are more dependent on agriculture than others, (but not much more; almost half their income comes from off-farm sources). The problem is that the returns to their labor are much lower than for the less- poor. Safety net programs that can help them diversify into higher-return activities (for example by raising agricultural productivity), or increase the returns to their labor, are thus an important part of any strategy. ii 9. Movements in and out of poverty. In designing a safety net strategy it is important to understand whether households are moving in and out of poverty (and thus more likely to need an intermittent ‘cushion’) or living more permanently in poverty, and thus in need of longer-term support. Panel survey data suggests about 25% of rural families move in, or out, of poverty over a 5-10 year period. There is no very clear pattern as to which households fall into poverty, or rise out of it; (although the limited evidence suggests that rising out of poverty is often associated with characteristics of the community - such as market access and integration - as much as it is with characteristics of individual households.) 10. Shocks Faced by the Poor. The primary shocks reported by households include: (i) unexpected crop price movements; (ii) food price increases; (iii) prolonged drought; and (iv) idiosyncratic shocks (death, illness). However these shocks seem to affect the poor and non- poor about equally; the difference is that the poorest households recover from shocks more slowly. 11. One of the main ‘shocks’ faced by the poor is seasonality in food stocks and price: Subsistence households run out of the grain about 5-8 months after the harvest each year, and then enter a ‘lean season’ before the next harvest; but this is also the time when market prices for grain are highest – typically 50% higher than in the post-harvest period - placing tremendous hardship on the poorest. Any safety net or policy intervention that can help ameliorate this seasonal food shock will be an important part of the safety net solution. (Examples include seasonality in public works employment and transfers). 12. Food Inflation. Average prices for key food items increased between 50 and 60% from 2007 to 2009, while the purchasing power and incomes of the poor rose by nowhere near these amounts. Micro-level evidence suggests this has been a major factor in increased impoverishment of the poor in recent years, with households cutting back food consumption as a result. 13. Growth and Poverty. While the economy as a whole has grown by about 7% p.a. over the past decade, the level of poverty has declined only marginally. There is much debate about the reasons for this, but growth-incidence analysis shows that the poorest 10% are benefiting least from growth. This suggests a strong case for focusing safety net interventions at the bottom 10% of the populations that have been ‘left behind’ by the growth process. 14. The very poor tend to engage in low-risk, low return behaviours: examples include limited use of fertilizer, or reluctance to diversify from subsistence grains into cash crops. They cannot take on the risk because they are living so close to the subsistence minimum that they cannot afford the potential losses if things do not work out; or do not have the cash income to finance the necessary agricultural inputs. 15. Consumption; Education and Health: Medical and education spending represent a small share of consumption, even for the poor; and incidence data show the poor tend to use education and health services almost as much as the population as a whole, suggesting that health and education-related interventions (such as scholarships, or health exemptions) may not be as large a part of the safety net strategy in Tanzania as they are in some other countries. However there iii are some behaviours that makes sense to tackle with conditional-cash-transfer incentives: encouraging the poor to start school at the right age; to have girls to remain in secondary education; or to better utilize nutrition, maternal and family planning services. 16. The Geographical Distribution of Poverty. Poverty is concentrated in the central band of the country, but there are large numbers of poor in non-poor areas; so geographical targeting will leave out a lot of very poor Tanzanians. At the same time, Comprehensive Food Security and Vulnerability Surveys (CFSVA) show that the Districts with the lowest food consumption change quite significantly over 5-year periods, suggesting that areas, like households, move in and out of poverty. The implication is that in some circumstances geographical targeting may make sense; but mostly for short-term interventions during a period of difficult years. This argues for programs such as public works employment that can be expanded and contracted as needed. 17. Malnutrition remains stubbornly high throughout Tanzania, with rates of severe child stunting of 13%. Early childhood malnutrition at these levels affects lifetime achievement and productivity. Malnutrition in Tanzania is not strongly linked with poverty levels or food security, suggesting the problem is less food intake than other factors (dietary composition, feeding practices and intestinal disease) and the solution is not transfers per se, but rather targeted nutritional interventions. The implication for safety nets is to link benefits with changes in behaviour or participation in nutrition programs 18. Most-Vulnerable Children (MVCs) and Orphans. There are an estimated 2.4 million orphans in Tanzania. However not all orphans are poor; many are in absorbed into functioning, non-poor households. Recognizing this Tanzania has quite righty developed the definition instead of ‘most vulnerable children’ (which includes those living in child-headed households, with elderly guardians, or in extremely poor households that cannot adequately clothe and feed them); of which there were an estimated. 900,000 in 2010. Clearly these groups need to be a primary target for any safety net support. 19. Poverty among the Elderly. Statistically poverty is not on average worse among the elderly than among the population as a whole, except in households containing only elderly and young children, with no working-aged adults, where it is 50% higher than the national average. These ‘grand-parent-headed’ households are an obvious candidate for safety net transfers. There are also undeniably some elderly living on their own in conditions of extreme destitution. Again the challenge is finding them in order to deliver transfers to this small sub-set of the elderly. 20. Other Vulnerable Groups. There are an estimated 1.1 million people living with HIV/AIDS; and some 2.4 million disabled persons, of whom about 300,000 are estimated to be severely mobility-impaired. As with orphans and the elderly, many of them do not need safety net transfers, because they are adequately looked after by extended family, or are functioning well economically on their own; while others are destitute and desperately need assistance. The difficulty is in identifying which are truly in need of support. Any system will need to need to rely on community knowledge to distinguish the neediest amongst these sub-groups. iv 21. Based on the poverty analysis some very broad conceptual objectives for a national safety net strategy in Tanzania might include: - Focusing on orphans and other MVCs: this has the benefit of being readily acceptable as an objective – both socially and politically – but leaves out many extremely poor people. The same transfer programs that help orphans could be fairly easily expanded to include the elderly and disabled who are destitute. - Reduce the impact of seasonal shocks on the poor: Use selective transfers to cushion the impact of the seasonal grain shortage shock on the poor and medium-poor. This has the benefit that it can be tailored to achieve substantial welfare gains at relatively low cost. (but does not necessarily reach the chronically poor). - Tackling food insecurity and malnutrition: focusing support on those with food consumption below the accepted minimum requirement (estimated at about 16% of the population) – on the grounds that these are the poorest; that inadequate caloric consumption directly affects their productivity and long-term potential; and that it is morally unacceptable that Tanzanians should not have enough to eat. Which of these objectives the country wants to achieve, and how much to spend, depends on social and political preferences, and trade-offs with other poverty-reducing expenditures. The Role of Safety Nets in National Development Strategy 22. Growth, and increasing the returns to the poor’s labor, clearly needs to remain the central solution to poverty in Tanzania. But as we have seen growth is not reaching the poorest fast enough. Under these circumstances there is a logical role for safety net transfers to: (a) raise the productive potential of the poor, so they can better participate in the growth process; (b) help protect against uninsured risk, and provide temporary support in times of difficulty – either seasonal or shocks; and; (c) support those who will likely be left behind by the growth process. 23. A new generation of safety net programs, if well-designed, can raise longer-term productivity through: Creating physical assets: for example by using public works employment of the poor to build or maintain roads, or financing soil and water management, reforestation, and irrigation works. Building human capital: almost all transfers to the poor result in increased human capital formation (due to direct impacts on consumption, and greater use of education and health services); these can be enhanced by using conditional cash transfers to promote participation in nutrition programs, attending antenatal clinics, or continuing girls’ education. Helping the poor escape inter-generational poverty traps: examples in Tanzania include transfers to child-headed households or to elderly persons supporting orphans, allowing the children to continue in school; or linking benefits to improved early-childhood nutrition. v Enabling the poor to diversify sources of income: small injections of cash income, if linked to participation in savings or micro-credit programs, can allow the poor to invest in diversified activities. Examples from Tanzania include very poor women selling clothing or cooked food at local markets. Allowing the poor to take on higher-risk, higher-return activities: an example in the case of Tanzania would be the greater use of fertilizer and other purchased agricultural inputs; or shift to growing higher-valued crops. Finally, safety net transfers represent an injection of funds directly into the lowest level of the economy: where they have high multiplier effects, increasing demand and fuelling growth at the village and small-town level. Coverage and Costs of Existing Programs 24. Tanzania currently operates six main transfer programs (a support scheme or orphans and vulnerable children; distribution of subsidized maize by the government; a school feeding program; two public employment schemes (one for cash and one for food), and a fertilizer voucher scheme); about US$175 million is spent annually on these programs. In addition there are a number of small cash transfers or pension pilot schemes for the poor. 25. Most Vulnerable Children’s (MVC) Program: Provides support to about 570,000 orphans and other vulnerable children; at a cost of about US$ 50 million annually. It provides assistance for education, health services, food, and shelter.1 Vulnerable children are targeted through community groups – the targeting system appears to work well, but unit costs are high (about $80 per beneficiary), and the value of benefits delivered to children are low relative to costs. Benefits are sporadic, and do not always correspond to the greatest safety net needs of individual children – which might be more for food or cash. The program is implemented through the Department of Social Welfare and a network of international and local NGOs; it is financed primarily by PEPFAR (USAID) and the Global Fund. 26. Subsidized Food Distribution: the National Food Reserve Agency (NFRA) is used by the government to distribute food free, or at highly subsidized prices. It reaches about 1.2 million people annually, at a cost of about $19 million equivalent (2009/10). Food is directed to Districts identified as food insecure each year; and typically covers about a third of the country. Subsidized food is in theory targeted at the poorest in each community, but there is no data on actual beneficiaries, and survey evidence suggests that there are large inclusion errors (that is, food going to households that are not the poorest). 27. School Feeding: currently covers about 600,000 primary students, or 8% of the total, at a cost of about $18 million annually. The program, funded largely by WFP, is concentrated in food-insecure Districts. Studies show that it has some positive impact on learning and attendance, but the effect is not overwhelming. Unit costs are $31 per student per year, and the food transferred represents about half of the daily nutritional requirements of the child. The program is not targeted within schools; there is no data on beneficiaries, but inclusion errors may 1 Note MVC is not solely a transfer program, but also finances community and social support capacity-building. vi be large. To expand nationwide would cost about US$250 million annually. In the longer term ways need to be found of making the program sustainable, and limiting its costs (perhaps by sifting to take-home rations for the poor) 28. Public Works Employment Programs: Two public works programs are run by local governments and TASAF (which pays in cash) and WFP (Food for Assets, which pays in food). Both are very small – each employs about 25,000 people a year, reaching about 1% of the poor. They both suffer from providing only once-off benefits to households, so the impact on poverty- reduction is limited; and they operate mostly in Districts ranked as food insecure, so miss much of the country. However they provide the basis – with appropriate design changes - for the move to a larger-scale national public employment scheme for the poor. The food-for-work program is considering shifting to paying cash for work for at least some beneficiaries; and it would make sense to move both programs towards a coordinated (and ideally, ultimately a unified) approach. 29. Pilot Cash Transfer Programs: (KwaWazee; SCF, TASAF). Existing programs are very small pilots, reaching only a few thousand households. Based on the limited experience so far, they seem to have had success in improving living conditions; have tested systems for identifying and targeting beneficiaries; and have introduced the principle of conditionality of transfers. The TASAF Conditional Cash Transfer (CCT) program, which targets the poor and vulnerable, is due to be scaled up; it would be logical to combine it with the elements of the MVC program, which has a larger-scale, established targeting system, and which should shift more to cash payments; into a single national system of cash transfers that supports MVCs/orphans and the destitute elderly and disabled. Other Public Transfer Programs 30. National Agricultural Input Voucher Scheme: The largest single transfer program in the country, NAIVS provides vouchers for seed and fertilizer to 1.5 million small farmers. Although designed primarily as a productivity-enhancing scheme, it has several characteristics that may make it attractive as a longer-term productive safety net program. The value of benefits to the household can potentially be as much as $3 for every $1 spent by Government on the vouchers; and the fertilizer/seed intervention can help the poor shift to higher-risk, higher-return production practices. Although in theory targeted at farmers with less than 1 ha, in practice benefits are currently going to mostly non-poor farmers. A revised version of the program in the longer run, targeted only at poor farmers, with smaller and/or free packages, could be a highly-leveraged form of support. 31. Vulnerable Groups Program: Operated under TASAF, provides grants to small groups to run income-generating projects, at the cost of about US$7 million p.a. Data shows it reaches the poor, but coverage is limited (about 18,000 annually). The grants provided are large (about three times the poverty-line income), and as yet there is no information on the financial viability of the projects financed. The VG program is not really a safety net transfer, in the sense of other programs reviewed, and needs to be compared with the many other income-generating and micro-credit programs in Tanzania as part of a graduation strategy. vii 32. Pensions for the Elderly: Formal pension programs cover only about 6% of the population, who are all employed in the formal sector, and are not among the poorest. Of note however is a proposal to expand coverage of old age pensions to the non-formal sector, with a universal, non-contributory old age pension. The proposal, which is estimated to cost about US$227 million equivalent annually, would involve very large inclusion errors (many elderly are not poor); and the same money could have a far larger poverty-reduction impact if directed at safety net programs that benefit the poorest. The report recommends instead a targeted social pension, with cash transfers to the very poor elderly, building on the MVC and CCT pilot models. 33. Assessment of Overall Impact: Tanzania is already spending quite a lot on transfer programs (about $175 million annually, or $ 83 million excluding the NAIVS voucher scheme), but coverage is limited; most programs reach less than 1% of the poor.2 x The limited data suggests there are major inclusion errors (providing benefits to people who do not need them) and exclusion errors (missing people who do need support): most existing programs are targeted geographically at food insecure Districts; this makes some sense, but the result the overlapping coverage by different programs in the same areas, and almost none in other areas x Almost none of the programs keep good data on who they are reaching (some are in the process of collecting it) but the limited CFSVA survey findings suggest some concerns – a significant share of benefits appear to be going to the non-poor x Much more rigorous, and independent, evaluation of the impact of programs is needed. x There is overlap, and duplication of approach. (For example the MVC, public works, NAIVS, TASAF CCT, and food-for-assets programs all operate different community- based targeting systems to identify the neediest at the village level3) x There is very limited coordination of benefits or beneficiaries: the same household (or village, or District) could receive benefits from 5 or 6 programs, while others - equally poor - receive none4 x Many existing programs only deliver once-off benefits to a household (PWP – TASAF, FFA), or very small and intermittent ones (MVC), which have little or no impact on poverty levels, on productivity behaviors, or human capital development – what is required is more sustained – and predictable - transfers. Fiscal Space and Affordability 34. The report estimates cost of a number of options for national safety net using different scale and coverage of suggested programs. These estimates range from US$100 million per year 2 Only the MVC, NAIVS, and subsidized food sales from the NFRA appear to reach any significant share of the population; and the MVC delivers small and intermittent benefits; the NAIVS is not targeted at the poor; and NFRA appears to suffer from significant inclusion and exclusion errors. 3 In some cases different mechanisms are justified due to differing program objectives – but a single community- level targeting system should be able to be adapted to identify variants of the main target groups – the very poor and vulnerable. 4 In theory coordination of programs takes place through Directors at the District level, but the capacity and systems to track individual beneficiaries are not there. viii to over US$500 million per year. It should be noted that total public spending on social transfer in Tanzania in 2008/09 was about US$7 billion. Given competing demand for public budget, the upper range does not seem to be realistic, but a more moderate program, in the order of $150-200 million annually, is probably affordable. 35. Current spending on all transfer programs is about US$ 175 million p.a.5; representing about 2.5% of public expenditure, or 0.3% of GDP, which is towards the low end of comparator countries, suggesting that Tanzania should be able to afford to spend somewhat more than it currently does. 36. All sectors are under-resourced in Tanzania, and financing for safety nets will remain tightly constrained, arguing for careful choice of programs and rigorous prioritization. However safety nets are a core function of government in all countries – even in very low income ones - and have the potential to contribute much more than they currently do to poverty-reduction in Tanzania. 37. The policy implications are, that given the fiscal constraint: x Programs should capture existing expenditures to achieve safety net objectives (using recurrent expenditure on road maintenance to employ the poor in the off-season is a good example); x Programs should be chosen that leverage spending, to produce the greatest consumption benefits to the household per dollar spent (the agricultural input scheme is a good example); and, above all, x Careful attention needs to be paid during design to leakage, targeting, and delivery costs. The Way Forward 38. The report recommends a combination of programs that seeks to achieve three objectives: - More broadly raise the incomes of the poorest and most food-insecure, through a system of sustained (and financially sustainable) productive transfers; - Helps protect against lean-season food shortages and price rises; and, - Provides targeted, direct support to those unable to participate in the labour force or fend for themselves: the subset of disabled, elderly, and orphans and other vulnerable children who are not living in viable households. 39. Tanzania can afford such a program, if it refines existing approaches, scales up a limited number of programs to achieve greater cost-effectiveness, and utilizes money that is already being spent, either in the budget, or on donor-financed safety net programs. 40. A number of basic principles need to underlie any revised safety net program: 5 US$83 million excluding the fertilizer vouchers scheme, which is not targeted at the poor. ix x Transfers need to be provided to the poor in a consistent and predictable manner – this generally means a monthly transfer, as opposed to once-off; x Coverage needs to be greater – reaching a few tens of thousands of the poor will not make a difference; x Rather than the current collection of small (mostly donor-driven) interventions, select a very few cost-effective programs, and operate them on a scale that is large enough to make a difference; x Programs should be capable of being scaled up and scaled down as need dictates – especially for seasonal coverage in the hungry season; x Programs should be chosen that simultaneously contribute to longer-term growth and poverty reduction (examples include creating assets under public works employment programs, or promoting use of modern varieties and fertilizer use through input subsidies targeted at the poorest farmers); x Programs should generally shift to cash transfers, although it may make sense to retain some food and in-kind transfers in specific circumstances – for example in places where no food is available in the lean season; x Keep it simple – targeted programs are administratively burdensome, especially on mid-level local supervisory staff, who are in short supply in Tanzania - system design should be kept simple; and avoid the stop-start programming which has characterized past approaches – moving towards a more unified national program will help; x Establish an institutional home for safety nets; identifying one agency with overall responsibility for safety net programming will improve coordination, monitoring, and impact; x The time is right for Tanzania to move toward a more unified, and permanent national safety net system. Even though the degree of need will go up and down over time, there will always be a need for some form of productive safety net for the poorest; rationalization of existing programs over the next two years can create the basis for such a permanent national safety net system. 41. The Targeting Challenge. Universal vs. Targeted Programs: the evidence (and fiscal constraints) argues strongly for maintaining a targeted approach. Universal programs would involve too many inclusion errors, and be too expensive in Tanzania at this stage. 42. Given the administrative and data constraints, programs should use self-targeting wherever possible (examples include offering low-wage public employment, which will only appeal to those without any other income opportunities), or small ‘packages’ of benefits (such as low-valued fertilizer vouchers, or very small cash transfers). 43. Community-based targeting: using local knowledge, transparent processes and village committees appears to be the only feasible way to identify the neediest (e.g. orphans, elderly, disabled who need support, as opposed to those who do not). The MVC program has made good progress – it should form the basis of a broader-based national system. However the difficulty and costs of operating effective community-targeting systems should not be under-estimated. 44. Geographical targeting: there are both attractions and drawbacks to this approach. There are some very poor food-insecure areas, and when resources are constrained concentrating on x them provides a simple way of prioritizing. However calculations show that concentrating on the lowest third of Districts rated food insecure (as most programs currently do) leaves out about 68% of the extremely poor population in Tanzania. As the move is made to a more unified program, it should be national in scope, with the capacity to scale operations up or down regionally in response to need. 45. Recommendations: The report recommends a national program that consists of: x A large national-scale public works employment program: for the able-bodied poor, concentrated in the four-month ‘lean season’ (because it is self-targeting, builds assets that can raise incomes in the longer term, and can be scaled up and down in response to needs – both in time, and geographically); plus, x A limited program of surgically-targeted cash transfers: (either conditional or unconditional) for those who cannot work. (Focused on providing predictable transfers - mostly in cash – to orphans/MVCs, the destitute elderly and disabled who are not adequately looked after by families.) 46. The seasonal public works program would likely account for the majority of beneficiaries, perhaps 75-80%. 47. Policy-makers face two choices: how widely to expand coverage of cash transfers (as opposed to public works), and whether or not to make them conditional. The report argues that Tanzania can probably not afford to extend cash transfers beyond the most vulnerable who cannot participate in public works schemes – this would imply about 2-4% of the population, and even that amounts to 1 million people. If the coverage is that small, it means focusing on only the truly destitute, in which case there would appear little rationale for requiring them to comply with conditions; however: (a) there is a strong preference for conditions, including among beneficiaries; and (b) conditions, even if fairly ‘soft’ can be used to encourage human capital formation within these groups. 48. This program should involve a more unified approach - to identification, targeting, delivery - through either a single national program, or at least far greater coordination across programs within a common framework. The result would be greater poverty impact at an affordable level of spending. 49. The move towards this program can phased with: (i) immediate steps to strengthen existing programs; (ii) restructuring of the existing package of programs over the next two years – to rationalize them and lay the basis for a more unified permanent national system; and (iii) over the longer term, movement towards a single national program, owned, and largely operated, and eventually financed, by the Government of Tanzania and domestic organizations. 50. Tanzania currently faces a unique opportunity to achieve this re-structuring. - Existing programs are all currently being revised or restructured (TASAF, MVC, WFP) within the coming year. xi - There is a strong basis for building on and expansion in several programs: the MVC program, which has established a community-targeting system that covers much of the country; the TASAF public works and WFP food-for-work programs, which have established functioning public works employment systems; - This restructuring represents an opportunity to much better co-ordinate targeting, beneficiary coverage, and delivery mechanisms. It can lay the basis for the move to a more permanent, public system of transfers, which can be expanded, and fine-tuned over time. - There is strong donor interest in supporting expansion - especially if structured around a unified national safety net program; this donor funding – which would have to be committed over a fairly long timeframe – could build the bridge to more sustained public financing of the system over time. 51. Next Steps. The following immediate steps are recommended. x Evaluate community targeting systems under existing programs (MVC, FFA, TASAF CCT, vulnerable groups, NAVIS) identify best practices, and combine into a single national system for identifying the most needy at the village level, for all cash and in-kind transfers programs. x Initiate discussions between the Department of Social Welfare (DoSW), USAID, PEPFAR, and the Global Fund on shifting MVC from sporadic in-kind support to more predictable cash and food transfers. x Review geographical targeting, its effectiveness, and overlap and exclusion errors, and decide what extent to pursue geographical targeting in the national safety net program. x Review experience with Food-for-Assets and TASAF public works programs, take the best of both and consolidate into a single, consistent national model for employment- based transfers to the poor. x Examine the potential for using existing (or expanded) spending on maintenance of roads and other public infrastructure to employ the poor during the lean season– using a self- targeting low wage rate. x Identify mechanisms for coordinating geographical coverage of PWP and Food-for- Assets. x Bring together donors, DoSW and TASAF and discuss consolidated approach to moving forward on next phase on a unified national program of cash transfers; both conditional and unconditional. x Monitor and review experience with NAIVS, start considering follow-on program targeted only at poor farmers. x Undertake a more detailed review and analysis of targeting errors for food distribution (NFRA), Food-for work, and school feeding implied by the CFSVA data, to assess the extent of benefits going to the non-poor, and scope for rectifying inclusion errors and redirecting resources to the poor. x Examine mechanisms for better tracking and coordinating overlap of coverage by all programs (including PWP, FFA, school feeding, MVC, cash transfers, VG and NFRA) to reduce gaps, and rationalize duplication of support. x Establish an institutional home for safety nets in Government. xii 52. Shape and Costs of A longer-Term System. The report presents three illustrative options for the costs and coverage of a unified national safety net program. The middle of the three options consists of a public works program that would provide employment to about 700,000 people annually (3-4 million total beneficiaries; reaching many of the chronically food- poor), most receiving about four months’ worth of transfer annually; combined with a cash transfer program that would provide about Tsh. 5,000 per month per adult equivalent (about US$ 40 annually) to about 300,000 households (estimated 1 million total beneficiaries; consisting of the most vulnerable and destitute MVCs, elderly and disabled). The cost is estimated at about US$ 150 million p.a., much of which could be financed by re-directing existing resources. 53. The cash transfers could be either conditional or un-conditional. Conditional transfers to support building human capital might include tying payments to: (i) participation in nutrition programs, or use of micronutrient supplementation packs; (ii) starting school at the appropriate age; (iii) regular school attendance (for some groups and areas); (iv) girls staying in school beyond Form IV; (v) participation in neonatal and family planning programs; (vi) delivery of babies at safe facilities. Each of these requires further investigation as to likely effects and costs. 54. Other options the Government might want to consider, to supplement this core program, include: - Possibly a continued version of NAIVS in the longer-run – but smaller, targeted at poor farmers (because it delivers the largest benefits for each dollar spent) - Utilizing increased rural road maintenance spending to employ the poor at a self- targeting wage-rate, (to expand the coverage of the PWP component, while addressing the backlog of under-funded maintenance and providing essential routine maintenance that has a high pay-off). Financing the transition to a more significant national safety net program 55. Donors currently finance about 75% of transfer expenditures. Some of these resources are fungible, and some are not (for example most funding for the MVC program is tied to donor HIV/AIDS programs). The trick will be to capture donor financing in support of the transition. Donors with limited fungibility can be encouraged to re-orient exiting programs in support of the unified national program; for others re-direction of financing and/or re-design of programs can be negotiated. Over time, it should be possible to engineer more ‘basket’ financing for a unified program (this approach has worked in Ethiopia, for example); and slowly transition into picking up more of the financing out of the recurrent budget. xiii CHAPTER I: INTRODUCTION Background – Why Safety Nets and Transfers? 56. Tanzania has made significant economic progress in the recent past, with per capita national income almost doubling from US$ 230 equivalent in the late-1990s to US$ 440 today6 . Nonetheless, in 2007 about 13 million people lived below US$ 1 per day, and about 6 million, or a sixth of the population, consumed less than the minimum basic food requirements. 57. Despite a decade of impressive GDP growth, averaging about 7% p.a.7, poverty rates have remained stubbornly high. The failure of growth to reduce poverty in Tanzania has been the subject of much recent debate (see for example Hoogeven and Ruhindula (2009))8. The reasons in part have to do with the composition of growth, and the failure of the rural agrarian economy to transform rapidly enough to keep up with population growth. The net effect, however, is that there remain many people whose incomes have not grown adequately as a result of the growth process. 58. In addition the poor in Tanzania face risks and shocks which undermine their long-term productivity, and hinder the transition to higher-return activities (examples include seasonal unpredictability in their food production and prices, the impact of long-term droughts, and the loss of breadwinners to HIV/AIDS). At the same time, there are some large and growing groups of the poor who are overwhelming the capacity of traditional safety nets to support them – the most notable being the 1 million orphans and most-vulnerable children. 59. Under these circumstances, it makes sense to ask what role public safety net programs might play in accelerating poverty reduction. Well-designed transfers can raise the immediate consumption of those who are living below the poverty line, while at the same time facilitating more permanent increases in their incomes – through building human capital, enabling the poor to take on higher-return activities, or to escape from inter-generational poverty traps. Box 1 below highlights some key ways in which this might be achieved in Tanzania. These results are not guaranteed however, and depend on the judicious choice of programs and design. This paper examines the current safety net efforts in Tanzania, and suggests how they can be adjusted to achieve greater poverty-reducing impact. 6 2008 GNI, atlas method. 7 2001-2008 8 “Lost in Translation: Poverty Reduction in Tanzania since 2001;Good intentions, few results” 1 Box 1: Safety Nets: Accelerating and Deepening Pro-Poor Growth The right choice of safety net programs can protect immediate consumption, while helping to more permanently reduce poverty: x Transfers under public-works employment schemes can create assets for longer term growth (examples include building roads that improve access and market integration, or undertaking soil and water management, reforestation, and irrigation works.) x Safety net transfers help the poor cope with the impact of shocks; in Tanzania this includes cushioning the annual shock of food shortages and price rises (which result in reduced consumption and productivity losses); or preventing the more permanent declines into destitution that result from families selling assets, such as land or livestock, during prolonged droughts. x Safety net programs can support human capital development – almost all transfers result in increased human capital formation by households (due to direct impacts on improved consumption, and greater use of education and health services); this effect can be intensified by linking payments to school or clinic attendance, use of nutrition programs, or providing scholarships for girls who continue their education. x Safety net programs can help the poor manage risk – by allowing them the flexibility to take on higher-risk, higher-return activities (an example in the case of Tanzania would be the greater use of fertilizer and other purchased agricultural inputs; or diversifying cropping). x Safety net transfers can lift the poor out of inter-generational poverty traps – examples in Tanzania include transfers to child-headed households, or elderly persons supporting orphans, allowing the children to continue in school; or improve their nutritional status. x Safety net transfers can help the poor finance the transition to more permanent income increases – injections of cash income can allow the poor to build small amounts of capital and invest in diversified activities (good examples from Tanzania include poor women selling clothes or food in local markets). x Finally – safety net transfers represent an injection of funds directly into the lowest level of the economy; where they have high multiplier effects, increasing demand and fuelling the growth of opportunities at the village and small-town level. Objectives of the Study 60. This paper explores the possible role of safety net transfers in Tanzania. It is worth noting at the outset that the study looks at programs that provide transfers to the poor – either financially, or in-kind – such as public works employment, food and feeding programs, and subsidies and cash payments. It does not look at the many other forms of public intervention that can improve their lives (for example education and health services, income-generating programs or loan schemes), nor does it go into any depth on contributory pension schemes in the formal sector; not because these are not important, but because they are adequately addressed elsewhere.9 9 See for example, “Options for Reform of the Tanzania Pension System” draft August, 2010; World Bank 2 61. Safety net transfers are a core function of the state. Even in very low-income countries Governments want to protect those who are at unacceptably low levels of consumption, and productive safety nets form an essential ingredient in the poverty reduction strategy. However there are many competing demands for public expenditure, and in the tight fiscal circumstances faced by the Government of Tanzania, safety net programs need to be carefully chosen so that they are cost-effective, and simultaneously contribute to the kind of productivity enhancing objectives outlined in Box 1. 62. Tanzania has recognized this: social protection is a pillar of MKUKUTA, and the draft national Social Protection Policy Framework lays out the broad outlines and priorities of the government. However it lacks specificity on program interventions. A key objective of the current study is to present a range of costed program options. 63. This paper attempts to lay out what the options might be, to locate them within an analytical assessment of the nature of poverty and shocks faced by the poor in Tanzania (Chapter I). It examines the effectiveness of existing transfer programs (Chapter III): how well they are working, how cost-effective they are, and how well they address the needs of the poor in Tanzania. Based on this, it makes suggestions as to which programs it might make sense to scale up (and also which it may make sense to reduce or phase out). It also looks at approaches that have been tried elsewhere, but do not exist in Tanzania, which might form part of the national safety net strategy. 64. At a strategic level it then evaluates the capacity of the state to spend on transfers, and how safety net programs might fit into the wider national development agenda (Chapter IV). The paper concludes by discussing some of the institutional and administrative concerns that effect program design (Chapter V); and then outlining both a series of immediate steps to improve the effectiveness of existing programs; as well as a medium-term strategy for moving towards a more unified national program (Chapter VI). 3 CHAPTER II: POVERTY ANALYSIS FOR SAFETY NET TRANSFERS 65. Deciding what the ‘right’ safety net strategy is depends on the nature and distribution of poverty. This section examines the characteristics of poverty in Tanzania, in order to help determine: x What aspects of poverty – including shocks and uninsured risks – can be addressed using safety net transfers; x Which groups to target; and, x Whether there are characteristics of the poor – such as where they live, what they do, or what they own – that can be used to help design and target safety net programs. 2.1 Poverty and Ultra-Poverty in Tanzania 66. Approximately 12.9 million persons, or 33.6% of the population, lived in poverty in 2007 (defined as having less than the minimum consumption required to meet basic needs)10 , and some 6.4 million, or 16% of the population, lived at levels of income so low that they cannot afford to consume the minimum daily intake of calories. 67. The first thing the policy makers should be concerned with from a safety net point of view is how that poverty is distributed among the population: are there many people, for example, gathered fairly narrowly around the poverty line; or smaller proportions of the populations who are very far below it? Figure 1: Distribution of income in Tanzania Fig. 1 Distribution of Consumption - Relative to the Poverty Line (2007 Tsh per adult equivalent per month) 100000 80000 Average per capita Consumption 60000 40000 Food Poverty Line 20000 0 Basic Needs Poverty Line 1 2 3 4 5 6 7 8 9 10 68. A number of things are immediately clear from Figure 1: except for at the tails, the distribution of income is relatively flat, with the largest share of the population living just above the poverty line. There is also quite a large group (about 6 million people) who live below the poverty line, but not far below it.11 10 Household Budget Survey (HBS), 2007. 11 These are the population who live above the food poverty line, but below, or just below, the basic needs poverty line- a difference of only about US$ 2 per month on average (per capita, based on half the distance between the Basic Needs and food poverty lines in 2006 Tsh.). 4 69. When thinking about safety nets, it is worth asking whether there exists a distinct group of ‘ultra-poor’ who are significantly worse off than the poor as a whole, and whom it might make sense to target with safety net transfers. To examine this question in more detail it is necessary to unpack the distribution of incomes among the bottom half of the population (see Figure 2). It is clear that there is a distinct discontinuity in consumption; the average incomes of the poorest ten percent of Tanzanians, for example, are 40% lower than those of people in the next decile. Figure 2: Differences in Average per capita Consumption among the Poor (Per capita monthly household consumption, Tsh. Per adult-equivalent 2006) 20000 15000 10000 5000 0 Poorest 2nd 3rd 4th 10% Poorest Poorest Poorest 10% 10% 10% Source: HBS data. 70. In subsequent sections the report examines in a bit more depth the attributes of this group – their demographic characteristics, the assets they own, and how they make their livings – to try to ascertain whether there ways to identify and target them. 71. On the basis of a very broad decomposition of the population into poverty groups, then, Table 1 summarizes the numbers of people in some main poverty categories. Later on (Chapter 4) the report explores the implication of these numbers for possible objectives of a national safety net program. 5 Table 1: Approximate Numbers in Broad Poverty Groups 2007 Approximate Cumulative Income/Consumption What It Means Number of Number of Level Persons Persons The Bottom 10% Have incomes far below even the 3.8 million 3.8 million poor in general – obvious target for safety nets. Below Food Poverty Line The very poor – almost certainly 6.4 million 6.4 million require some form of safety net intervention. Above Food Poverty Line May require intermittent safety net 6.3million 12.7 million but below Basic Needs support, in difficult times. Poverty Line Sources: HBS 2007, Rapid Poverty Assessment (2008); own calculations 2.2 Characteristics of the Poor and the Very Poor 72. The objective of this section is to look at various attributes of the poor, and the non-poor, and the very poor, to help understand whether there are aspects of their poverty that it makes sense to tackle with safety net transfers, and – equally importantly – to help think about criteria that might be used to identify and target beneficiaries. 73. The poor in Tanzania are overwhelmingly rural (84% of the poor), and overwhelmingly dependent on agriculture as their primary source of income (74%). Table 2: Some Basic Characteristics of the Poor In Tanzania 2007 Area of Residence (% of poverty group) Ultra-Poor/a Poor Non-Poor Urban 18.7% 17.9% 33.7% Rural 81.3% 82.1% 66.3% Primary Occupation (% of poverty group) Farming, Fishing, etc 86.2% 81.3% 59.3% Self-Employed 9.6% 11.2% 22.5% Employee 4.2% 6.5% 17.3% Average Household Size (No.) 6.7 5.9 4.3 Source: 2007 HBS data, and PHDR, 2009; a/ Living below the food poverty line 74. Poverty is not notably higher among female-headed households and the elderly than in the population as a whole. This does not mean that many women in Tanzania, and many of the elderly, do not live in very difficult circumstances, only that in a consumption sense the household data do not reveal any consistently higher incidence of poverty. We cannot, of course, say anything on the basis of the HBS data about the distribution of consumption within households, although micro studies and anecdotal evidence often suggest that children and women receive less than proportional food shares. (See for example, UNICEF (2008)). 6 Although it is not as obvious from the aggregated data, the very poor tend to live in larger households12. Figure 3 illustrates the very strong relationship between number of household members and poverty. Figure 3: Household Size and Poverty Incidence Figure 3- Household Size and Poverty 60 Incidence Incidence of Poverty 9 10+ (Headcount Ratio) 50 40 8 7 6 30 5 20 4 3 10 1 2 0 0 5 10 15 No. of Household Members Source: HBS 2007, Table 1.1, Chapter 8. Asset Ownership among the Poor and the Extremely Poor 75. The data do not reveal any very distinct differences in asset ownership between the poor and the non-poor, with the obvious exception of higher-end assets such as televisions and motor cars. While ownership of more basic goods such as bicycles, radios, and farm implements does increase with income (Table 3), it is relatively evenly spread among the bottom 60% of the population, making it difficult to use asset ownership as a targeting proxy for transfers. Table 3: Housing Quality and Asset Ownership by Income Status 2007 Non-Poor Poor/a Very Poor/b Bottom 10% Housing Quality Mud or Earth Floor 63.5% 83.4% 88.4% 90.8% Mud or Earth Walls 62.7% 75.9% 83.0% 87.3% Durable Roof 58.2% 41.8% 29.6% 27.9% Toilet - % with no toilet 5.8% 8.0% 10.8% n.a. Ownership of Some Key Assets Radio 75.6% 63.2% 51.2% n.a. Bicycle 50.5% 47.2% 41.6% n.a. Plough 10.7% 13.3% 15.3% n.a. Sheep, Goats, etc. (number)/c 4.6 4.9 3.5 n.a. Cattle, Lrg. Livestock (no.) /c 5.8 9.8 3.0 n.a. Source – HBS data; created from Tables 38-40, PHDR 2009, and Rapid PA tables 3.4-3.6; a/ Poor are below the Basic Needs poverty line; b/ Extreme Poor below the Food Poverty Line c/ rural sample only. 12 This is to some extent tautological, as incomes – which are determined primarily by agricultural production - are spread between many more people (generally children and older dependents) in large households, and household per capita incomes are therefore lower. 7 76. Similarly, although there is a relationship between income status and housing conditions, almost all of the poorest half of the population lives in houses with mud or earth walls and floors, and without a durable roof (Table 3), so the value of housing status as a means of distinguishing the very poor from the poor is limited. 77. Landholding: The most significant asset in determining poverty status in an agrarian economy is usually landholdings, and in many such countries the very poorest are those who are effectively landless. The relationship in Tanzania is more complex. Both the HBS (2007) and the Agricultural Census (2005) show surprisingly little difference between the landholding patterns of the poor and the non-poor, and that quite a large share of even the very poor own what, in other countries, would be considered quite substantial holdings (5 acres plus). This may be in part because the data does not account for difference in land quality (the poor may have land in low-productivity areas, or own large plots of dry grazing land), and in part because Tanzania is less densely populated than other low-income countries. The implication is that targeting safety nets on the basis of landholdings, to reach the very poorest, is less feasible than elsewhere. Table 4: Landholding by Income Class in Rural Tanzania (% of Income Group owning amount of land shown) Non-Poor Poor Very Poor None 26.0% 13.3% 12.8% < 1 acre 9.7% 10.1% 10.4% 1-2 14.8% 16.0% 16.4% 2-3 12.6% 14.2% 16.0% 5+ acres 21.2% 28.0% 26.3% Source: calculations based on HBS data. Note the accuracy of landholding data in the HBS cannot be confirmed. 2.3 Movements In and Out of Poverty; and the Impact of Shocks 78. An important consideration when planning safety net interventions is whether people are chronically poor, or whether they are moving in and out of poverty; that is, whether the same households need continuous support, or a different population of beneficiaries needs help at different points in time. 79. Households may be stuck well below the poverty line – caught in traps which prevent them from generating enough income to ever rise to an acceptable level of consumption – in which case they likely need continuous support in the form of transfers. Or, they may live near the poverty line – being above it in good times, and falling below at others - in which case they need only an intermittent safety net. 80. Furthermore, in a longer-term, dynamic sense, some households may be rising out of poverty over time, as their circumstances change, and others may be falling into poverty (for example as people age). 81. Unfortunately there is little information on movements in and out of poverty in Tanzania. Recent qualitative work by the Chronic Poverty Research Centre (2010), and panel survey data in Ruvuma and Kilimanjaro (Pan and Christiansen, 2010) suggest about equal shares of the population falling into, or rising out of poverty over a 5-10 year period. The reasons for 8 improving livelihoods generally have to do with better agricultural productivity, diversification of income sources, and attributes of the community rather than of the individual household (such as improved access, and market integration). Table 5: Movements In and Out of Poverty Kilimanjaro and Ruvuma Panel Surveys 2003-2009 Remained Fell Into Rose Out Remained Poor Poverty Of Poverty Non-Poor Kilimanjaro 22% 18% 18% 42% Ruvuma 21% 20% 20% 41% % of Households; constructed from Christiansen & Pan; See Annex table – for more disaggregated data .Note poverty line is from panel data, differs from national HBS poverty line. 82. Between 10-25% of the population in these small samples were judged to have fallen into poverty during the reference period. Reasons for deteriorating livelihoods include the effects of prolonged drought, price declines for crops, and – to a lesser extent – idiosyncratic factors such as death or illness. In many cases villagers have cited the large increase in food prices (discussed below) as a reason for reduced consumption in recent years (see for example de Corta et.al.). 83. Shocks faced by the poor – in fact by everyone - include drought, unexpected declines in cereal and cash crop prices, crop and livestock loss due to pests or theft, and death of a household head; but the reported incidence of these shocks was no higher among families who had fallen into poverty than in the population as a whole (or even those who had risen out of poverty), making it difficult to generalize as to what factors cause families to become poorer. (See Table 6 and Annex 1.2). Perhaps the greatest ‘shock’ faced by poor households is the annual shortages and price rises in basic food grains, discussed later in the section on food security. Table 6: Proportion of Households Reporting Shocks in Past Year – By Income Transition Group Remained Fell Into Rose Out Remained Poor Poverty Of Poverty Non-Poor Drought 17% 12% 17% 15% Unexpected Decline In Cereal Prices 11% 5% 21% 22% Unexpected Increase in Cereal 11% 11% 20% Prices Unexpected Decline in Cash Crop 20% 19% 26% 20% Prices Major harvest loss 16% 20% 18% 19% Loss of Livestock 16% 18% 5% 17% Major Illness 22% 18% 23% 17% a/ Constructed from Christiansen and Pan;Tables 46, 47 Kilimanjaro sample, Incidence of shock applies to previous 12 months in Initial survey period; Ruvuuma sample results are not very different .Poverty line from panel 84. Work on coping strategies (see Kessy; da Corta; Higgins; and WFP (2010)) shows that households adjust primarily by reducing food intake. There is little analytical work on the impact of coping strategies; and the relationship with income status does not emerge clearly (perhaps because the poor have less room to reduce consumption and fewer assets to lose). What is clear is that the poor take longer to recover from whatever losses they incur after shocks. (Table 7). 9 Table 7: Impact of Drought and Recovery By Household Food Poverty Status Food Poverty Income Loss Asset Loss Due Food Loss Due HH Totally HH Category/1 Due to Drought to Drought to Drought Recovered Partially Recovered Poor 80% 24% 91% 6% 29% Borderline 92% 31% 82% 7% 28% Acceptable 91% 35% 77% 15% 38% Source: CFSVA; % of HHs reporting loss; 1/ HH Food consumption status as measured in CFSVA;see p.17. 85. Panel survey data13 show just over half of the poor remaining in poverty during a 5-year period (with the balance, about 46%, rising out of poverty). Conversely, about a third of families who were not poor in the first round had fallen into poverty 5 years later. To the extent these findings can be generalized, the implications for safety net strategy are that (a) there is a significant core of the poor who remain poor (and thus probably require sustained transfers); but at the same time: (b) there is also a sizable minority who move in and out of poverty, for whom a flexible safety net is needed. There are very few obvious correlations of movement in or out of poverty with other household attributes (see Annex 1.2), making it difficult to say with certainty which types of households would need continuous support. 2.4 What Is Poverty? How Much Do the Poor Earn, and Where Does Their Money Go? Income levels: What Does Poverty Mean? 86. The Basic Needs poverty line in 2006 was about Tsh 14,000 per adult per month, roughly equivalent, in purchasing power parity terms, to US$ 1.10 per day, and is thus very close to the international dollar-a-day norm.14 The food poverty line is about 80% of that, or roughly equivalent to US$0.80 per day. Table 8: The Definition of Poor: Levels of Poverty in Tanzania Level of the Poverty Line Tsh per person per month (2007) Equivalent in US$ per day/a Food Poverty Basic Needs Food Poverty Basic Needs Line Poverty Line Line Poverty Line Tanzania 10,219 13,998 $0.80 $1.10 Mainland Estimated: 2010 /b 14,000 18,100 a/ Based on PPP exchange rate of Tsh 454/US$, and 28 days per month. b/ late 2010;Tanzania mainland ;Author’s calculations, based on CPI changes 2007-2010 . 87. According to the HBS in 2006 the poorest people in Tanzania were surviving on an average income of Tsh. 7,335 per month15, equivalent to about 57 cents US per day16. There is some doubt that people’s incomes are quite as low – in absolute terms – as the HBS data 13 Christiaensen and Pan, 2010. 14 As calculated in Rapid Poverty Assessment, 2009; p.7-8. 15 Decile-wise HBS data; household per capita consumption for lowest 10%World Bank calculations. 16 Based on PPP exchange rate Tsh 454 per US$. 10 suggests.17 It is likely however, that the relative orders-of-magnitude are correct; and if the poorest are living at anywhere like these levels of consumption, the argument for focusing a national safety net strategy on the very poorest –say the bottom 10-15% - is extremely strong. 88. Growth and Poverty: Although there is some debate about the data, it is nonetheless widely agreed that the impact of growth in Tanzania has not been as a great as would be hoped for. What is interesting from a safety nets point of view is the distributional impact of growth, and to what extent it reaches (or fails to reach) the poorest. Fig 4 shows the growth incidence curve, which illustrates the impact of economic growth on consumption by income group. The curve is relatively flat, suggesting that all income groups benefited equally from growth, with the notable exception of the poorest 10%, who got worse off, and the richest 10%, whose consumption grew relatively fast. This is a significant finding for safety nets strategy, because it suggests – at least on the basis of the data for 2000-2007 - that the very poorest are those who are not benefiting from growth, and most likely to be in need of sustained transfers.18 Figure 4: The Impact of Economic Growth on Consumption by Poverty Class Growth incidence, Tanzania Mainland, 2001 - 2007 15 10 Consumption growth (%) 5 0 -5 0 10 20 30 40 50 60 70 80 90 100 Consumption percentiles Sources of Income: Livelihoods of the Poorest 89. As noted earlier, farming or fishing is the main source of income for more than 80% of households living below the poverty line. (See Table 2). However the incomes of Tanzanians, including the poor, are more diversified than in other subsistence economies in the region – likely reflecting the beginnings of commercialization and integration into the cash economy. 90. Despite the preponderance of farming, the poor earn almost half their incomes from informal off-farm activities and employment; the problem is that the returns to their off-farm activities are substantially lower than those of other Tanzanians (Table 9). 17 It is not clear that the value of own-production of crops, which represents a substantial share of the income of the poor, was accurately quantified in the 2006 HBS. The uncertainty also stems from the fact that the national accounts data implies higher incomes than does the HBS; and that households have accumulated substantial assets since the last survey, which is not reflected in commensurate income growth; (see, for example, discussion in Poverty Monitoring Group (2008) 18 The growth incidence curve for rural areas is noticeably closer to zero than for the country as a whole, suggesting that for most people living in rural areas growth has had a negligible impact on consumption; and again re-enforcing the argument for focusing o n rural areas in a safety net strategy. 11 Table 9: Average Household Income By Income Class and Source Agriculture Non-Farm Wages and Salaries Income Poorest 19,500 (51%) 10,900 (28%) 8,200 (21%) 2nd Quintile 26,200 (41%) 22,300 (35%) 16,000 (25%) 3rd 30,400 (32%) 43,900 (46%) 21,600 (23%) th 4 35,400 (28%) 54,200 (43%) 37,500 (30%) Wealthiest 43,200 (18%) 125,100 (53%) 70,200 (29%) Source: Drawn from HBS 2007, and Rapid Poverty Assessment, p.27; total monthly HH income in Tsh. 91. Nonetheless, the poor are twice as dependent on agriculture as the non-poor (Annex Table 1.1.1). The recent CFSVA survey found that households with below-acceptable levels of food intake (who are generally the poorest) tended to consist of either small subsistence farmers who do not grow cash crops (who constitute about 25% of the rural population), or those dependent on daily wage labour (about 9% of the rural population). (See Annex 1.1; Livelihoods). Consumption Patterns; Utilization of Education and Health Services by the Poor 92. Nearly all Tanzanians spend a majority of their income on food, with food accounting for about 60% of consumption even among the relatively well-off. What is worthy of note is the poor are more dependent on their own production of food than are the non-poor (Table 9)); but even the very poor purchase almost a third of their food from the market. It is also worth noting that both medical care and education account for a very small share of consumption, even among the very poor (typically only 2-3% of household expenditure), suggesting, a priori, that safety net interventions related to health and education spending are not likely to represent a significant part of the program; although catastrophic health expenses can place a major burden on the poor. Table 10: Consumption Patterns among the Poor, the Non-Poor, and the Poorest (Share of consumption accounted for by consumption item) Consumption Item Non-Poor Poor Very Poor Food - Purchased 42.6% 33.2% 30.3% Food – Not purchased 19.5% 33.7% 33.4% Medical 1.9% 2.0% 2.7% Education 3.3% 2.5% 2.8% Personal care 2.1% 2.0% 2.0% Fuel/a 8.1% 8.5% 8.7% Transport & Petrol 3.4% 1.9% 1.7% Telecoms 2.7% 0.9% 0.5% Source: Own calculations based on HBS data; Note: selected consumption items only. a/ for cooking and light. 93. The reasons for the low proportion of spending on health and education have in part to do with the fact that the poor (and almost all Tanzanians) have such low consumption levels that after accounting for the essentials of food and fuel there is little left, and the share of any other single consumption item is inevitably low; the fact that basic services (such as primary education) are largely free or low-cost; and that coverage is limited, and the poorest, who tend to live in more remote areas, have less access to services (such as hospitals) that would cost them money. 12 94. Nonetheless, with increased coverage of the education system, many more of the poor are now in school. Education participation by income class is fairly egalitarian, and following the introduction of free primary education, enrolment rates are fairly high (Table 11), averaging 84% nationwide, and 78% among the poor.19 The issues are that the poor are more likely to start school later than are the non-poor20, and less likely to complete it. Issues that might be amenable to tackling with conditional safety net interventions (see chapter 6) include encouraging students to start school at the appropriate age, encouraging girls to continue beyond Form IV (at which point many currently leave school), and to improve sporadic attendance. (See for example, Burke (2004) and World Bank (2008). Table 11: Use of Education and Health Services by Wealth Quintile 2007 School Attendance % 10-13 Yr. Use of Health Facilities /a Wealth Primary Secondary Olds Not Yet Any Quintile Started School Provider Public Private Poorest 78% 10% 26% 1.26 .85 .27 2nd 79% 12% 17% 1.40 .85 .35 3rd 84% 13% 11% 1.27 .82 .36 4th 89% 21% 5% 1.42 .96 .34 Wealthiest 91% 25% 2% 1.01 .62 .34 Source: constructed from Rapid Poverty Assessment (2009), Table 11, Table 4.6, based on HBS 2007 data. a/ Average no. of household members consulting health services. 95. Health status is uniformly poor – and somewhat worse among the poor than the non-poor; as is utilization of health facilities, although the empirical evidence does not suggest that the poor use health facilities much less than the non-poor (Table 11). There is continuing debate around the impact that health fees have of discouraging utilization - exemption and safety net options are discussed in Chapters 3 and 6. 2.5 The Geographical Distribution of Poverty 96. Poverty in Tanzania is concentrated in the rural areas. The overwhelming majority of the poor (about 84%) live in rural areas, and levels of poverty are far higher in the countryside than in towns (Table 12). 19 Lowest quintile Net Enrollment Rate; HBS 2007 and Rapid Table 4.1. 20 For example 26% of children in the lowest wealth quintile are reported as never having attended primary school; as opposed to only 11% in the middle quintile, and 2% among the wealthiest (Hoogeveen, World Bank 2008) 13 Table 12: The Regional Distribution of Poverty in Tanzania Region Incidence of Poverty % of the Poor Number of Poor Basic Food Below Below Needs Poverty BN Poverty Food Poverty Line Rural 34.6% 16.4% 84% 10.7 million 5.3 million Urban (not Dar es Salaam) 24.1% 12.9% 13% 1.6 million 874,000 Dar-Es-Salam 16.4% 7.4% 3% 474,000 212,000 97. While there has undeniably been an increase in urban poverty in recent years, and while the poorest in urban areas undeniably live in conditions of squalor, it is still worth highlighting the continued difference in consumption levels between urban and rural Tanzanians. Urban poverty is still nowhere near as deep nor as widespread as in rural areas: to be truly poor in Tanzania still means to be rural and poor. The focus of any safety net strategy, therefore, needs to be primarily on addressing rural poverty. 98. Geographically, poverty tends to be higher in the central band of the country (where there are fewer cash crops, lower rainfall, and less integration with urban markets), and in the drier areas of the far north and south (where people depend on grazing of livestock). It is worth noting, however (Annex 1.3) that regions with lower average incomes are not necessarily those with the highest incidence of poverty – suggesting that within some relatively well-off areas there are large numbers of households who are not benefiting from the general economic prosperity around them; while within some poorer areas incomes are relatively more evenly distributed. The implication is that geographical targeting will miss very large numbers of the poor. For example in 2001 (the last year for which reliable District-wise poverty data is available), focusing on only the poorest third of the country (as most programs currently do), would leave out about 64% of the poor, and 58% of the extremely poor - those living below the food poverty line.21 99. Note however that successive CFSVA surveys have found that the set of Districts where people have below-acceptable food consumption22change quite significantly over 5-year periods, suggesting that areas – like households – move in and out of poverty. The implications for SNs are that in some circumstances geographical targeting may make sense; but mostly for short-term interventions that provide intensified support to an area during a period of difficult years. This argues for interventions such as public works employment that can be expanded and contracted as needed. 21 Based on selecting the 7 Regions (out of 21) with the highest food-poverty headcount ratio; and applying 2002 HBS region-wise poverty rates and 2002 Census population estimates. See Annex table 1.3.2. 22 The reasons for this have not been investigated in any depth, but are thought to include a mix of changes in attributes (such as market and road integration); the shifting impact of drought; economic developments or innovations (such as the regional adoption of particular cash crops); and the impact of intensified food-security and transfer programs. 14 2.6 Food Insecurity and Vulnerability 100. Many poor Tanzanians are still subsistence farmers. They rely almost entirely on their own production of food grains. They have little cash income, so the depth of their poverty depends very much on how much they are able to grow in a given year on their own land, and how long it lasts them into the next year. 101. It is estimated that some 2 million Tanzanians are food insecure in any given year, and another 6 million are at typically at risk of falling into food insecurity if their harvest is inadequate, or there is widespread drought.23 The numbers vary substantially from year to year, depending on rainfall. The most recent Vulnerability Assessment survey24 found that 4.1% of rural households had poor food consumption (defined as having an almost exclusively cereal- based diet, eating vegetables only three days a week and pulses two days a week, with almost no animal protein), and a further 18.9% had only borderline food consumption.25 Figure 5: Caloric Consumption by Wealth Quintile Fig.5 - Caloric Consumption by Wealth Quintile 7000 Kcal per day (adult equivalent) 6000 5000 Caloric 4000 Consumption 3000 2000 Estimated 1000 Minimum Requirement 0 1 2 3 4 5 6 Source: Interpolated from PHDR 2009 Fig 50 p.149. 102. About 16% of Tanzanians consume less than the daily minimum requirement of calories. The question is to what extent this is due to generalized poverty and insufficient incomes, and to what extent is it due to food security factors, such as the availability of food, failure of their harvest, or poorly functioning food markets. To the extent it is the latter, food-based security nets may be an important part of the national strategy. 103. Most food insecurity is ultimately an issue of income poverty: if people have enough money - wherever they are in the world - they can generally buy food. However for Tanzanians in the bottom half of the income distribution, especially in rural areas, it is generally unlikely that they have the purchasing power to solve their food security problems through buying food from the market. 23 Annual FEWS/VAM assessments, 2002/03-2009/10. 24 Mainland Tanzania Food Security and Vulnerability Assessment; WFP/NBS, 2010 25 Defined as having an only marginally better diet – eating pulses, vegetables and fruit approximately one time more per week than poor consumption households. 15 104. The issue from a safety net point of view is whether solutions should involve food- security based interventions, such as transfers of food or assistance programs that improve the poor’s own production of food, as opposed to cash transfers. 105. Tanzania is generally self-sufficient in its staple crop – maize – but poor infrastructure in rural areas, high transport costs, and poorly functioning markets limit the internal distribution of food from surplus to deficit areas. 106. More importantly, and in common with many subsistence economies, the poor who live in these areas have little cash income, limiting the extent to which they can purchase food to offset deficits in their own production, and further constraining the development of functioning markets, due to the lack of effective demand in poor areas. One consequence of this is the very large seasonal swings in food prices that place a particularly high burden on the poor (discussed below). 107. The weak markets are in part a consequence of weak purchasing power; if the very poor had more cash income, there would be more traders operating in these areas, and the extreme variations in food supply and prices would be reduced. In designing safety net interventions, therefore, careful attention needs to be paid to the trade-off between providing food (which will still be needed in times of extreme shortage, or in isolated areas), and providing cash, which, if predictable and sustained enough, will help kick-start the functioning of local markets. Seasonality in Food Insecurity and Poverty 108. As in all rain-fed subsistence economies, the consumption of the poor depends very much on the time of year. Immediately after harvest, food is plentiful and prices are low. As the dry season progresses, stocks are used up, and just as the rains begin for the next year, food supplies are running down. Thus as rural households plant and await the next harvest, they have used up all of their food reserves, and there is little available in local markets to buy, resulting in a 4-to-5 month ‘hungry season’. 109. In Tanzania the coastal and northern areas benefit from two rainy seasons, so seasonal food shortages are less of an issue, and the hungry season typically only lasts 2-3 months. (see graphic below) Furthermore, some coastal and highland areas have considerable cash crops, and are better linked with urban markets, which both increase off-farm employment opportunities and the generation of agricultural cash income for the poor, so they are better-equipped to purchase food if they need it. 16 Bimodal Areas (Coastal and northern areas with two rainfall and planting seasons) Vuli Harvest Masika planting Hungry Season Masika rains Vuli rains Jan Feb Mar Apr May June Jul Aug Sep Oct Nov Dec Hungry Season Green harvest Msimu harvest Hungry season Msimu Dry Msimu rains Msimu rains Rains Spell Msimu prep and planting Unimodal Areas (Inland areas with a single rainfall growing season) 110. Typically the food harvested by a family lasts about 5-6 months in unimodal areas, and about 8 months in the bimodal areas26, although it lasts substantially less among households in the poorest livelihood groups (eg. 4 months and 6 months, respectively, among families primarily reliant on day-labour (see Annex 1.4). The graph below illustrates how dramatically families run out of food. Figure 6: % of Households with Food Reserves Remaining from Previous Harvest – By Month Fig. 6 % of Households with Food Reserves Remaining from Previous Harvest - by Month 100 (unimodal areas) 80 60 40 20 0 May J J A S O N D J F M Apr Constructed by the author; from CFSVA 2010; Fig. 24, p.54 The Poor: Net Buyers and Sellers of Food 111. In general the very poor tend to produce less months’ worth of food from their land, and thus face a longer, and deeper, hungry season, and have to buy more food from the market. There is no good country-wide data on the status of net sellers and net buyers of food grains by income27. Table 13 below shows the proportions for two sample districts, both of which are relatively food insecure. In Kilimanjaro, almost 90% of the poorest are net buyers of food, and the proportion falls as households get wealthier. In Ruvuma, on the other hand, more of the poor tend to be net sellers of food, and the percentage of households that are net sellers actually falls 26 Source: CFSVA, 2009/10; Table 10. 27 although the HBS shows that the extremely poor purchase slightly less of their food than the population as a whole, perhaps in part because of their limited purchasing power, and because they tend to be subsistence farmers . 17 as incomes increase (probably because the better-off have more diversified sources of incomes, and are less reliant on food sales.) Table 13: Net Buyers and Sellers of Maize Consumption Kilimanjaro Ruvuma Quintile (Northern Highlands) (Southern Highlands) Net Food Buyers Net Food Sellers Net Food Buyers Net Food Sellers (% of total) (% of total) (% of total) (% of total) Poorest 89% 11% 47% 53% Second 81% 19% 61% 39% Third 72% 28% 53% 47% Fourth 76% 24% 61% 39% Wealthiest 73% 28% 68% 32% Source: Sarris, Savastano and Christiansen (2006)FAO (reproduced in WB (2009) Seasonality in Prices 112. The poor suffer doubly by the seasonality of food supply: because of shortages, the time at which they need to buy food from the market is also the time of highest prices. 113. The seasonal variance in supply and demand for grains combined with the weak integration of markets leads to significant swings in prices. Figure 7 below shows the variation in price of maize over the past 6 years. Typically there is a ratio of high-season to low-season prices of almost 2 to 1. Furthermore, because of the weak integration of markets, increases in consumer prices do not necessarily translate into similar increases in farm-gate prices for farmers, so the medium-poor who might be net sellers of grain do not benefit commensurately. Anything that can be done to smooth this variation in prices could result in large welfare gains for the poor, and is potentially an important part of a safety net strategy. Figure 7: Seasonal Movements in Maize Prices 2001-2007 Deviation from trend 40000 Maize price per tonne 35000 Linear trend 30000 25000 20000 Tshs 15000 10000 5000 0 2000/01 2001/01 2002/01 2003/01 2004/01 2005/01 2006-01 2007-1 -5000 -10000 114. Note that the variance is less in some areas than others. Between January 2009 and January 2010, for example, maize prices increased by 65-80% in some Districts, while others experienced no increases, or even price declines28, suggesting that a large part of the problem is the lack of integration of markets. 28 Source: 2010 RVA p.11 18 115. Seasonality in Labor: There are large periods of time when able-bodied poor do not have enough work to do, and these points to the obvious use of a public-works employment scheme as one of the main safety net interventions. The evidence shows that off-farm employment does not pick up to compensate for the drop in agricultural work demands on the farm during this slack season (Fig.8), so the opportunity is there for productive employment on PWP programs. The drawback is that the time of greatest household need (the November-February hungry season, previous graphic) is also the time when farmers are busy with on-farm planting and cultivation activities (figure below), so payment has to be made either later in the season for work done during the slack period, or systems developed that encourage households to save the payments until they need the money (or food) in the hungry season. Figure 8: Seasonality in Labour Use & Livelihood Activities (% HHs Engaging Activity by Month CFSVA 2010) 90 80 70 60 agriculture small business % HHs 50 livestock 40 commerce/business daily w ork 30 20 10 0 Feb Jan March June Oct May July Nov Dec Sept April August Source: CFSVA An Aside on Food Inflation and the Poor 116. The prices of almost all basic food stuffs increased dramatically in the past five years, and particularly in the period 2007-09 (Table 14), placing an additional burden on the poor. This was in part a result of regional shortages in eastern Africa, in part due to international food and fuel price increases, and in part due to slow growth in food production. Table 14: Estimated Increase in Prices of Some Basic Foodstuffs 2001-07 and 2007-09 Commodity Price Increase Price Increase Price Increase 2007- 2001-2007 2007-2009 (Rural) 2009 (Dar es Salaam) Rice +87% +42% +50% Maize Flour* +111% +56% +73% Vegetables** +129-166% +3% +16% Meat*** +141% +34% +20% Cooking oil/Fats**** +107% +18% +49% Sugar +112% +4% +28% Sources: Own Calculations, based on 2001-07 Table 6.5 p.36, Rapid Poverty Assessment; 2007-09; Tables 36-38, pp 71-73 National Panel Survey 2008-09 Preliminary Baseline Report .* ‘Maize’ only 2007-09; ** Onions and tomatoes 2001-2007; *** ‘beef’ 2001-07; **** ‘fats’ 2007-09 19 117. While the major price inflation of 2008-09 appears to have abated, the poor suffered a significant consumption shock, from which it appears unlikely that they have fully recovered. Qualitative studies confirm that many respondents have reduced food intake – either reducing the number of meals, or substituting lower-valued foods, dropping items like meat and milk from their diets, due to affordability problems.29 It would seem that the increased demand for food from the growing urban population is contributing to price pressures, which may feed through into welfare losses for those of the rural poor who are net purchasers of grain; and even for those who are net sellers, since market rigidities hinder the pass-through of consumer price increase to farm-gate prices. 2.7 Nutrition 118. Malnutrition is widespread in Tanzania, although not quite as severe as in other low- income countries of the region.30 Approximately 38% of children under five are stunted – exhibiting low height-for-age - and about 13% are severely stunted. (Stunting reflects a failure to consume adequate nutrition over a number of years, and is often associated with poor overall economic conditions). About 3% of children are wasted, signifying acute malnutrition. 119. There is relatively little relationship between areas of food insecurity and areas of high malnutrition, suggesting that the problem is not so much one of insufficient food, as of poor feeding practices. Areas of cereal surplus – mostly in the south and west31 - are also areas with relatively high rates of malnutrition; which is linked more to feeding practices (for example stopping breastfeeding too early), diet (involving a heavy reliance on cereals that are low in energy and nutritional value), and health status (diarrhoeal diseases and parasitic infections, which affect appetite and the body’s ability to metabolize food). 120. There is also a fairly weak relationship between malnutrition and poverty status in Tanzania. As shown in Table 15, levels of malnutrition are about equal among the bottom 60% of the population. Studies have shown that the income elasticity of nutrition is low (in the range of 0.25-0.5), meaning that a 10% increase in incomes leads to only a 2.5-5% decline in malnutrition, so income growth alone will not solve the problem. If Tanzania were to meet the MDG goal of halving child malnutrition, income growth will have to be complemented by large- scale program interventions. Those with the highest benefit-cost rations include food fortification, mineral, and vitamin provision, and improved pre-natal care and care and feeding practices for young children.32 29 See for example papers by Higgins; daCorta; and also Kessy. 30 See for example World Bank (2008) p.71; and Annex Table1.1.5 31 ref. UNICEF/REPOA (2009) 32 See “Tanzania: Advancing Nutrition for Long-Term Equitable Growth” World Bank/UNICEF/ (2007); and Alderman, Hoogeveen (2005). 20 Table 15: Child Malnutrition by Income Group Wealth Stunting Wasting Underweight Quintile (Height-for Age) (Weight-for-Height) (Weight-for-Age) >3 s.d. > 2 s.d. >3 s.d. > 2 s.d. >3 s.d. > 2 s.d. Poorest 17.6 44.9 0.5 3.1 4.9 24.8 Second 15.5 42.8 0.3 3.5 4.7 25.8 Third 13.6 40.9 0.3 2.5 4.3 23.3 Fourth 10.3 37.5 0.5 2.9 3.0 20.0 Wealthiest 3.9 15.7 0.2 2.9 0.6 12.2 All Tanzania 12.8% 37.7% 0.4% 3.0% 3.7% 21.8% Source: DHS 2005 121. Most damage from malnutrition occurs in the first year or two of life and has lifetime effects on productivity and well-being. Evidence from Tanzania shows that improved nutrition increases years of schooling and school outcomes, and can raise long-term productivity (by 5- 17%) and lifetime earnings (by an estimated 12%)33 Addressing early childhood malnutrition thus has long-term impacts because it can break the poverty-malnutrition cycle. Safety net interventions might potentially be connected with nutrition through linking conditional transfers to participation in nutrition programs addressing food fortification, or behaviour change training (see discussion in Chapter 6). 2.8 Poverty among the Most Vulnerable - Specific Groups of the Poor Orphans and Most Vulnerable Children 122. In addition to the generalized poverty experienced by many children in Tanzania, there exists a large sub-class of orphans, many of them created by the death of parents due to HIV/AIDS, and many of whom live in conditions of abject poverty – either in households with no adult, or living with an elderly relative - generally grandparents – who lack the skills, energy, and resources to adequately feed and care for them. 123. There are about 230,000 children who have lost both parents, and about 2 million who have lost at least one parent, many of whom are consequently abandoned, or at risk of abandonment34. While orphans are a significant part of the poverty problem in Tanzania, and the conditions under which they live can be truly horrendous, Tanzania has – quite rightly - adopted the concept of ‘most vulnerable children’, rather than focusing on orphanhood alone. This recognizes that not all orphans are poor (they are absorbed into functioning, and sometimes relatively prosperous, families), and that there also exist many children who are not orphaned, who are nonetheless extremely badly off. 124. The definition adopted in Tanzania for ‘most vulnerable children’ is: - Children living in child-headed households; 33 World Bank (2009) 34 Evidence across HIV/AIDS affected countries shows that children who have lost one parent, especially if it is the mother, are at considerable risk of abandonment; in Tanzania the MVC registration system had found 26% of MVCs to be abandoned (MVC MIS Update presentation; DoSW, 2010) 21 - Children living in an elderly-headed household with no adult aged 20-59 years present; - Children with both parents deceased; - In rural areas: children with one surviving parent living in a house with very poor quality roofing (mud or grass) and children with a disability living in similarly poor conditions; - In urban areas: children with one surviving parent living in a house with poor roofing (mud or grass) or walls, or without a toilet; and disabled children living in similar conditions. 125. By this definition there were an estimated 900,000 to 1 million MVCs in Tanzania in 2010 (Table 16), representing about 5% of the child-aged population. Table 16: Estimated Numbers of Most Vulnerable Children 2010 Rural Urban Total No. of children in child-headed households 140,656 59,527 200,091 No. in elderly-headed households 294,106 33,408 327,514 No. of double-orphaned children 162,213 68,043 230,256 No. Of disabled children 185,177 33,237 218,413 Total No of Most Vulnerable Children 825,454 218,643 1,044,096 Source: NCPA; Projected number of vulnerable children 2010, Appendix VI, p.62 126. With 36% of the population living in poverty anyway, and 16% below the food poverty line, it seems reasonable to ask how different the conditions of these children are from those of poor children more generally. Estimates made by Lindboom, Leach et al suggest a gap in consumption of between US$ 17.50 and $49 per year between MVCs and those living close to the poverty line, depending on the age of the child. (See Table 17)35 Table 17: Estimated Consumption Gap Between Children Living in Households below 30% of the poverty line, and those living at about the Poverty Line Expenditure Gap Approximate Approximate Age (per child; 2006 Tnz Sh. Per annum) US$ Equivalent Number of MVCs Non-Food /a Food Total (per child p.a.) 0-6 Years 2,381 18,348 20,790 $ 17.50 181,000 7-14 Years 7,225 31,281 38,506 $ 32.00 481,000 15-17 Years 12,888 46,138 59,026 $ 49.00 266,000 929,000 a/ represents an approximate average of urban and rural costs, which are slightly different for non-food items; see Table 1.5, p. 11, Lindboom, Leach, et.al. (2007) Persons Living with HIV/AIDS (PLWH) 127. The overall rate of HIV infection in adults in Tanzania is about 6% (2007-08 National HIV/AIDS survey), thus the AIDS situation is not as bad as it is in some other countries in sub- Saharan Africa; although levels rise to about 10% in some districts, and overall this still means about 1.1 million persons are living with HIV/AIDS. 35 These appear to be based on a somewhat arbitrary estimation of MVCs as consuming below 30% of the poverty line consumption levels. 22 128. The link with poverty status is not clear. Certainly as a result of their incapacity and illness, many people are not able to work or fend for themselves; but at the same time AIDS tends to be, if anything, a disease of the non-poor. The recent National HIV/AIDS survey found no strong relationship between poverty indicators and HIV/AIDS status, and if anything, HIV prevalence tends to be higher among better off (for example prevalence is 8.1% in the richest quintile, and only 4.6% in the poorest), and significantly lower in rural areas, where most of the poor live.36 129. While some PLWH are very badly off – living on their own, and unable to adequately feed, clothe or house themselves - others are living with their families, who can in some cases care and provide for them well, and in some cases cannot; while yet others are receiving treatment and living full productive lives. It is thus difficult to generalize about the impact of AIDS for safety net purposes. We know that there are individuals who desperately need assistance, but in the absence of case-by-case data, there is no way of saying with any certainty how much assistance is needed. In general the way this problem has been handled is – quite correctly – to rely on community targeting, and agencies working with HIV/AIDS sufferers, to identify the individuals that most need assistance. The Elderly 130. There are some 2 million people in Tanzania over the age of 60, representing about 5% of the population.37 . Concern with poverty among the elderly has been rising (see for example HelpAge et.al. (2010)). However, while the elderly are undoubtedly more affected by illness and disability than other Tanzanians, poverty rates among them are not significantly different from among the population as a whole. (Table 18)38. Table 18: Poverty Among the Elderly: Headcount Ratio by Age Group Below Food Below Basic Needs Poverty Line Poverty Line Children < 14 18.4% 36.3% Working Age Adults (15-59) 15.1% 30.9% Older People (60+) 15.3% 33.0% All Tanzanian 16.1% 33.6% 131. There is substantial debate at the moment about the advisability of introducing a universal old-age pension. This has been triggered in part by concern with inter-generational 36 Tanzania HIV/AIDS and Malaria Indicator Survey 2007-08; TACAIDS, 2008; see Table 9.4 p.116. (8.7% urban prevalence; 4.7% rural). 37 The single largest group of the elderly are between the ages of 60 and 65, only about 3% of the population is older than 65, and about 2% older than 70. The number over 60 is projected to grow to 3 million by 2025, but to decline slightly as a share of the population. 38 Note that the HBS collects data by household, so it is difficult to assess intra-household distribution of consumption – we do know that the very poor tend to live in larger households (Fig.3), which may contatain more elderly people, and HelpAge estimates poverty rates are about a fifth higher than average in HHs containing elderly people; however the HBS data (Tasble 19) show that households consisting of only elderly people have substantially lower poverty rates thasn the population as a whole. 23 poverty traps associated with poor grandparents raising orphans, and the successful experience with the KwaWazee pilot project; coupled with a perception that traditional family support mechanisms for the elderly are breaking down. 132. There seems little doubt that poverty rates among households with children but no working age adults are very high (Table 19). While selective support for this group would seem to be justified, many of the elderly are absorbed into non-poor extended families, and, given the overall poverty rates among the elderly, the case for providing universal support would appear to be weak (see discussion in Chapter 5) Table 19: Poverty Rates in Households with Only Children and the Elderly % of Population Poverty Headcount Children and Elderly Persons Only 1.5% 45.4% Elderly Persons Only 1.1% 17.2% All Households 100% 33.8% Source: Table 20, p.91 PHDR 2009; based on HBS 2007 data. People with Disabilities 133. An estimated about 6% of the population suffers from some form of disability (NBS, 2009)39. The Disability Survey shows that of these, about a third of these people are severely enough disabled that it significantly affects their functioning. Blindness is the most common disability, accounting for about 3% of the population; and about 2.4% of the population are mobility-impaired (there is overlap between these groups), of whom about 300,000 people are significantly mobility impaired, representing a bit less than 1% of the population. What the data do not tell is what proportion of these people with disabilities are adequately looked after within households, and which are alone, or in extremely poor households, and might need safety net support. 134. About half of the people with disabilities are married or living with a partner, and 90% report receiving support and assistance from family members, but there is no information on how much support they receive. Therefore it is hard to estimate what proportion require safety net assistance, but if it were 50% of those reporting significant impediments, then the number would be something like 400,000. Note however that the incidence of disability is much higher in those 60 and older40, so there is a lot of overlap between these 400,000 and the potential target group of elderly, discussed above. 39 National Disability Survey, 2009 40 30% of those aged 60 and above are disabled, as opposed to just 6% of the population as a whole. 24 Table 20: Summary Data on Disabled Population 2008 (,000s) Level of Seeing Hearing Mobility Self-Care Cognition Communication Difficulty Some 917 408 623 193 273 131 A Lot 214 131 277 59 121 69 Unable 38 68 58 73 63 53 Total 1169 607 958 325 457 253 As % of total Population Some 2.3% 1.0% 1.5% 0.5% 0.7% 0.3% A Lot 0.5% 0.3% 0.7% 0.1% 0.3% 0.2% Unable 0.1% 0.2% 0.1% 0.2% 0.2% 0.1% 2.9% 1.5% 2.4% 0.8% 1.1% 0.6% Source: Own Calculations – based on National Disability Survey NBS, 2008; Table 3.5, p.47 2.9 Informal Safety Nets and Transfers 135. Finally, in thinking about the role of public transfers to the poor, it is important to bear in mind the role that informal private safety nets play – that is, support provided by families or communities under traditional exchange/transfer mechanisms. Effective private transfers (to the extent they exist) should not be displaced with public ones, and the public programs should not undermine traditional, informal coping mechanisms. Examples of such mechanisms might include extended families taking in orphans, religious or community groups providing help to impoverished persons, or community insurance funds. 136. There is no rigorous study of the role of informal safety nets on Tanzania. 41 The limited evidence from micro studies and anecdotal evidence suggests they consist mostly of funeral societies, and limited help from mosque or church associations. The main source of informal transfers in Tanzania is remittances, either from members of the same family who have jobs in town (such as civil servants); or seasonal remittances from members of the family who migrate temporarily in search of jobs. The former tends to affect mostly non-poor households, and the latter is really more of a livelihood strategy – moving to find work elsewhere - than an informal safety net transfer. 137. The empirical data shows that such transfers are not very significant in the incomes of the poor. The HBS data (Table 21) in fact show that transfers and remittances are substantially smaller, and represent a somewhat smaller share of income among poor households than among the non-poor. Table 21: Informal Transfers by Income Group (HBS, 2007) Average Transfers Share of % Reporting T & R as Income Group and Other Income Main Source of Income Receipts/a Non-poor 5,570 13.9% 1.8% Poor 1,448 11.0% 2.1% Ultra-poor 1,118 12.8% 2.6% Source HBS data and author’s calculations. a/ Tsh per month per household. 41 See for example, Dercon; de Weerdt. 25 138. This is not surprising, when one thinks about it, and is consistent with experience worldwide, which suggests that transfers tend to take place between members of similar income and social groups (that is, between the non-poor and non-poor, and the poor and the poor) and since the poor have much less to give, and are generally in difficult circumstances themselves, the value of transfers among this group is low. (See Alderman, 2010). 139. More fundamentally, if non-formal transfers were truly playing a significant role, the very poor would not be as badly off as they are; so the group targeted with safety net programs - the chronically poor - are in general, by definition, not benefiting sufficiently from informal safety net mechanisms. 140. It should be noted that that many shocks (e.g. drought, seasonal food price rises, flooding) tend to be co-variate, affecting all members of the community at the same time, so informal transfers are often less helpful (because everyone is poor at the same time). They are more helpful in cases of idiosyncratic shocks – such as illness, accident, sudden loss of employment, or death of a breadwinner - in which case extended family, community, or religious organizations can rally around the affected household and provide support. 141. Nonetheless, it is quite possible that some informal safety net systems work very well for particular groups, and in particular circumstance (the example of orphans being taken in be extended families is the most obvious); and in designing safety net programs it is important to do specific analytical work to understand them, and design around them. Box 2: A Note on Poverty and Safety Nets in Zanzibar About 1.1 million people, or 3% of the population, live in Zanzibar, which has unique cultural and historical characteristics, and considerable autonomy in managing budgets and programs. Almost all of the transfer programs that operate in mainland Tanzania (discussed in Chapter 3) also operate in Zanzibar, and by and large the same strengths and weaknesses apply. The poverty profile is not very different in Zanzibar than for Tanzania as a whole – for example about 13% of the population live below the food poverty line, as opposed to 16% in mainland Tanzania (HBS –as cited in ILO PER p .55); although extreme food insecurity is less (the CFSVA rated 96% of the population of Zanzibar as having ‘adequate’ food consumption, as opposed to only 77% in the mainland.) The main distinction that probably affects safety net programming is one that is difficult to measure: the homogeneous social structure and the preponderance of Muslim social and religious institutions that help support the poor. Zakat, or ‘alms for the poor’ is the Islamic principle of giving a percentage of one’s income to charity. Waqf is the withholding of property in order to use the revenues for philanthropic purposes, and Sadaqat is a voluntary charitable act. There is no good data on the scale of these activities, although the one existing study (ILO, Zanzibar 2010), concluded that the total amounts were small relative to poverty needs. Nonetheless, in designing the Zanzibar activities of safety net and transfer programs, it is important to take these unique circumstances into account, and ensure that traditional support mechanisms are not being displaced or undermined 26 CHAPTER III: EXISTING TRANSFER AND SAFETY NET PROGRAMS 142. There are currently a large number of transfer programs, many of them very small, and many covering only limited areas of the country. This chapter reviews the largest of the existing ones, along with some small innovative programs that might provide lessons for future scaling- up. Table 22 lists the main transfer programs operating at the moment. Table 22: Summary of Main Existing Transfer Programs in Tanzania (On-going in 2009/10; Expenditures and Benefits per annum) Direct Estimated Average Program Expenditure Beneficiaries Coverage Transfer per Agency (annual) (annual) (annual) Participant Safety Net Programs Aimed Primarily at the Poor Most Vulnerable Children $ 45 million 570,000 570,000 n.a. DoSW Program (est) National Food Reserve $ 19 million 1.2 million 1.2 million Tsh. 18,000 MAFC/ Agency/e (est) PMO School Feeding $ 6.2 million 220,000 /b 220,000 Tsh 40,000 /c WFP/M oE Food-for-Assets $ 2.9 million 54,000 272,000 Tsh 65,880 WFP Public Works Program $ 3.3million 12-25,000 60-125,000 Tsh 90,000 TASAF Other Transfer Programs Vulnerable Groups $ 6.4 million 18,000 18,000 Tsh.1.3 TASAF Program million / d National Agricultural Input $ 69 million 1.5 million 7.5 million Tsh 65,000/a MAFC Voucher Scheme Author’s calculation; Notes: a/ Cash value of voucher, actual benefit to household of maize produced is about 2-3 times higher. b/ in process of expanding to 600,000. c/ Actual value to beneficiaries yet to be calculated; 40,000 based on cost of $31 per student p.a. d/ Represents a long-term grant to invest in income-generating activities, rather than a transfer as such; average value of the transfer is unknown; e/ based on est. 12 kg/person/month, for 5 months, value at 350 Tsh/kg. 3.1 Most Vulnerable Children (MVC) Program 143. The MVC program is the largest transfer program aimed at the poor, it provides transfers to support orphans and other vulnerable children42. It currently reaches about 600,000 children annually, at an estimated cost of US $45 million.43 144. Most of the support consists of in-kind transfers, in the form of items such as such as school supplies, clothing, and health service cards. In only a few cases are food transfers 42 MVCs are defined as outlined in Chapter 2 (Section 2.8, p.20) 43 Estimate only missing data on Government and UNICEF financing 27 provided. There is also a large capacity-building element to the program, to develop community institutions to provide support for vulnerable children. 145. The program is operated by the Ministry of Social Welfare. Financing comes mostly from PEPFAR and the Global Fund, as part of global effort to address HIV/AIDS. It currently operates in some 85 Districts out of 140, but efforts are underway to expand coverage to the whole country. 146. The MVC program grew out of the National Costed Plan of Action (NCAP) which developed a national approach, and identified some 900,000 potential beneficiaries, representing about 5% of the child population (see Chapter 2). 44At present some 746,000 individual children have been identified as being eligible and about 586,000 have received some form of benefit.45 Table 23: Costs, Financing, and Coverage of the MVC Program 2008/09 Est.No. of Beneficiaries /a PEPFAR $25.2 million 290.000 Global Fund Est. $ 14.5 million 235,000 UNICEF n.a. 56,109 Government of Tanzania n.a. n.a. Estimated Total $45 million (est.) 570,000 a/ MVC registered as having received at least one form of basic support (Annual Update December, 2009, time period not clear). 147. We do not know the true value to the beneficiaries of the transfers they receive. The vast majority (about 80%) receive either school uniforms and/or scholastic supplies, or Community Health Fund cards (which provide a family with health coverage for a year, and cost about Tsh 10,000 (US$6.70)), while a much smaller proportion (about 10%) receive help with housing and/or bedding, mattresses, and the like; and even fewer (about 6%) receive food rations, or – in the case of the very young – supplementary feeding.46 148. Targeting and Implementation. The program is administered by the Ministry of Social Welfare, and implemented mostly through two large international NGOs (PACT and Family Health International), which channel funds to a network of smaller agencies and community organizations who actually deliver goods and services. 149. Funds are allocated amongst Districts on the basis of estimated need. The eligibility and priority needs of individual children are assessed by village committees, with follow-up visits by trained facilitators, who are often social welfare officers of the MoSW. Some funds are channelled through these village groups, but primarily goods and services are delivered by a large number of smaller local and international NGOs, many of which cover only certain geographical areas, or deliver only a certain kind of support (for example school supplies or uniforms, skills training, or forming women’s savings and investing groups). A potential problem with this approach is that the benefits being delivered are dependent on the policies and 44 Pilot programs based on intensive community-based assessment of eligibility in selected districts found eligibility levels of 5.3% of the child population – confirming the order-of-magnitude estimates in the NACP. 45 Based on NCPA Implementation Update for December 2009. Note PEPFAR review reports higher number of beneficiaries reached than implementation update – awaiting data from MoSW to finalize. 46 Note: based on a sample of Global Fund beneficiaries; there is not good data on benefits for program as a whole. 28 priorities of the particular NGO involved, and may not be coordinated across beneficiaries or types of support. 150. There has been no rigorous evaluation of the program, and because implementation is disbursed among many different NGOs, with differing levels and types of support, it is difficult to get a clear picture of performance. One area of concern is that beneficiaries often receive only once-off support, in the form of school supplies or clothing, when it would seem that for many of them – the orphaned, the abandoned, those living in child-headed households - a continuous stream of transfers is needed until the time they are able to earn a living for themselves.47 151. Early reviews48 noted that support was small in relation to needs, and often ad hoc, inconsistent and unpredictable – depending on funding availability, and the sector priorities of the NGO delivering it. 152. An evaluation of the program prior to scaling up (Linebom et al (2007)) noted that the costs of items being provided far exceeded the norms for spending on these same items among children in Tanzania in general; and the costs per beneficiary – at least at that time – were very high compared to total household spending per child among poor families as a whole. Costs remain high, in the order of US$ 80 per beneficiary (or 75% of the poverty line income), of which only a small proportion represents the value of actual transfers to MVCs This is particularly worrying since the package of benefits does not usually include food – the largest share of identified needs of orphans and MVCs.49 153. A register of children has been established, and while data on poverty status of beneficiaries is not available, the general sense of those involved with the program is that the community-targeting system is working well at identifying and reaching the most vulnerable children. One problem is that large numbers of children have been identified, and limited resources are available to respond to the many needs identified50, as a consequence implementing agencies have had to carry out a further assessment of children in order to effectively target the limited resources available. 154. Commentary. The program appears to have had success in identifying what are usually a difficult-to-reach set of beneficiaries. Community targeting is the appropriate mechanism, given the need to distinguish MVC from poor children more generally; the fact that not all orphans are necessarily poor, and that there are many non-orphans who are worse off. The targeting has cost an estimated $70,000 per District to set up (or about US$ 6 million for the 60% of the country covered; equivalent to $10 per beneficiary); although it would be good to know what the recurrent costs of sustaining the system will be. More generally, it is unfortunate there has not been a rigorous evaluation of the program. 47 In response to this concern the program is investing more in income-generating and community-strengthening interventions. 48 Leach et.al. (2007); and Musoma rural review. 49 The scaling up needs assessment, for example, estimated Tsh 30 billion out of the 37 billion estimated to be required to support MVCs would be for food; whereas the MVC program delivers very little food to beneficiaries. (Ref Lindeboom, Mhamba, et al (2007)) 50 Sharing the Lessons: Tanzania’s National Orphans and Vulnerable Children Program under PEPFAR I 29 155. There are some obvious areas of concern: the high unit costs, the pastiche of once-off support instruments, and lack of evidence regarding the impact on the consumption and welfare of MVCs. Finally, the MVC program is only partially a transfer program, and it is clearly highly dependent on the continued inflow of AIDS-related donor funding. Nonetheless, it has invested substantial effort in identifying and registering a large body of individuals who will have to be beneficiaries of any safety net program in Tanzania, and appears to have developed a functioning community-targeting mechanism. 156. There is a consensus among those involved in orphan-related programs that Tanzania has done an exemplary job in defining MVCs (as opposed to just orphans), and in developing a functioning community-based registration and targeting system. Given the amounts invested it would seem sensible to retain the core of this system, to adjust levels of support, and to critically evaluate whether orphans and MVCs should receive more continuous support, in the form of a more coherent package of goods and services, or regular cash transfers, sustained over a period of years. Finally, consideration should be given to expanding the same community-targeting and transfer system to include the very poor elderly and disabled, who need similar types of individual targeting and sustained transfers. 3.2 Food Subsidies – The National Food Reserve Agency (NFRA) 157. During times of shortage food is released by the National Food Reserve Agency (formerly the Strategic Grain Reserve). The majority of grain (90 % in the 2010 season) is sold at a subsidized price; a proportion is distributed free to the most vulnerable, while some is released at commercial prices, in order to increase aggregate supply and put downward pressure on prices. 158. The extent of the subsidy is large; maize is currently sold at Tsh.50 per kg, compared to a market price of about Tsh.350/kg; each beneficiary is eligible for 12 kg per maize per month51 representing a transfer of about Tsh. 3,600 per month, or about 30% of the rural food poverty line. 159. The amount of subsidized grain distributed under the program each year depends on need, and on the ability of Government to finance purchases and subsidies to the NFRA52, but is substantial: in the past year (2009/10) 85,424 mt of grain was distributed , reaching an estimated 1.4 million beneficiaries. 51 There are two releases per year; typically each beneficiary household receives 2-3 months’ worth of food /release. 52 Total capacity of the reserve is 120,000 mt., although it has never reached that level of stock. 30 Table 24: Operations of The NFRA/SGR (Maize Distributed and Beneficiaries) Subsidized (mt.) Free (mt.) Total (mt.) Beneficiaries (Tsh/person) 2009 April 19,438 2,166 21,604 720,000 October 51,066 5,764 56,740 1.9 million 2010 April 17,000 11,684 28,684 956,000 Average 2000/01-2009/10 54,900 915,000 (est.) Estimated Value of Benefit per Beneficiary (2009/10) /a Tsh. 18,300 ($13.10) Estimated Cost per Beneficiary/b Tsh.16,100 ($11.50)/b a/ 2009/10; based on average maize price of Tsh 350/kg,; distribution of 60 kg.per beneficiary ; b/ very rough estimate based on 2009/10 budgeted expenditure; note actual costs may differ considerably, see discussion in text. 160. Implementation and Targeting: The day-to-day operations of the NFRA are managed by the Ministry of Agriculture and Food Security (MAFC), while the Disaster Management Department in the Prime Minister’s Office makes the policy decision to release food for any particular intervention. The release is based on assessments by the Government’s disaster relief committee, and distribution of food to beneficiaries is managed by local government through District Councils. 161. The program is targeted geographically, operating in 72 Districts (out of a total 142) in the last year. The area covered varies substantially from year to year, depending on the severity of food shortages, and the amount of grain government has in the reserve. Food insecure Districts are identified by the MAFC, and verified through a rapid assessment by the Department of Disaster Management and WFP. 162. Within Districts, households to receive subsidized or free grain are identified by village committees, and their eligibility confirmed by local government staff. There is no good data on the accuracy of targeting. Anecdotal reports suggest that while the poor and vulnerable tend to be targeted, there is a tendency for village committees to spread the food more widely, in order to maintain social cohesion, resulting in smaller benefits and greater coverage. Survey data from the CFSVA also show that rural households receiving food distribution benefits are spread fairly evenly over wealth quintiles. (See Table 32 at end of this Chapter) 163. Food subsidies through the NFRA represent one of the largest safety net transfers in Tanzania at the moment – costing an estimated $19 million in the most recent year53 . Given the scale of the NFRA, it is important to bring it into the discussion of safety net interventions, and coordinate its operations with other transfers to ensure targeting effectiveness, and to carefully assess the extent of inclusion errors. 53 Based very roughly on 2009/10 releases – rough estimate based on Tsh 300/kg. purchase price, and revenues approximately offsetting distribution costs; note budget costs in 2009/10 of Tsh 20.5 billion (about US$15 million); excluding local government costs; but represent transfers to NFRA from MoF in the year; not necessarily direct costs of benefits delivered in that year. 31 3.3 School Feeding Program 164. The ‘Food-for-Education’ program has been feeding about 220,000 children in 350 primary school, at an annual cost of about US$ 6.5 million. It is in the process of being expanded to cover 600,000 students (7% of all primary students), at an estimated annual cost of US$19 million. The program is financed primarily by WFP, which provides the food distributed, and covers about 84% of the costs.54 165. Each child receives a morning snack and lunch, for an average of 194 school-days a year55. The transfer has a caloric value of 718 Kcal, equivalent to about 40% of the minimum daily food requirement. The principal justification for the program is presented as much, or more, in terms of encouraging school attendance and improving educational performance, as it is a transfer program. 166. Nonetheless, the transfer represents a substantial proportion of per capita household income for very poor families – and may be significant if a family has several children receiving the benefit. The average cost of providing the meal is estimated at 16 cents US per day, or about US$31 (Tsh 40,300) per student per year. The value of the benefit to the household is estimated to be about Tsh.21,700 annually for each child they have receiving the school meals.56 167. Targeting and Implementation: The program is implemented by WFP, the Ministry of Education and local governments. The Government has developed a policy paper on school feeding to guide institutionalization of school feeding. The intention is for WFP to eventually phase out, and hand over the program to government. At the moment however the program relies almost exclusively on WFP for financing. 168. The school feeding program has been targeted at 16 of the most drought-prone and food- insecure Districts, based on the Vulnerability Assessment. Within the Districts, selection of wards or divisions is supposed to be done by district authorities on the basis of poverty and educational attainment indicators; but as a 2009 assessment notes, there is no evidence as to whether they applied these criteria. 57 There is no targeting of individual students within the schools, presumably because this was judged to be too divisive, and/or too difficult to implement. 169. There is no evaluation that would allow us to judge whether the program benefits primarily the poor, the very poor, or the non-poor; although the CFSVA data suggests that the benefits are concentrated in the second-lowest wealth quintile (see Table 32), rather than the poorest. A review in 200858 found that children in participating schools showed slightly better 54 Based on data in WFP Country Program 2007-2010 Annex III 55 Full school year; it is not known how many days meals are actually provided (in many countries it is less than the whole year); average attendance in school feeding schools is about 81% (see table 25) 56 Assuming the child receives meal all 194 days of the year ; about 20% less if average attendance applies. 57 WFP Evaluation – WFP/MOEVT (2009) 58 “Report on the Impact Assessment of the WFP-Supported Food-for-Education Programme in Tanzania”; Prepared for WFP and MoEVT. 2009 32 educational performance and attendance than in non-participating schools; but the differences were not very significant. (Table 25) Table 25: Performance of Food-for-Education and Non-FFE Schools and Students Indicator FFE Schools Non-FEE Schools All Primary Schools % Change in Enrolment (2000- 51% 53% 39% (2002-07) 2007) Drop-Out Rate (2007) 1.3% 1.5% 1.0% (2007) Mean Attendance Rate 80.9 79.5 n.a. Average Pass Rate: Grade IV National Examinations Male 78.7% 81.4% 85.3% (2008) Female 77.2% 76.2% 84.4% (2008) Grade VII National 38.8% 33.1% 54.2% (2007) Examinations Source: Drawn from WFP/MoEVT (2009) 170. Reports found that the indicators (and differences) vary from year to year (see MOEVT/WFP (2009)), and while an effort was made to identify similar schools, the samples are not controlled for income, parental achievement, or quality of educational inputs. Nonetheless the results showed some consistent – if only slightly – better outcomes in schools with school feeding; especially in the Grade VII exam results, and in attendance, which showed less seasonal variance in the FFE schools, perhaps suggesting that children were being withdrawn for farm labour less. 171. As with all school feeding programs, there is the risk that parents reduce meals at home because of the expectation of feeding at school (see Grosh et al (2009)), but the transfer nonetheless represents a net gain to the household. In caloric terms it represents about 40% of minimum food requirements. The cost per student is about two times the estimated annual value to the child’s family of the food transferred. While this does not account for the full value of the food-supplement provided, and does not include any quantification of the schooling benefits, it does suggest that the educational benefits would have to be quite substantial to justify the high costs as a transfer mechanism. 172. It should be emphasized that the FFE is intended primarily as an education intervention, rather than as a safety net transfer. While it has the attraction of achieving both objectives at once, it is a relatively expensive way of trying to induce behaviour change (encouraging attendance), while as a transfer mechanism it suffers from large inclusion errors. A more effective way might be to provide take-home rations to a smaller sub-set of households in need. 173. Even with expansion, coverage is still limited; to expand the program nationwide (8 million students) would cost some US$ 248 million annually, about double the entire non- wage primary school budget in 2009/10. The plan appears to be to shift responsibility for providing food to communities, in order to address the sustainability problem, but it is not clear how likely this is to be embraced, especially if communities consist primarily of resource-poor households; and while it may still achieve the educational objectives, it would eliminate most of the transfer benefit. 33 Box 3: International Experience with School Feeding Programs Every country on which information is available now operates some kind of program to provide food to its school children. Middle-income countries run near-universal school feeding programs, covering, for example, 120 million children annually in India, and 35 million in Brazil. In lower-income countries coverage is typically lower, and programs are often dependent on donor financing, especially from WFP. Coverage in Africa ranges from about 50,000 (Ghana) to 200-300,000 (Malawi, Mozambique, Zambia), and 500,000+ (Ethiopia, Uganda), typically reaching less than 10% of the school population. Tanzania (600,000) is thus near the high end. Programs may provide meals, fortified biscuits, or take-home rations. On-site meals are a relatively expensive way of feeding the poor, because they provide meals to many children who may not need them. Take-home rations cost slightly more, but can be better targeted, allowing more coverage for the same expenditure. Globally, costs average $40 per child p.a. for on-site programs, slightly more for take-home rations, ($52 for a sample of four programs) and much less ($13 per student) for fortified biscuits. Targeting is often geographical: in Indonesia 530,000 students in vulnerable areas receive fortified biscuits, at a cost of about $18 p.a.each; Bangladesh provides high-energy biscuits for about 400,000 students in food-insecure areas ($12 p.a.). The trend worldwide is to shift from donor-run to domestic programs as countries become better off, and this transition can be accomplished quite quickly: El Salvador, for example, went from 100% WFP financing in 1999 to a totally domestic program by 2008. Ecuador has shifted to a full domestic program for 2 million children, using a trust fund to engage WFP to manage procurement and logistics. Kenya has a long-established program reaching 1.2 million children in vulnerable areas, at a cost of $28 per child; it is slowly transitioning to government ownership, with the Home Grown School Feeding Program aimed at 550,000 children previously fed by WFP. In 2009 the government allocated $6 million to this program, with cash transfers made directly to schools, who procure food locally. The evidence on impact of school feeding on educational outcomes and attendance is positive, but not very strong1. As a nutrition intervention, school feeding has been shown to have some positive impacts; but it reaches children later than the critical under-30 month age, and is nowhere near as cost- effective as supplemental feeding or food fortification1 . On balance school feeding programs are not a particularly cost-effective way of achieving either educational outcomes or consumption transfers, but they have the benefit of contributing to both simultaneously, and of being politically and socially readily acceptable. 34 3.4 Public Works Program (TASAF) 174. The Tanzania Social Action Fund (TASAF) operates a public works program to provide transfers to the poor through employment on labour-intensive construction projects. In common with such programs elsewhere, it seeks to raise the immediate consumption of the poor, while building infrastructure that will contribute to longer-term growth. Because the objective is primarily to help food insecure households and areas, the program is known as the Food Insecure (FI) sub-projects component of TASAF. 175. Estimates of coverage are inconsistent, but the most reliable data suggest that the program has employed about 27,000 people per year, at a total cost of about US$ 3.3 annually. On average participants have been employed about 20-30 days each, and received a transfer of about Tsh 90,600 (US$ 74) annually each. [Note there is substantial variation in data on the scale and performance of the program, but Table 26 shows some best estimates of beneficiaries and amounts transferred.] 176. Targeting and Implementation: There is a two-stage targeting process: firstly communities are selected based on poverty indicators, food insecurity, and accessibility.59 Secondly beneficiaries are selected to work on the projects, through community-guided targeting of food-insecure households. Furthermore, as in most public works programs, a below-market wage rate is used to discourage participation by the non-poor. 177. The wage rate is in theory set 10% below the prevailing local wage for unskilled labour. In practice there appears to be substantial local discretion in setting wages, which vary partly due to differing local conditions, and rural-urban differentials. Examination of a sample of 2009-10 projects shows rates which vary between Tsh.3,000 and Tsh.5,000 per day. While the lower level is in line with current wages the poor could earn elsewhere, the upper end appears to be above the normal wage for unskilled daily labour. There is no data available on the household characteristics of participants, and no evidence yet whether the program benefits the poor or not.60 178. Employment is targeted at the slack season. The program initially had difficulty in achieving this, due to delays in the preparation of subprojects 61 and no perceptible seasonality to the distribution of work was evident. 179. Note that because in the Tanzania social fund public works have been funded out of the same basket, and using the same selection system, as more traditional village social fund projects 59 Program documentation states: “Ranking will give weight to communities with (i) low literacy and high.. drop- out[ rates]; (ii)a high percentage of female-headed households, and. lack of job opportunities; (iii) high incidence of shocks such as seasonal droughts and crop failures.; (iv) inaccessibility and remoteness; (v) whether communities are persistently short of food; and (vi) whether they lack access to cash income.” Ref. WB PAD Ad’l Financing, 2009.P.182. In reality it is hard to see how these multiple and disparate criteria are weighted, and there is no evidence as to how they are being applied in practice. 60 Some data on participants is collected during the targeting process, and is available at the local level. Impact evaluation is being conducted and will be available in 2012. 61 Implementation Completion Report, TASAF I, p.47. World Bank (2006); there is no more recent data available on employment by month. 35 (such as new classrooms or water systems), the public works schemes have to be proposed by communities, and compete for funds with other village-development projects. In fact, because local governments have substantial discretion in selecting projects, many fewer PWP activities have been financed than originally foreseen.62 In part as a result, additional funding for TASAF has been earmarked for public works, and the amount of employment created is expected to increase. 180. A main problem with this ‘projectized’ approach is that villages (and villagers) receive only a single, once-off infusion of support under public works – usually lasting only a few months – and the program then moves on to other localities, so no mechanism is established for making sustained transfers to the very poor. 181. Financing and Costs. Since funding is pooled with village development projects, it is difficult to separate out TASAF’s overheads, and thus to say what it is actually costing to deliver public works transfers under TASAF, (there are also difficulties in assessing the true cost to local governments of implementing and supervising the program); but some broad estimates can be made on the basis of performance under the first phase of the program (when components were separated), and some rough assumptions about current performance. Table 26: Costs & Cost-Effectiveness of the TASAF Public Works Program Estimated Costs Source and Time Period ICR (2000-2005) “Completed” Projects 2005-10/a Sub-Project Costs $ 11.0 million Tsh.7.108 billion Of which: transferred as wages $ 4.26 m. Tsh.3.348billion Overheads & Management $1.9+ m. Est.673 million Total Cost $ 12.9+ m. Tsh. 7.781 b. ($ 6.0 million) No. Of Beneficiaries 113,646 36,947 Amount Transferred per Beneficiary $ 36.50 Tsh.90,600 ($75.50) Estimated Cost per Beneficiary $ 113.51 Tsh.210,600 ($175.50) Estimated Cost per $ (or Tsh) $ 3.10 2.32($2.32) Transferred Author’s calculations a/ “Completed” project data as of October, 2010; data available for only about a third of projects actually completed. (234 ‘completed’ projects out of 681 ‘funded’ projects 2006-2010). 182. In the first phase the vast majority of sub-projects were rural access roads, followed by – to a far lesser extent – water storage and irrigation, and village environmental protection projects (such as planting seedlings). An earlier review found that unit costs for roads were lower than those constructed under other programs; but in the absence of rigorous evaluation it is difficult to say anything about the quality and appropriateness of infrastructure built under this public works program. 183. Given that it is costing between US$2.35 and $3.00 for every $1 transferred under the program, its justification as a poverty-reduction program depends critically on the benefits of the 62 This in part because PWP projects represent higher transaction and administrative costs for local governments – during the period 2005-2009 communities proposed some 31,700 PWP projects, but only 485 (1.5%) were funded (Table 2, Additional Financing paper; World Bank (2010). 36 infrastructure created, in terms of its contribution to long-term income gains; so at least a sample assessment of the development impact would be very useful. 184. Commentary: Public works clearly have a role to play as a transfer instrument in Tanzania, and the TASAF program has established a strong institutional base. The drawbacks with the current program would appear to be its limited coverage (employing only about 25,000 annually, or less than three-tenths of 1 per cent of the poor), and the fact that it provides only a limited, once-off infusion to households, whereas one of the main benefits of public works programs is generally their capacity to provide a more sustained transfer to the poor (often during each lean season). 185. It seems unlikely that a once-off transfer to households of Tsh. 90,600 (representing about 10% of the annual poverty-line income for a family of 6) would be enough to make any significant difference in their poverty status. Anecdotal reports suggest that some households are saving out of this transfer, to accumulate assets that may generate income, but there is no empirical evidence available. 186. At any rate, the absence of a rigorous evaluation is a gap that needs to be rectified – such an evaluation would be designed to get a better grasp of the characteristics of those being reached, whether the beneficiaries are in fact among the poor; to critically examine the targeting mechanism and wage rate; and to have a better look at the appropriateness and benefits of the infrastructure being created. 37 Box 4: Some Experiences Worldwide with Public Works Programs It is possible to reach greater numbers of the poor, and transfer more to them, using public works programs than is currently done in Tanzania. In India, the National Rural Employment Guarantee Program provides a guarantee of 100 days of work per household, on demand, to all rural families, at a minimum local agricultural wage rate, and is completely self-targeting on the basis of the low wage rate. In Ethiopia, the PSNP program employs some 1.2 million people annually, for an average of 150 days each, at a cost of about US$280 million p.a. It uses a combination of self-targeting through the wage rate, along with geographical targeting (poor areas), and community selection of beneficiaries (because there is excess demand for employment). The Ethiopia program has had success in transforming some areas to higher long-term productivity by improving soil and water management, as well as the more usual road construction projects. While there are challenges (and costs) in mounting this scale of program, even countries with less ambitious programs (such as Malawi and Zimbabwe) have managed to achieve coverage of about 300- 400,000 persons per year. Argentina’s Trabajo program achieved a labour-intensity of about 60% of expenditure going as wages to the poor, as do programs in Zambia, Madagascar, and India; while only between 38% and 47% of spending in Tanzania currently goes in wages. The LIPW program in Botswana, which focuses mostly on maintenance of dirt roads, achieves levels of 63-78% in wages. Shifting to road maintenance has a number of other benefits: it does not require the formulation of separate ‘projects’ to employ the poor, it can be administered through existing systems, and can make use of money that is already being spent in the budget. This option is discussed further in Chapter 6. 3.5 Food-for-Work: The Food for Assets Creation Program (WFP) 187. The food-for-assets program provides work in the lean season to the poor in food- insecure Districts, paying participants in food. The objective is to reduce pressure on families by providing food when stocks are low, and prices are high. The assets created tend to be linked to longer-term food security, such as irrigation works and farm-to-market access roads. 188. The program has until recently employed about 25,000 people annually (currently being expanded to 55,000), at an average cost of about US$ 2.1 million per year63. Each participant receives 3 kg. of food per day worked64, with a value of about Tsh.2,20065. Since the program is intended to improve food security more generally, it also includes training in farm management and post-harvest practices. 189. The average participant works about 30 days. Each receives a family ration, based on an average of 5 persons per family 66 equivalent to 962 kcal per capita, or about one third of the 63 Based on costs in Country Program document – assuming over 3 years; note evaluation document (p.57) reports only $1.5 million expenditure in 2009. 64 The average actual ration consists of 3 kg. maize, 450 g. of pulses, and 225.g. of vegetable oil. 65 Based on an estimated value per ‘piece’ ration of Tsg 732; a larger ration is being introduced in the new program with a value of 1,527 per piece (about Tsh. 4,600 per day) 66 Based on a daily ration of about 0.2 kg of grain per person) [per beneficiary = 1 kg. per worker? To clarify w/Sheila] 38 family’s daily minimum food requirement. The average transfer per participating household is about 90 kg. of maize67, with a value of about Tsh 65,880 , or 8% of the food poverty line income. Table 27: Food for Asset Creation – Costs and Coverage 2007-2010/a Est. Using Evaluation Data (annual avg.)b/ Cost of Food $6.2 million n.a. Total cost of Program $ 9.8 million $ 1.26 million Number of Persons-Employed 110,000 18,500 Number of Total Beneficiaries 440,000 93,000 Average Transfer per Beneficiary Tsh. 13,200 Tsh.13,200 ($ 10.14) ($10.14) Average Cost/Beneficiary $22.27 $13.55 Cost per $ Benefit Transferred $2.20 $1.30 Author’s calculations using: a/ Planned, based on WFP CP document 2007-2010; b/ based on costs in program evaluation document for 2007-2009 (table . p.57), actuals for 2009/10 appear to be substantially higher.. 190. Targeting and Implementation: In the first instance the program is geographically targeted, operating inDistricts judged to be food insecure on the basis of the Vulnerability Assessment exercise. Individual targeting of households to participate then takes place through a Community Managed Distribution and Targeting (CMDT) mechanism using specially-elected village committees. The program is also targeted in time – taking place only in the lean-season months, when labour is in excess, and food needs are greatest. 191. There is no assessment available that would allow us to categorically say what the poverty status is of the persons receiving transfers, but it would seem reasonable to suspect that – based on the geographical targeting of highly food insecure areas, and the extensive community targeting methodology - that the poorer, if not the poorest, households are receiving benefits. However it would be worth confirming this more rigorously; and, at a minimum, comparing the ration paid with the wage levels for unskilled labour in the same villages during the slack season, to determine whether the non-poor are likely being attracted into the program. 192. Assessment: Like the public works program under TASAF, Food-for-Assets appears to have built a good base for employment-based transfers. Also like TASAF, the relevance of the program is highly dependent on the poverty-reducing impact of the assets being created, and for that a more rigorous assessment is needed. 193. At the current scale, employing 54,500 people in 2010, the program has only limited impact as a poverty-reducing measure, and although it may be significant in the areas directly affected, the CFSVA data show no more than 1% of rural households reporting receiving benefits from food-for-work in any District. Subject to confirmation that it is being cost- effectively implemented, it is potentially expandable, and has some important characteristics that might make it part of the on-going/future national safety net strategy 67 The ration for each ‘piece’ of work is 1 kg of maize, 150g. of pulses, and 75 g. Of vegetable oil; (based on a family of 5, five times an individual ration of 200g, 30 g., and 15g. Respectively) 39 194. Of particular interest is the extent to which food transfers are critical in the areas impacted. While cash is clearly always the more cost-effective option (and consideration is being given to phasing the FFA program towards a more cash-for-work, or voucher scheme), it is nonetheless possible that in the areas affected food supplies may be too scarce, and food markets too shallow, for the poor to be able to access food even if they were provided with cash. This is an empirical question which can be investigated further, and to the extent it is true, food-for- work probably should remain part of the arsenal of safety net interventions that the government uses. Other Transfer Programs 3.6 National Agricultural Input Voucher Scheme (NAIVS) 195. NAVIS is the largest transfer program currently operating in Tanzania (at a cost of about US$ 69 million annually, and reaching about 1.5 million beneficiary households)68. It provides input subsidies to farmers growing Tanzania’s two main food staples: maize and rice. Although designed primarily as a productivity-enhancing program, NAIVS has many characteristics that make it potentially attractive - with suitable adjustments – as a longer-term safety net intervention. NAIVS was designed to replace the Government’s earlier fertilizer subsidy scheme, which had proven unsustainable69 . It provides vouchers to farmers that cover half the cost of fertilizer, and enough seed, to cultivate 1 acre maize or rice. Because farmers invest their own labour and land in the production process, the gross benefit, in terms of value to the household, is potentially four times greater than the cost of providing the transfer. (see discussion below, and Table 28). 196. The primary rationale of the program is to increase use of fertilizer among small farmers – at present only 5.7% use improved crop varieties together with fertilizer.70 The reasons for sub- optimal fertilizer use among the poor include unwillingness – or inability - to take the risk of using fertilizer in the face of unpredictable rainfall, the absence of sufficient cash to buy inputs, and/or failures in agricultural credit markets. Since the primary objective is productivity increases, NAIVS is mostly targeted at areas of higher potential; although because it includes rice as well as maize, it also incorporates poorer areas (and in fact now covers much of the country 71). Within these areas it targets households growing 1 ha. or less of maize or paddy, and is ultimately expected to reach some 2.5 million farmers, or about half of the farming households in Tanzania. 197. Each family receives a voucher valued at about Tsh 60,000 in today’s prices72 . With proper use, fertilizer can potentially double yields73. Depending on assumptions about fertilizer 68 2009/10 target; expanding to 2 million farming households and about US$ 100 million in 2010/11. 69 See World Bank (2009 b) 70 5.7% of maize farmers and 0.7% of paddy farmers. 71 The program operates in – out of 140 Districts; it would have been mostly in southern highlands, but is now in nearly every region because of the inclusion of rice. 72 The value varies with the market price of fertilizer, and a remoteness premium; in 2008/09 prices the face values of the vouchers ranged from Tsh 24,000 to 27,000 for a 50kg. bag of urea, and 45,000-48,000 for a bag of DAP— 40 response, and maize prices, the value of the output generated could be up to Tsh. 260,000 (US$ 173) per household (Table 28). As a transfer mechanism, the voucher scheme – or something like it - is thus a potentially very attractive mechanism. Table 28: Approximate Costs, and Benefits to Households of Inputs Voucher Scheme At 65% Fertilizer At 80% Fertilizer Efficiency Efficiency Cost of Fertilizer Package (Tsh) 120,000 120,000 Value of Voucher (Tsh) 60.000 60.000 Estimated Additional Maize Production (kg.)/1 600 742 Estimated Value to Household of Additional 210,000 ($140) 260,000 ($173) Production (Tsh (US$))/2 Approximate Ratio of Benefit to HH to: (i) Cost of transfer per HH /3 2.45:1 3:1 (ii) Cash Outlay by HH 3.5:1 4.3:1 1/ Author’s calculations - based on 0.5 ha. of hybrid maize, and potential production of 2,975 kg. /ha. 2/ Based on maize value of Tsh 350 per kg.; for net consumer households. 3/ Based on total cost per beneficiary including overheads of about US$ 57 per HH. 198. The total cost of the program is estimated at US$ 299 million over the next 3 years, although this includes some once-off costs associated with strengthening the input supply network. On average the overhead costs of delivering the program are about 25% of the value of the vouchers74, and very roughly, by our estimates the program in total is costing only 25-45 cents for every $1 worth of benefit delivered to households in terms of increased consumption75. (Note however these are based on potential yield increases, actuals could be much lower; careful monitoring of performance is essential to assess NAVIS’ cost-effectiveness as a transfer mechanism.) each family receives one of each.; plus 10 kg, of seeds. In 2010 the total package is reportedly worth Tsh 120,000, and the voucher about Tsh 60,000. 73 From 1,120 to between 2,450-3,200 kg. per ha. for maize, and from 1,735 to 2,800-3,300 kg./ha. for paddy. 74 Note overheads in the initial phase are high, because the program includes parallel measures to strengthen the network of traders and suppliers . It is not clear to which estimates include the costs to District and local government departments of implementing the program. [CHECK W/ MADHUR; see p.123 Of PAD; last table of this section ] 75 Assuming they are net-consumers, and reducing purchases from market; the correct measure of benefits for a poverty-focused version of the program. Note the benefits to non-poor net-sellers are substantially lower. 41 Table 29: Approximate Costs and Coverage of National Agricultural Input Voucher Scheme 2009/10 2010/11 2011/12 Subsidy Costs $69 million $ 99.5 m. $ 92.8 m Total Program Costs $83.7 m. $113.2 m. $ 102.3 m. Number of Beneficiaries Participating Farmers 1,540,000 2,040,000 1,800,000 Estimated Number of Persons 7,700,000 10,200,000 9,000,000 Reached/2 Estimated Cost per Beneficiary $13.09 $11.10 $11.37 Potential value of increased $18.55-30.92 $24.12-40.14 $27.83-46.38 consumption per beneficiary /3 Source Author’s calculations;WB 2009 b Tables A.8.1, A.9.1; p.122-123; 2/ Based on estimated HH size of 5; 3/ efficiency of 50% 2009/10, 65% 2010/11 and 80% 2011/12; maize price range of Tsh.300-500 kg, 199. The NAIVS program is financed by the Government, using its own resources and those provided by the World Bank. Half of the subsidy, and a share of the overheads, are financed for using the proceeds of World Bank credit for the next three years. 200. Targeting and Implementation: The program is administered by the Ministry of Agriculture, Food Security and Cooperatives (MAFC) and local governments. District targeting decisions are made at the central level, and then village allocations are made within the Districts, based on the estimated number of eligible famers per village. Individual targeting takes place through elected Village Voucher Committees76, which determine eligible households. Beneficiaries must be farming households, and must cultivate one hectare or less of maize or rice; preference is supposedly given to farmers who have not used fertilizer and improved varieties in the past, and to female-headed households. 201. It is too early to say how effective the targeting is, and who is actually benefitting. There are anecdotal stories of poorer farmers not being able to afford their share of the package, or of selling the vouchers at a steep discount rather than using them, but the field monitoring teams have not so far come across evidence to substantiate these on any scale. At any rate, the program is being rigorously monitored through a series of panel surveys77, and detailed information on beneficiaries and impacts should be available in about a year’s time. 202. Note however a preliminary assessment using the Kilimanjaro and Ruvuma data78 found: (a) that farmers preferred the voucher to a cash transfer by quite a large margin; (b) that some families that qualified did not take up the vouchers because of concerns with financing their share of the package; (c) participation was more likely for farmers linked into the village leadership structure; and (d) no conclusive evidence on productivity increases (although this was only in the first year of the program, and was not based on a scientific measurement of crop output.) 76 Districts aggregate data on the number of eligible farmers per village; in some villages the number of vouchers available might cover half of the potentially eligible farmers – this proportion is to be raised with expansion of the program. 77 A panel survey is being undertaken in two rounds per year over three years, to track implementation and impact. 78 “Poverty Evolution and the Input Voucher Scheme in Kilimanjaro and Ruvuuma” Pan and Chritiansen 2009 42 203. While it is undoubtedly a transfer program, there is some question as to whether NAIVS is a poverty program. It is designed to give a once-off boost to food production – to overcome the effects of the global crisis, high food prices, and regional shortages, and to kick-start use of fertilizer and improved varieties by small farmers. It is thus concentrated in high-potential areas, which are not those of greatest poverty. But within those areas it is supposed to be selective of smaller farmers (those with less than 1 ha. of maize or paddy), who are presumably among the less well-off; and, as shown in Chapter 2 above, there exist many very poor people in better-off Districts. Furthermore, in most marginal areas, the majority of farmers are reportedly proving eligible for the vouchers.79 204. It would seem evident that NAIVS is not reaching the poorest (they are more likely to be landless, unable to work, to finance their share of the package, or otherwise ill-equipped to utilize the inputs); but given the wide coverage is probably reaching the middle-poor in the areas covered. However it is worth thinking seriously about whether a revised version of the program might be extended over the longer term to address the needs of poorer farmers. Some attributes of an amended program might be smaller input packages, possibly a 100% subsidy, and narrower targeting at the poorest. [A good example is the Malawi ‘starter pack’ program, which provided very small input packages to poor farmers, just large enough to apply to subsistence maize plots80]. The attraction is the potentially very high returns to poor households, relative to the cost of the transfer. Challenges might lie in the political difficulty of shifting to a more targeted approach, after the program has been nearly universal, the potential difficulty of targeting, and the ability of poorer farmers to effectively use the package. 3.7 Vulnerable Group Program (TASAF) 205. The Vulnerable Group (VG) program provides grants to small groups of vulnerable people (such as the elderly, orphans, or the disabled) to undertake income-generating activities. At present the program reaches about 20,000 persons per year, at a cost of about Tsh.8 billion annually (US$ 6.4 million).81 206. Each ‘group’ of about 10 people receives a grant of about US$ 8,500 equivalent82, to finance a business such as poultry or livestock-raising. As such, it is more an income-generating program than a safety net transfer. [While income-generating projects are a legitimate part of the poverty-reducing strategies of many countries, they are not primarily safety net/transfer programs per se, and if the VG program is included, then the scores of other income-generating and micro-credit programs operating in Tanzania should also be evaluated, a task which lies beyond the scope of this study. Nonetheless, as the VG program is incorporated in TASAF with the public works scheme, and because there may be some lessons for future safety net strategies, 79 Based on verbal feedback to author from field visits; data not yet available. 80 The program shifted over time between packages and vouchers, and between universal and targeted coverage; there were benefits and drawbacks to both approaches, but it had a major impact on consumption of the poor. 81 Based on funded sub-projects over the first 5 years (2006-2010), amount disbursed of Tsh.31.4 billion over 4- and-a-half years, plus 10% overheads; but note most are continuing beneficiaries. 82 Based on actual performance up to February 2010 (as reported in Implementation Support Mission status report of March 2010, TASAF); the project documentation for the recent expansion of the program shows a target grant size of about US$ 10,000 per group 43 a brief examination of the program is included here. A detailed evaluation is presented in Annex 2. 207. Implementation and Targeting: Targeting is undertaken through a process of community-based identification of beneficiaries. Preliminary evaluation results suggest that VG participants are on average slightly worse-off than non-participants drawn from similar vulnerability categories from the same village, and substantially less well-off than the population as a whole in the same villages. (Annex Table 2.1). Although the program operates nation-wide, funding for expansion has been earmarked for the 40 most food-insecure Districts, introducing a further layer of geographic targeting. 208. Commentary. The VG program has some interesting characteristics: this is not the group one would expect to be the obvious clientele for income-generating activities. Typically it is the more dynamic, younger, and ‘middle-poor’ in villages who are best equipped to take advantage of small-scale commercial opportunities. If the VG program can be shown to work, it is thus a potentially promising way to raise incomes of some of the more poor permanently. However the impact of the VG program, and its potential cost-effectiveness as a transfer instrument, depends critically on the financial viability of the projects funded. 209. To date monitoring and evaluation has concentrated on the indirect evidence of welfare and consumption changes among individual members. The important thing to do moving forward is to rigorously assess the financial flows being generated by the projects being undertaken. 210. It is worth noting that the $1,000 per beneficiary transfer is very large, compared to both poverty line incomes, and to grants or loans typically provided under similar programs. A further potential concern is the incentive structure, and consistency with other small business programs, most of which provide loans rather than grants. 211. Given the scale - reaching only a few tens of thousands of persons a year – the VG program is unlikely to form a significant part of a national safety net strategy. The very high levels of transfer ($10,000 per project) limit the capacity to expand this program; to reach just 3% of the poor, for example, would cost about US$180 million, based on its current cost structure83. 212. Given strong policy preference for self-help rather than pure transfers in Tanzania, it is quite possible that income-generating programs – if they can be shown to work – could form a meaningful part of the poverty-reduction strategy. We would reiterate however, that they are not ‘safety net’ interventions in the sense that the other programs reviewed in this paper are, and that the Vulnerable Group program really needs to be assessed in comparison with other income- generating and microcredit programs in Tanzania. 83 Based on 13 million poor. 44 3.8 Formal Transfer Programs 213. The formal social security system in Tanzania consists of five contributory schemes, of which the two main ones are the National Social Security Fund (NSSF), and the Public Service Pension Fund (PSPF). 214. The NSSF is the largest, and is intended to provide coverage for private sector workers; while the other four cover various types of public employees. All provide a pension at a certain age (usually 60), and typically pay amounts that are well above the poverty line income (see Table 30). Table 30: Summary Characteristics of the Formal Social Security Programs Active Members (2007) Average Monthly Pension Scheme (Tsh. 2006) NSSF 307,500 52,900 PSPF 235,000 85,825 Parastatal PF 64,000 37,560 Local Authority PF 45,000 n/a Gov’t Employees Provident Fund 22,000 40,165 215. The average pension under the NSSF, for example, in 2006, was equivalent to about US$ 529 p.a., which represented about five times the per-capita poverty line income, and is far greater than most of the transfers to the poor provided by other programs discussed in this paper. 216. Despite efforts to extend the system to the informal sector, coverage is essentially limited to those in formal sector employment - representing perhaps 6% of the population, who inevitably tend to be among the least poor. As a poverty reduction safety net, the formal social security system is thus of limited relevance. 217. It is also worth noting that many participants take lump-sum withdrawals, thus dissipating the intended long-term income-support benefit of the programs. Also several of the programs are facing financial sustainability challenges, and are being covered by a parallel World Bank study 84, and thus are not analyzed in any further depth here. Health Exemptions and Insurance 218. Health insurance schemes have been introduced over the past decade to spread the costs of providing health care, to pool risks, and reduce the impact of catastrophic expenditures on households, However as with the formal pension system, they tend to cover mostly formal sector employees. The National Health Insurance Fund (NHIF) is the largest; membership is compulsory for all public sector employees and as of the program covered about 2 million beneficiaries, or roughly 5% of the population.85 84 Options for Reform of the Tanzania Pension System; draft;World Bank (2010) 85 Sources: Tanzania Social Protection PER (ILO 2009) and Health Financing Policy Note (draft, WB, 2010) 45 219. The Social Health Insurance Benefit (SHIB) is a sub-set of the NSSF, and allows participants in the NSSF to insure themselves for medical benefits. There are currently only about 51,000 members. As with the NSSF in general, participation tends to be limited those in formal sector employment, so its relevance as a safety net for the poor is limited. 220. Community Health Funds were established to create health coverage for the broader population, with matching grants provided from the government through the Health Basket Fund to finance CHF coverage for the poor. However there has been only limited enthusiasm for these schemes – it is estimated that spending by such community-based funds represents only about 2% of health spending86, and only about 4.4% of the population has joined such a fund.87 221. Exemptions: Fees for basic health services were introduced in the 1990s, as a means of mobilizing resources for local health facilities. From the outset there has been concern that they were discouraging use of services by the poor. There are two types of exemptions: exemptions granted to pregnant women and the elderly – which appear to be fairly arbitrary and not always honoured; and a program free CHF cards provided to the poor by District governments (financed with the matching grants referred to above). The approximate value of the card is Tsh 10,000, which provides a family with free access to all health services in the District for a year. About Tsh 1 billion (US$ 670,000) is spent on the program annually, to benefit about 100,000 households (about 500,000 people). The cards are distributed using a community targeting system. There have been no studies that track whether or not the cards go to the poorest, nor of the impact on health-seeking behaviour. 222. How important are health insurance or exemptions, potentially, as part of a safety net strategy? The evidence is contradictory. Although much is made of the burden placed on the poor as a result of health care costs, the HBS shows that health care represents only about 2-3% of household spending, even among the very poor (Table 10 in Chapter 2)88. Clearly in catastrophic circumstances however the amounts can be significant – especially for the poor who have very little cash income, and in a policy sense one does not want people to be failing to seek essential health care because of cost. 223. While the very small shares of average consumption suggest that health fee waivers and the like are probably not a large part of the safety net solution in Tanzania; there is however enough anecdotal evidence (see CARE (2009)) to suggest that fee barriers are discouraging use of services in some circumstances. The HBS data show that about 26% of people who do not seek health care report not doing so because it is too expensive; and although the poor report similar utilization rates of health facilities as the non-poor (Chapter 2), it may be that they are going for low-cost interventions, and not going for more critical, and expensive health, interventions. It is important to ensure that existing exemptions for the elderly and pregnant women be enforced, and – subject to further analysis of how well the system is targeted - to possibly expand the program of free CHF cards for the poor. 86 Social Protection PER p.37 (ILO, 2009) 87 Health Financing Policy Note: Table 1. 88 Other surveys report different percentages, but confirm this low order-of-magnitude 46 3.9 Small and/or Innovative Programs 224. There are many more transfer programs in Tanzania, most of them are very small-scale, often operated by NGOs covering a very limited geographical area. This section highlights some of the more significant ones, including two particular ones – a cash transfer pilot, and an old age social pension - that are relevant to the current debate around expansion of safety nets in Tanzania. Pilot Cash Transfer Programs 225. There have been three programs of cash transfers to the very poor – the KwaWazee program in Kagere region, one funded by SCF in Linde District, and an on-going TASAF CCT pilot program. All have had some success, but all have been piloted on a very small scale, none has been implemented for very long, and none have been rigorously evaluated to assess their impacts. 226. KwaWazee - An Old Age Pension: The KwaWazee program initially provided transfers to elderly persons supporting orphans, it had success in improving welfare in the households affected89, and served as a model for the current proposal for a universal pension for the elderly.The program provided a transfer of Tsh. 6,000 per month (about US$5 at the time) to poor and vulnerable people over 60 who were caring for children without parents, plus child benefits of Tsh. 3,000 for each grandchild. The pilot operated over four years in the Kagere district, and eventually supported about 700 elderly persons (of whom about 90% were women, and of whom about half supported children90). Beneficiaries were identified by community volunteers on the basis of age, health, and living conditions. A combined qualitative/quantitative evaluation found a reduction in begging and selling of assets among beneficiaries; and improved school attendance and food consumption. 227. SCF Cash Transfer Program: Save the Children (SCF) piloted an unconditional cash transfer scheme for the extreme poor in Linde District from 2007 to 2009. The program provided assistance to 60 households, most of which were headed a single mother or grandmother supporting vulnerable children. Each family received Tsh. 6,000 per month, plus 3,000 for each vulnerable child. A qualitative evaluation91 found the funds were used primarily to purchase food and school materials, and concluded that the program did reach truly vulnerable households, and materially improved their consumption during the pilot period – increasing from 1-2 meals a day to 2-3. Several recipients reported longer-term gains (purchase of assets, income generating activities); although more reported that their situation reverted to extreme poverty after the program ended. Suggestions for future programs included incorporating more training on income-generation and nutrition, and adding conditionality to the transfers. 228. TASAF is piloting a conditional cash transfer (CCT) to elderly persons supporting orphans or children. To be eligible, the household head must be 60 years of age, and/or include 89 See “Salt, Soap, and Shoes for School: Evaluation Summary” REPSSI/Helpage/SDC/WorldVision 2008 90 The program was expanded beyond its original scope – because it was found that there were many equally- vulnerable elderly who did not have children living with them. 91 Final Evaluation of Lindi Unconditional Cash Transfer Program; SCF (2011) 47 vulnerable children; and must fulfill certain conditions (such as school or clinic attendance for children, or the elderly person going for a medical check-up.) The coverage is very small, currently reaching only 6,000 households. Each receives a monthly transfer of Tsh 7,500 monthly per adult, and 3,750 for each eligible child, for an average payment of about Tsh. 15,000 per household, every two months. Targeting is in theory done by village committees, who identify the most needy households in the village, in accordance with guidelines laid out by TASAF, although in practice a combination of administrative and proxy means testing is used. Compliance with conditions is monitored by a combination of the village committee, TASAF, and local government staff. 229. The program has only been going for a year, and it is too early to tell how effective is, although beneficiaries and those involved in community targeting claim it is having a positive effect on the households involved. CCTs are being considered for expansion. Box 5 presents some experience worldwide, and a discussion of the benefits and drawbacks of conditioning transfers in Tanzania is presented in Chapter 6 and Annex IV. 48 Box 5: Global Experience with Conditional Cash Transfers CCTs have two objectives: to provide short-term poverty alleviation through a cash transfer and to reduce inter-generational poverty by requiring families to invest in human capital, by, for example, keeping their children in school, or maintaining them in good health through preventive health and nutrition programs. The benefit paid is usually equivalent to about 15%-25% of households’ baseline consumption. Fiscal impact varies depending on the size of the program, but nationwide programs such as Brazil’s, México’s or Colombia’s cost about 0.4 % of GDP per year. Evaluations have shown that CCTs can be effective in improving health, education and malnutrition, while increasing consumption among the poor in both middle- and low-income countries. For instance, in Brazil, between 2003 and 2008, the CCTs explained 35% of the reduction in extreme poverty and 13% of the fall in inequality; in Colombia during the first two years of the program beneficiaries increased total consumption by 15 percentage points more than households without the program. In Malawi, enrollment and attendance among beneficiary girls grew significantly more than those without transfers, and the impact persisted after the transfer was suspended. In Cambodia enrollment rates among children in the program are significantly higher than those without program with the biggest different among the poorest. In Nicaragua the CCT program reduced chronic malnutrition by 7 percentage points and the impact persisted after the program ended. In India, a conditional cash scheme increased ante-natal care and in-facility births significantly, and is responsible for a reduction of 4.1. peri-natal deaths per 1000 pregnancies and 2.4 neo-natal deaths per 1000 live births. Evaluations in Malawi, Mexico and Ecuador have demonstrated that conditions matter and that programs that condition the transfer have greater impact in school enrollment and attendance than unconditioned transfers. However careful design and implementation are essential for CCT programs to be successful. Experience has shown that the following are critically important: (i) defining the level and type of transfer, (that is, whether it is paid per family, per beneficiary member, or per conditionality); (ii) the definition of the beneficiaries’ co-responsibilities, and a verification process to monitor compliance; (iii) appropriate targeting mechanisms (CCT programs usually combine geographical, proxy means and community targeting methods); (iv) maintaining the frequency of payments; (v) transparent payment mechanisms; combined with control and audits at local level; and (vi) regular re-certification of program beneficiaries. Finally, it is critical that beneficiaries should have access to the services linked to the CCT program (usually schools and health providers), and these services must be effective. Sources: Brazil (Barros, RP, M de Carvalho, S. Franco and R. Mendoça (2010) “Markets, the state and the dynamics of inequality: The case of Brazil”, UNICEF, Working Paper, January 2010, and Barros, RP and M. de Carvalho (2009) “On the Brazilian recent sharp decline in poverty and inequality: 2003-2008), ppt presented at the World Bank Brazil Brawn Bag Lunch -November 2009); Colombia (Attanasio, O. and A. Mesnard (2006) “The impact of a Conditional Cash Transfer Programme on Consumption in Colombia”. Fiscal Studies, vol. 27, No 4); Cambodia (Filmer, D. and N. Schady (2006) “Getting Girls into School: Evidence from a sholarship Program in Cambodia”, WB Policy Research Working Paper 3910) India (Lim, SS, L. Dandona, JA Hoisington, SL James, MC Hogan and E. Gakidou (2010) “India’s Janani Suraksha Yojana, a conditional cash transfer programme to increase births in health facilities: an impact evaluation”, The Lancet, Vol. 375, June). Malawi (Baird, S. C. McIntosh, B. Ozler (2011) “Cash or Condition? Evidence from a Cash Transfer Experiment” Nicaragua (Maluccio, JA and R. Florez (2005) “Impact Evaluation of a Conditional Cash Transfer Program The Nicaraguan Red de Protección Social”, IFPRI, Research Report 141). Mexico (de Brauw, A. and J Hoddinott (2008) “Must Conditional Cash Transfer Programs Be Conditioned to Be Effective? The Impact of Conditioning Transfers on School Enrollment in Mexico”, IFPRI Discussion Paper 00757 Ecuador (Schady, N. and C. Araujo ( 2008) Cash transfers, conditions, and school enrollment in Ecuador. World Bank 49 3.10 Overview of Impact of Current Programs 230. How well does the existing package of programs respond to poverty needs? Table 31 shows a summary of coverage and targeting criteria. The first thing that is immediately clear is how few of the poor are being reached by existing transfers. The only programs that are large enough to have any significant impact are food distribution under the NFRA, and the MVC program - although the latter delivers only very small and intermittent benefits. 50 Table 31: Summary of Coverage and Targeting of Existing Transfer Programs Program Intended Targeting % of the % of Shocks/Aspects of Comments/ Target Mechanism Poor Extreme Poverty Addressed Significance of Group Reached/a Poor/b Benefits to Households NAIVS Farmers w/ < Community n.a. n.a. Seasonal Food Significant benefits; 1 ha. Committee Est.5-10% Est.0-5% Shortage; low- but not currently & risk/low-return targeted at the poor. Geographical behaviour MVC Households of Community Est. 4-5% Est.<9% Orphanhood/Extrem Generally small and orphans and Committee e Poverty intermittent. other MVCs Significant in some cases (e.g. housing), but not sustained. FFE All school Geographical Est. 3% Est. 6% Geographical Food Relatively (School children in – Food Shortages; low significant; but Feeding) selected Insecure education small coverage, and Districts Areas participation not targeted at poorest. FFA Poor Geographical Est. 1% Est . Seasonal Food Relatively (Food for Households in – Food 1-2% shortages significant; approx - Work) food-short Insecure -% of food p-line areas Districts plus income; in lean Community season. Committee NFPRA Households in Geographical Est.20%. Est.20%. Seasonal food Potentially (Subsidized food-short – Food shortages and price significant to Food areas. Insecure increases families receiving Distrbt’n) Districts plus benefits – est. 35% Community of food poverty line Committee income (if distributed as intended). Public Able-bodied Geographic,se Est.1% Est. 1% Low household Once-off transfer Works poor. lf-targeting incomes only. (TASAF) plus Community Committee VG Small groups Community 0.5% <1% Vulnerable groups Really an income- (TASAF) of vulnerable targeting such as widows, generating program; individuals AIDS sufferers, grant is extremely unemployed youth large Pilot Cash Low-income Community Less than < 0.2% Orphanhood, Potentially Transfer elderly with Targeting; 0.1% elderly/infirmity significant; but Schemes children Food-Insecure program too small to Areas; PMT be meaningful at this stage Author’s calculation; a/based on 12.7 million below BN poverty line; b/ based on 6.4 million below food poverty line . Note estimates of % reached are extremely rough order-of-magnitude, based on coverage numbers, and CFSVA reports on receipt of benefits for rural areas.(See next table) 231. The coverage numbers in Table 31 are based on some very rough assumptions of the possible incidence of benefits. There is not good monitoring of beneficiaries for any of the transfer programs and therefore it is not known what proportion of benefits are truly going to the 51 very poor, and which are going to other, unintended, beneficiaries. However, the recent CFSVA Survey produced some interesting - and worrying – results on the possible extent of inclusion and exclusion errors. Table 32: Some Evidence on Coverage and Inclusion and Exclusion Errors: % of Rural Households receiving Various Forms of Food and Non-food assistance (CFSVA 2010) % of Households Reporting Receiving Any Kind School Food for General Money Assistance By Wealth Quintile of Food Feeding Work Food Assistance Distribution Poorest 29.0% 1.9% 0.8% 21.0% 13.1% 2nd 23.5% 2.1% 0.2% 18.0% 5.8% rd 3 22.8% 0.7% 0.3% 16.0% 9.3% 4th 20.1% 1.2% 0.4% 14.4% 10.1% Wealthiest 18.5% 1.2% 0.7% 13.0% 11.5% Total Mainland Tnz. 23.0% 1.5% 0.5% 16.6% 10.0% By Food Consumption Group Poor 33.8% 5.9% 0.7% 20.6% 4.3% Borderline 34.4% 1.8% 0.8% 25.4% 14.3% Acceptable 19.6% 1.2% 0.4% 14.2% 9.5% Source CFSVA data; rural households only; Annex Tables p.208-209, re-calculated for this report by WFP. 232. If this data is accurate, it implies that about 13% of the households in the wealthiest fifth of the rural population are receiving free or subsidized food distributions; that the majority of participants in food-for-work are non-poor (with almost as many beneficiaries coming from the wealthiest quintile of the rural population as from the poorest), and that almost half the beneficiaries of school feeding are from the better-off half of the rural population. It should be noted that these data show the proportion of households reporting receipt of each kind of aid – they do not tell how much of the aid they received – so the apparent mismatch may be not as bad as it first appears. For example, it may be that while many well-off households receive food- distribution food, they receive very little of it. Nonetheless, the implicit level of mis-targeting is potentially a major cause for concern, and needs to be urgently investigated further. Box 6: Data, Monitoring, and Evaluation Concerns Almost none of the existing programs track whether they are reaching the poor, nor what impact they are having on the welfare of beneficiaries. Most do not even have reliable administrative data on how many people they are reaching, or the value of benefits they are receiving. None has had a rigorous evaluation done of its impact. Doing so is essential to choose the right programs, and get more poverty-reducing impact for the large amounts of money being spent. A priority should be (a) to collect independent data on which income groups are benefiting from transfer programs: (b) to mount rigorous independent evaluations of existing programs; and (c) to collect better data on benefits and beneficiaries within the programs. Chapter 6 suggests some immediate steps. 233. How well are current programs aligned with the possible poverty-reduction objectives for productive safety nets outlined in Box 1 at the beginning of this paper? 52 x The productive risk-reduction aspect is not particularly well-served, because most programs provide only once-off transfers; except for the NAIVS which supports farmers overcome the risk associated with using modern inputs; x The ‘promotional’ aspect is not well-served; the Vulnerable Group program potentially increases long-term incomes, but coverage is very small; transfers under the various works and cash programs could potentially contribute to savings and investment higher long-term incomes, but at the moment transfers are so small, and so intermittent, that this seems unlikely. x The human capital objective is really only achieved by the school feeding program at the moment, and potentially by the CCTs under TASAF, once they reach a larger scale. x The objective of longer-term growth is contributed to by the food-for-assets and PWP programs; although there is no information on the quality and productivity of the assets created. x The objective of escaping inter-generational poverty traps is addressed partially by the MVC program (but again, benefits are small and unpredictable); and the cash transfer pilots. 234. Annex Table 2.2.2 shows very roughly how well (or how poorly) the main characteristics of poverty in Tanzania identified in Chapter 2 are being addressed by the existing programs. Towards a Re-structured National Program 235. The current collection of programs is piecemeal and duplicative. With the forthcoming redesign of several major programs, Tanzania faces a unique opportunity to consolidate, and move to a more focused, a more rational, and a more effective national system. x The existing programs deliver intermittent, and inconsistent benefits to the poor (for example the MVC and the public works program under TASAF) x There is duplication of effort – for example the Most Vulnerable Children’s Program, Conditional Cash Transfers, NAIVS, and Food-for-Assets programs all support separate, but very similar community targeting systems. x Coverage is low - only a few percent of the poor appear to be being covered by existing programs. x There are both large inclusion and exclusion errors - partly as a result of geographical targeting, which has concentrated many programs in the same food-insecure Districts. x Coverage is patchy, uncoordinated, and potentially duplicative: (the same households, villages, or Districts could receive benefits from school feeding, TASAF, MVC, and Food for Assets programs, for example, while others, equally poor, receive none.) The options for re-structuring are discussed in Chapter 6. 53 CHAPTER IV: FISCAL SPACE AND AFFORDABILTY: POTENTIAL OBJECTIVES AND SCALE OF A NATIONAL SAFETY NET STRATEGY 236. This chapter addresses the very broad macro-level choices involved in deciding the scale of national safety net spending. Tanzania, indeed any country, faces three main questions in framing a national safety net strategy: (1) What role should safety net transfers to the poor play in reducing poverty? (2) Which groups, and which aspects of poverty does it make sense to target? (3) How much – in very broad terms – does it make sense to spend on safety net transfers? 237. This chapter lays out the considerations that should underpin these decisions in Tanzania. A second set of choices has to do with which programs to use to achieve these objectives; these are discussed in Chapter 6. 4.1 The Role of Safety Net Transfers in Tanzania’s Development Strategy 238. The first choice Tanzania faces is the extent to which it wants to use productive safety net transfers to raise the incomes of the poor, as opposed to relying solely on economic growth and other poverty-reducing interventions (such as delivery of education and health services). This is to some extent a political choice, but it needs to be informed by a judgment as to which aspect of poverty can best be addressed by safety net interventions, and whether the benefits of growth will reach the poor quickly enough. 239. The evidence to date is not encouraging. As shown in Chapter 2 the poorest appear to be hardly benefiting from growth at all. While there is some debate about the reliability of the data, most sources agree that the absolute number of poor has not decreased between 2000 and 2007 (see PHDR (2009), Hovvegen (2009)). The evidence therefore suggests that a revised approach, including a more aggressive use of productive safety nets, makes sense. 240. Given the tremendous potential of Tanzania, the primary focus of reducing poverty clearly needs to remain on re-engineering growth to reach poor Tanzanians. This means raising the productivity of subsistence agriculture, improving markets and access, investing in education and infrastructure, and encouraging smallholder cash cropping and small business. But judicious transfers to the poor can complement these efforts and hasten reduction of extreme poverty. 241. A central role of safety net transfers is to equip the poor to participate more fully in this growth process, and to bridge ‘gaps’ that are preventing them from realizing potential income gains. “Smart” safety nets can increase their productivity (by building human and physical capital); allow the poor to take on higher-risk, higher-return activities (for example using fertilizer); and increase the returns to their labour (examples include small cash transfers that allow women to undertake petty trading; or subsistence farmers to buy food, and thus shift some of their land to cash crops). 242. In a dynamic sense, the role of safety nets should be to support those who are left behind by the growth process. Who will be left behind? agrarian households living in areas of low 54 potential, or remote areas, or those with very small land-holdings; urban migrants who lack skills and assets; and those who lack the ability to participate in the labour market, such as orphans, the elderly and the infirm. The good news is that much extreme poverty among the farming poor in Tanzania is related to technology, market, and input constraints. Many of them should not need transfers in the long term, except in particularly unproductive areas, in very dry years, or for an intermediate ‘bridging’ period, until agricultural reforms take hold. 243. Well-designed safety nets will also reduce the poverty rate in the longer term, by helping the poor escape from inter-generational poverty traps (through better education, health, and nutrition for their children); and by reducing the impact of shocks and uninsured risks. 244. Finally, in a country like Tanzania, with a small but significant share of the population consuming less than the minimum daily food requirement, it is important also not to lose sight of the short-term benefits of public transfers: immediately lowering the poverty rate; reducing productivity losses due to insufficient food consumption, and fuelling demand at the local level. 245. For all these reasons it makes sense to see spending on safety nets as an important complement to growth-based poverty-reduction efforts; as a way of better linking the poor into the growth process, and as a transitional mechanism, until the benefit of other poverty-reduction investments kick in. What Might the Objectives of a National Safety Net Program Be? 246. The second choice facing policy-makers is which aspects of poverty they wish to tackle with transfers. Based on the analysis of poverty in Chapter 2, the following are some possible choices of broad objectives, in descending order of ambitiousness: x Relieve the worst of chronic poverty and food insecurity: Such a strategy would essentially target the 16% of the population below the food poverty line, on the grounds that these are Tanzanians living at an unacceptably low level of consumption; and, based on the analysis in Chapter 2, they also appear to be the least likely to benefit from growth in the near-to-medium term. x Reduce the impact of seasonal shocks on the poor: The objective could be to use selective transfers to cushion the impact of shocks on the poor and the medium-poor - for example, seasonal swings in food prices and availability, or droughts. This approach has the benefit that it can be tailored to achieve substantial welfare gains at relatively low cost. The drawback is that it does not necessarily address the needs of those who are chronically poor. x Support only the extremely poor and most vulnerable: Provide selective targeted assistance only to those who are obviously unable to look after themselves – such as orphans, the disabled or elderly who do not live in households. This has the benefit that it is likely to be readily acceptable as an objective, both politically and socially; and there is likely to be consensus on the beneficiaries to be targeted. The drawback is that there are many extremely poor people who do not fall into these categories. 55 247. Tanzania is at the moment de facto pursuing a combination of the last two objectives. This makes some sense, but Chapter 6 argues that a revised strategy should also attempt to address the first objective (tackling chronic poverty), provided this is done in a way that captures existing resources, and contributes to longer-term growth. The current National Social Protection Framework largely reflects this approach, proposing a combination of targeted support to vulnerable groups, combined with an emphasis on income-generating and credit programs. 4.2 Estimating the Extent of the Need 248. It is impossible to say with any certainty what the ‘need’ for safety net spending is. It depends on which groups society wants to support with SSNs, and how large a transfer is provided; but the poverty analysis in Chapter 2 provides some rough guidance. 249. Size of Coverage: The following are the numbers in some obvious potential target population: - Most Vulnerable Children, including double orphans, as defined in the NCPA: about 900,000. - The elderly, disabled, and those suffering from HIV/AIDS who are not living in households that can support them. A rough estimate is an additional 1 million persons92. - Those living below the food poverty line: about 6.4 million (which includes almost all of those in the above two categories); - Families facing severe seasonal food insecurity, approximately 5-10 million93 (although the number varies a lot from year to year, and most need assistance for only about 4 months) - The population living below the Basic Needs Poverty Line – about 12.7 million. 250. Thus the minimum number of people requiring support is probably in the order of 2 million (the extremely vulnerable), while the maximum is probably in the range of 7 million (those below the food poverty line); with another 3-4 million who would benefit from intermittent assistance.94 How much is enough? Setting the size of the transfer 251. The second part of the question policy-makers need to confront is what size of a transfer to provide, and how long to provide it for. There is no way of saying what the ‘right’ size of the transfer is. It depends on a combination of what is affordable, and what will do the most good. Too small a transfer will not have enough impact on the welfare of the poor, and too large a transfer will be unfair and divisive – raising the incomes of the very poor above those of the ‘average’ poor who do not receive benefits. 92 Using a very rough estimate at 5% of the population (drawing on the population census, Disability survey, and DHS); and deducting the MVCs included in the previous category. [