September 25, 2007

Document of the World BankR

eport No. 42093-PE

Peru

Social Safety Nets in Peru

Report No. 42093-PE

PeruSocial Safety Nets in Peru

Bolivia, Ecuador, Peru and Venezuela Country Management UnitHuman Development DepartmentLatin America and the Caribbean Region

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PROMARN

PRONAA

MACHCS PRONA-

SIAF SIME

SISVAN SIS-SMI

S SN UBN UNDP UNICEF WDR UIT VdL

Food and Nutrition Program for Abandoned Minors at Risk o f Malnutrition (Programa de Alimentaci6n y Nutrici6n del Menor en Estado de Abandon0 y Riesgo Nutricional) National Food Assistance Program (Programa Nacional de Asistencia Alimentaria)

National Project for the Management o f Water Sheds (Proyecto Nacional de Mantenimiento de Cuencas Hidrogrhficas y Conservaci6n de Suelos) Integrated Financial Management System (Sistema Integrado de Administracibn Financiera) Integrated Monitoring and Evaluation System (Sistema Integrado de Monitoreo e Evaluaci6n) Integral Mother and Child Maternal Insurances (Seguro Integral de Salud) Information System for Food and Nutrition monitoring in Peru (Sistema de Informaci6n para la Vigilancia Alimentaria y Nutricional del Peni) Social Safety Net Unsatisfied Basic Needs United Nations Development Programme United Nations Children’s Fund World Development Report Unit Taxation based (Unidad Impositiva Tributaria) Vas0 de Leche, food assistance program

V i c e President: Pamela Cox Country Director: Carlos Fel ipe Jaramil lo Sector Director: Evangeline Javier Sector Manager: Helena R i b e Country Sector Leader: Dan ie l Cotlear Task Team Leaders: Cornel ia Tesl iuc and

Ian Walker

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CONTENTS

SUMMARY ............................................................................................................................................................... V I

1 THE PATTERN OF EXCLUSION AND VULNERABILITY IN PERU .................................................... 1

WHY DO SOCIETIES NEED SOCIAL SAFETY NETS? ........................................................................................ 1 THE RESILIENCE OF POVERTY AND INEQUALITY IN PERU ............................................................................ 2 WHO NEEDS SSN PROGRAMS? A PROFILE OF VULNERABLE GROUPS IN PERU ............................................ 4

1.1 1.2 1.3

2 THE SOCIAL SAFETY NET IN PERU ........................................................................................................ 10

2.1 MAIN COMPONENTS OF THE PERUVIAN SOCIAL SAFETY NET ................................................................... 10 2.2 PUBLIC SPENDING ON THE SOCIAL SAFETY NET ........................................................................................ 14 2.3 VASO DE LECHE ........................................................................................................................................ 20 2.4 WORKFARE PROGRAMS ............................................................................................................................. 22 2.5 F O N C O D E S ............................................................................................................................................. 2 4 2.6 THE JUNTOS C C T PROGRAM ..................................................................................................................... 27

THE REDISTRIBUTIVE AND POVERTY IMPACT OF PERU’S FOOD PROGRAMS ...................... 37

CRITERIA FOR ASSESSING THE REDISTRIBUTIVE ROLE OF FOOD PROGRAMS ............................................ 37 FOOD PROGRAMS COVERAGE AND BENEFIT LEVELS .................................................................................. 38 FOOD PROGRAMS’ TARGETING PERFORMANCE ........................................................................................ 4 0 FOOD PROGRAMS’ IMPACT ON POVERTY AND MALNUTRITION ................................................................. 42

THE WAY FORWARD .................................................................................................................................. 44

4.1 KEY ISSUES FACING PERU’S SSN SYSTEM ................................................................................................. 4 4 4.2 RECOMMENDED STRATEGY ....................................................................................................................... 4 7

3

3.1 3.2 3.3 3.4

4

BIBLIOGRAPHY ..................................................................................................................................................... 51

ANNEX 1 . PERU’S FOOD TRANSFER PROGRAMS IN 2006 .......................................................................... 53

ANNEX 2: ESTIMATING THE INCIDENCE OF PUBLIC SPENDING FOR FOOD PROGRAMS ............ 54

ANNEX 3: ALGORITMO PARA EL CALCULO DE LA PROBABILIDAD DE POBREZA ......................... 56

ANNEX 4: FINDINGS AND LESSONS FROM THE EVALUATIONS OF PERU’S FOOD PROGRAMS .. 59

ANNEX 5: IMPROVED PROXY MEANS TEST MODEL: AN ILLUSTRATION .......................................... 61

... 111

FIGURES Figure 1-1 : Malnutrition by expenditure quintile. 1996 and 2001 ............................................................... 3 Figure 1-2: School Enrolment by Age and Quintile, 2003/04 ...................................................................... 6 Figure 1-3 : Prevalence of Child Labor, Peru and LAC ................................................................................ -6 Figure 2-1: Recent trends in S S N spending in real terms ........................................................................... 15 Figure 2-2: Public Spending on Social Sectors in the LAC Region ........................................................... 15 Figure 2-3 Peru’s SSN Spending as % of GDP, with regional and global comparators ............................. 16 Figure 2-4: Modeled impact on the poverty gap of increased targeting o f SSN spending toward extreme poor ............................................................................................................................................................. 17 Figure 2-5: Distribution of Vuso de leche beneficiaries by quintile and area o f residence ...................... -21 Figure 2-6: Probability o f receiving Vuso de Leche by age and area of residence .................................... 21 Figure 2-7: Frequency of delivery o f Vuso de Leche benefits in rural and urban areas ............................. 22 Figure 2-8: Trends in the composition of VdL beneficiaries, 2001-2003 .................................................. 22 Figure 2-9: Distribution of beneficiaries ofA Trubujur Urbuno by consumption quintile, 2003 ............... 23 Figure 2-10: FONCODES’s geographic targeting progressiveness, compared with other social funds ..... 25 Figure 2-1 1 : The distribution o f Central Government transfers to sub-national governments, 2006 ......... 26 Figure 2-12: FONCODES investment in real terms ................................................................................... 27 Figure 2- 13 : Juntos targeting process: geographic selection, household assessment, and community validation .................................................................................................................................................... -28 Figure 2-14: Departmental poverty and extreme poverty rates, 2006 ......................................................... 29 Figure 2- 15: Reduction in Juntos’ Inclusion and Exclusion Error with an Improved Prediction Model .... 33 Figure 2-16: Juntos’ Simulated Impact on the Extreme Poverty Gap ......................................................... 34 Figure 2-1 7: Juntos’ Simulated Impact on Reducing Chronic Malnutrition ............................................... 36 Figure 3-1: Coverage and benefit levels of Peru’s SSN Programs compared with LAC ............................ 38 Figure 3-2: Targeting performance o f selected Latin American food programs ......................................... 41 Figure 3-3: Targeting Performance of selected Cash Transfer programs and Peru’s food programs ......... 42 Figure 3-4: The Simulated Impact o f SSN Programs on Poverty reduction ............................................... 43

TABLES Table 1-1: Poverty and extreme poverty in Peru. 1997-2006 ....................................................................... 2 Table 1-2: Circumstances Aggravating Poverty and Leading Indicators of Deprivation by Main Age Group and Quintile ........................................................................................................................................ 7 Table 1-3: Circumstances Aggravating Poverty and Leading Indicators of Deprivation by Main Age Group and Quintile ........................................................................................................................................ 8 Table 1-4: Incidence of Extreme Poverty ..................................................................................................... 9 Table 1-5: Distribution of Extreme Poor by Type o f Household .................................................................. 9 Table 2-1 : Social Protection Spending 2006 ............................................................................................... 12 Table 2-2: Public Spending on Social Sectors, 1997-2007 (% o f GDP) .................................................... 14 Table 2-3: Fiscal Position and Social Assistance Spending in Latin America, 2000-2001 ....................... 16 Table 2-4: Juntos Conditionalities .............................................................................................................. 31 Table 2-5: Juntos PMT Algorithm: Inclusion and Exclusion Errors ........................................................... 32 Table 2-6: Juntos’ Simulated Impact on Poverty Headcount, Gap and Severity ........................................ 35 Table 2-7: Chronic malnutrition rate, children zero to five ........................................................................ 35 Table 3-1: Household-level coverage o f Peru’s food programs ................................................................. 39 Table 3-2: Food programs’ coverage o f their declared target populations ................................................. 40 Table 3-3: Incidence o f Peru’s food transfers on consumption ................................................................... 40 Table 3-4: Targeting accuracy: Share of public transfers reaching each quintile ....................................... 41

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Acknowledgements

This report was prepared by Cornelia Mihaela Tesliuc and Ian Walker (LCSHS) with the help of a team o f consultants consisting of Lorena Alcazar and Rodrigo Lovat6n (decentralization o f basic social infrastructure and community kitchen programs), Pedro Francke (decentralization o f social programs), Anja Linder (review of social protection programs), and Juvenal Diaz (benefit incidence of social safety net programs). Pablo Lavado, Carmen Osorio and Andrea Portugal (JPAs, World Bank, Lima) provided invaluable assistance in conducting research and analysis.

The Propuesta Ciudadana group undertook a qualitative data research that contributed in-depth information on empowerment, participation, and service delivery. The team would l ike to thank the representatives of community based organizations and local authorities in 18 provincial and district municipalities in the departments o f San Martin, Cusco, and Piura for their effort and contribution during interviews and focus group discussions.

The work benefited from valuable comments, suggestions and peer review by Margaret Grosh, Laura Rawlings and Edmundo Murrugarra. Valuable comments were received from Daniel Cotlear, Helena Ribe, Kathy Lindert, John Newman, Carolina Sanchez Phramo, and David Warren.

The authors would like to thank the staff o f MEF, Juntos and MIMDES (in particular PRONAA) for providing much o f the data used in this analysis. We would also like to thank MEF for providing detailed comments on the draft final report.

The work was greatly enriched by the suggestions and comments o f participants in three workshops, in Lima, O f particular value were contributions from Cecilia Blondet (Instituto de Estudios Peruanos), Roxana Garcia Bedoya (Mesa de Concertaci6n para la Lucha contra la Pobreza), Juan Chacaltana (CEDEP), Marfil Francke (DFID), Martin Tanaka (Instituto de Estudios Peruanos), and Martin Valdivia (GRADE). In addition, we would like to thank Livia Benavides, Betty M. Alvarado and Erika Bazan (World Bank Office - Lima) for their collaboration in the publication of this book.

V

SUMMARY

This report - which forms part o f the World Bank’s Programmatic Analytical and Advisory Activity, RECURS0 2 - appraises the scope and performance o f Peru’s Social Safety Net (SSN) system and recommends a strategy for i t s future development. The report aims to contribute to the Government’s plans to rationalize social programs, by proposing a strategic fi-amework, within which programs can be made more efficient and effective, with clear objectives and strengthened accountability frameworks, differentiated between rural and urban sectors.

Chapter 1 provides an analysis o f the pattern o f exclusion and vulnerability in Peru, which highlights the following key issues: child malnutrition (affecting 26 percent o f all under fives, or around 750,000 children); low education cover and high child labor among poor children (in the poorest quintile, 26 percent o f children aged 10-14 are out o f school and 53 percent are working); and old age income insecurity (78 percent o f all elderly people have no pensions).

Chapter 2 provides an overview o f Peru’s Social Safety N e t (SSN) programs, their beneficiaries and spending trends. Peru has a plethora o f programs - mainly food programs - which accounted for 0.68 percent o f GDP in 2006, down from 0.96 percent in 1999. This i s a relatively low level o f social assistance spending, relative to national needs or compared with regional benchmarks. Nearly half o f the total (0.3 1 percent o f GDP) goes on food programs, the biggest o f which are: Vas0 de Leche (0.13 percent o f GDP); school breakfasts (0.06 percent), and community kitchens (0.04 percent). A further 0.07 percent o f GDP i s spent on the workfare program, A Trabajar Urbano; 0.24 percent on Social Funds; and 0.06 percent on the new CCT program, Juntos; the latter i s set to roughly double in size in 2007. The chapter analyses in detail four major programs, which account for over 80 percent o f SSN spending: the food program, Vas0 de Leche; the social fund, FONCODES; the workfare program, A Trabajar Urbano; and the rural conditional cash transfer program, Juntos -identifying their main strengths and weaknesses.

Chapter 3 presents an in-depth benefit incidence and poverty impact analysis for food transfer programs, which have historically been Peru’s predominant form o f transfer to poor households. I t shows that - although their poverty targeting i s reasonably good - they contribute relatively l i t t le to reducing either poverty or malnutrition. The main reasons for the negligible poverty impact are the low overall level of spending; and the fact that the resources are spread too thinly. There were 27 different food based programs operating in Peru in 2004; and only one o f them had a monthly benefit above US$4. There are major problems with the effectiveness o f large programs, such as Vas0 de Leche and Community Kitchens, which are made difficult to fix by their “ownership” by their existing beneficiaries, such as the Cornitis de Vas0 de Leche. Driven by such political economy dynamics, few o f Peru’s food programs reflect best practice in their technical design. Their low nutrition impact i s due to not being focused on young children, and being too centered on food distribution instead o f monitoring growth and showing mothers to how to feed and care for their babies.

Chapter 4 summarizes the main challenges and recommends a strategy to strengthen the S S N in Peru. It argues that the limited impact o f Peru’s SSN programs to reduce poverty or malnutrition i s the result o f a generalized “low quality equilibrium” in the social assistance and nutrition sector, which i s rooted in the lack o f clear objectives and measurable goals. This has opened the way for the “capture” o f programs by interest groups, and for their political manipulation. One reflection o f this i s the plethora o f programs; another i s the generally derisory value o f the benefits. In an effort to satisfy more and more client groups, the available resources are spread too thinly among small, low-benefit interventions, limiting their impact.

The mediocre performance o f Peru’s SSN programs has reinforced the low overall level o f social assistance spending. The Ministry o f Economy and Finance (MEF) has become skeptical o f approving “more o f the same”, setting up a vicious circle in which insufficient funding and poor program

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specification lead to weak impacts - which, in turn, undermines the case for more funding. To date, the decentralization process has done little to help resolve these problems.

To break out o f the low quality equilibrium, the report recommends establishing clear objectives and quality standards, and setting targets for improved outcomes. Program accountability should be strengthened through robust monitoring and evaluation systems. This line o f action i s now being pursued through the work o f the Results Based Budgeting (RBB) office in MEF and the social program optimization process (both supported by the World Bank’s REACT DPL series). The latter has already managed to reduce the number o f social programs in Peru to a third o f the previous level. The report suggests that this process should now focus on improving the effectiveness the major programs such as Vas0 de Leche, Comedores Populares, School Breakfasts, FONCODES and Juntos, which account for almost three quarters o f the resources used in the SSN sector.

The report argues that the SSN reform process needs to be anchored to a coherent national social safety net and poverty reduction strategy. The report suggests that the SSN interventions should be differentiated, as appropriate, between the urban and rural parts o f Peru. For instance, workfare programs to deal with cyclical unemployment only make sense in urban areas; and a nationally-led small-scale infrastructure program (such as FONCODES) only makes sense for rural areas. The Report also argues that the implementation arrangements for the SSN strategy should be differentiated for rural and urban areas, due the differences in capacity between the municipal administrations in the major cities and the rest o f the country. In the 30 biggest cities, SSN programs should be decentralized, to ensure better responsiveness to local needs and improved transparency. In the rest o f the country, for the foreseeable future, strong national agencies wil l be needed to ensure that SSN programs are effective, but they should work with local governments, as appropriate.

In both urban and rural areas, the report argues that the central, strategic goal o f SSN programs should be to tackle child malnutrition, which was identified in the analysis o f vulnerability and exclusion (presented in chapter 1) as Peru’s predominant Social Protection challenge. This point o f view was emphatically endorsed by President Garcia in his recent review o f the Government’s strategy, where he characterized the fight against chronic infant malnutrition - under the auspices o f Plan CRECER - as “the central objective o f the Government”’. Chronic malnutrition affects over a quarter o f the under-five population nationwide, or around 750,000 children. This level o f incidence i s extremely high for a middle income country such as Peru. It brings in i t s trail irreversible lifelong consequences, in the form o f physical and cognitive deficits in human capital accumulation, and engenders a vicious circle o f inter-generational reproduction o f poverty, vulnerability and exclusion. A significant reduction in chronic malnutrition would have enormous benefits for the affected households and communities, reducing poverty and vulnerability and improving distributional equity. And Peru as a whole would benefit from improved quality labor supply and stronger growth potential.

The lack o f progress on child malnutrition in recent years reflects the failure o f public policy to provide effective nutritional services and programs. For this reason, the report argues that the new SSN’s standards and accountability system should place a heavy emphasis on nutrition outcomes. The relevant programs (including Juntos and all the feeding programs) should be focused on nutrition outcomes. They should be held accountable for what they achieve to improve the quality and effectiveness o f growth monitoring, improve diets and reduce malnutrition among children under-five in their respective target populations.

’ Discurso del Presidente Constitucional de la Repdblica Dr. Alan Garcia Pkrez, 28 de julio 2007.

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I n rural areas (understood here to mean the whole country outside the 30 largest cities), the strategic focus o f the S S N should be on tackling chronic malnutrition among children under five. The rural strategy would need a strong national leadership, in coordination with the regional authorities.

0 Juntos should be re-focused on reducing chronic malnutrition, becoming the central program in the rural SSN. About a quarter o f Peru’s children are stunted. Changing this outcome wil l require increased parental awareness o f the problem, improved understanding o f good nutrition; and the economic wherewithal to turn this into improved feeding practices. Juntos could have a major impact on these issues. I t offers substantial cash benefits ($30 per month) to beneficiary families, significantly improving their consumption capacity. It can require beneficiaries to participate in MINSA’s nutrition monitoring and counseling sessions; and can support MINSA to improve those services. And it i s well targeted on communities with high malnutrition problems: during 2007, it wil l reach around 600 districts, covering 10 percent o f the national population - but almost 40 percent o f stunted children.

FONCODES (or i t s successor entity) should continue with the role o f supporting municipal development through the financing and construction o f small-scale infrastructure. Many rural municipalities will need such support for the foreseeable future. In the absence o f such an agency, the government’s “investment shock” runs the risk o f sidelining areas with low implementation capacity.

I n the 30 largest urban centers, where municipal capacity i s greater, SSN programs should be decentralized. The financing o f decentralized SSN programs should be supported by fiscal transfers, based on transparent, equitable criteria (poverty and population statistics). The government should encourage transparent decision-making by the municipalities, through requirements for budget consultation, participatory monitoring o f budget execution and the strengthening o f local poverty maps.

A decentralized administration, coupled with a strong accountability framework, will open up spaces for the reform o f existing programs (such as Vuso de Leche) where political economy factors have made sweeping national-level reform difficult to achieve. Once some local governments have decided to improve the targeting o f their programs and can show better outcomes, the demonstration effects of benchmarking those results will generate increasing pressure on other municipal governments to do likewise. And at a local level, the authority and credibility o f municipal governments may offset opposition to reform from the entrenched interest groups.

At a programmatic level, the strategic foci o f the urban S S N should be (a) re-distributional food transfers focused on poor children, to alleviate poverty and improve nutrition outcomes, and (b) an effective safety net mechanism to deal with labor market shocks.

0 Urban food programs should be rationalized. The Registro Unico de Benejkiurios (RUB), being developed by MIMDES-PRONAA, should be used to eliminate duplication o f beneficiaries and clear the way for program fusion. Food programs should also strictly apply the ru les on the definition o f eligible beneficiaries (e.g. limiting milk distribution to children under 6, as specified in the Vuso de Leche law).

A Trubujur Urbuno should be kept in place as a countercyclical program, to cushion households against temporary unemployment during cyclical downturns. I t should be operated at a minimum level during normal times, but retain the capacity to scale up quickly during recessions or in the aftermath o f disasters.

These strategic orientations would clarify the objectives o f the SSN, as a basis for establishing quality standards and measurable goals for each program, and strengthening their accountability, through robust monitoring and evaluation systems.

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1 THE PATTERN OF EXCLUSION AND VULNERABILITY IN PERU

1. This chapter frames the analysis o f the report by asking the questions: “why operate SSN programs?” and “for whom?” Section 1.1 discusses the general rationale for SSN programs. Section 1.2 shows how poverty and malnutrition have remained severe in spite o f the recovery o f economic growth, underlining the need for programs to protect the most vulnerable to accelerate the reduction o f poverty. Section 1.3 analyses the distribution o f vulnerability and exclusion in Peru, by income quintile and by age. It identifies among the most vulnerable groups, children in extremely poor households, who are vulnerable to multiple sources o f deprivation, likely to endanger their future development. It also highlights the need to address exclusion from school and high unemployment among young adults; the lack o f social insurance in the adult populations; and income insecurity for old people with no pension rights.

1.1 Why do societies need social safety nets?

2. Social safety nets are public programs that redistribute resources to the poor or vulnerable groups, thus protecting people from the worst effects o f poverty. They include cash transfers, food assistance programs, workfare, subsidies o f various types and programs that ensure the access o f the poor to essential public services, such as school vouchers or scholarships; fee waivers for health care services; and social funds. Social safety nets are only one element o f social protection policy. The other element (not dealt with in this paper) i s social insurance programs, such as contributory pensions or unemployment insurance, which need not include any re-distributional element.

3. There are two main reasons why societies need social safety nets. First, S S N programs are a short term solution to alleviate poverty and destitution in society. As i s well known, a sustainable reduction in poverty over medium to long-term requires broad-based growth, together with human capital investment which reaches the poor (especially in education, health, and access to basic services). However, such outcomes may take years to achieve. In the meantime, social safety nets are often the only available policy instrument to ameliorate the debilitating effects o f extreme poverty.

4. Second, SSN programs can help households manage risks better. Risk i s part o f everyone’s life, but i t s impact on the poor and vulnerable groups such as the elderly and disabled, i s often more severe than for others in society. Risk can materialize at household level (Le. illness, disability or death and unemployment), community or regional level (Le. floods, famine) or nationwide (Le. drought, global financial risks, shifts in terms o f trade). The adverse impact i s often more damaging to the poor than to those with better endowments o f income, physical and mental well-being and o f long-term human development. Poor people who lose income may be forced to sell land, livestock or their tools, undermining future earnings potential, or to pull their children out o f school and send them to work; or simply to eat less. Such reactions may help families survive from day-to-day, but will often make it harder for them to escape poverty in the future. An effective social safety net can reduce the need to resort to such dysfunctional coping strategies.

5. Social safety nets can help to increase options for the poor. The knowledge that safety nets exist may open the way to take initiatives that incur risks but bring potentially high returns. Crop insurance can encourage farmers to grow higher yield varieties o f crops and using modem farming methods; employment guarantees made possible by workfare programs may encourage households to concentrate their labor on the highest return activities rather than working in diverse activities and earning less; and the knowledge that the government will provide assistance in bad times might encourage households to hold assets in more productive, but less liquid ways (such as investing in micro-enterprises rather than keeping cash under the mattress for a rainy day).

6. The existence o f credible and effective safety nets can also facilitate more effective economic policies by making it easier to generate consensus around the need for reforms that generate losers as well

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as winners. They can broaden support for sound fiscal and trade policy, and allow other social programs to concentrate on efficiency rather than equity goals. For example, if sound safety nets are in place, the pension program can focus on improving the efficiency o f providing benefits to contributing workers, rather than finding ways to provide cash transfers to those who have not made adequate contributions.

7. The traditional role o f SSN programs has been to redistribute income and resources to the needy, helping them to overcome short-term poverty. But a new generation o f SSN programs, called conditional cash transfer programs, includes mechanisms to help poor households escape from poverty. These subsidies are conditional on families investing in their children’s human capital, through school attendance or regular use o f preventive health care services. Thus, they help reduce future poverty.

1997 1998 1999 2000

42.7 42.4 47.5 48.4 25.4 24.1 31.4 38.9 33.0 34.0 37.3 35.3 66.3 65.9 71.8 70.0

18.2 17.4 18.4 15.0 2.3 2.4 2.7 1.6 7.6 7.5 6.3 6.1

1.2 The resilience of poverty and inequality in Peru

8. Peru faces high levels o f poverty and inequality. Based on the most recent available data (from the 2006 ENAHO survey), about 45 percent o f Peru’s population i s poor and 16 percent i s extremely poor (Table 1-1). Based on data from 2003, inequality, measured by the Gini coefficient o f consumption per capita, stands at 0.42-below the Latin American average o f 0.52 but much higher than the average for middle income countries o f 0.30.

9. Despite economic growth, progress in combating poverty stalled between 2000 and 2005, but a strong reduction in poverty was registered in 2006. As a consequence o f the 1998 economic crisis, poverty increased by 7 percentage points between 1997 and 2001. The recovery o f growth after 2000 halted this deterioration, but only began to reverse it in 2006. However, the 44.5 percent poverty rate registered in 2006 st i l l remains above that o f 42.4 percent which was registered in 1998. Similarly, extreme poverty has only improved modestly in recent years, falling from 19.5 percent in 2001 to 16.1 percent in 2006. The problem o f poverty i s particularly acute in the rural parts o f the country, especially in the sierra, where almost 80 percent o f the population i s poor and more than half i s living in extreme

2001* 2002 2003 2004 2005 2006

49.8 50.0 52.2 48.6 48.7 44.5 28.3 34.3 33.7 30.9 32.6 24.2 42.6 39.0 39.5 37.1 36.8 31.2 76.9 74.3 75.7 69.8 70.9 69.3

19.5 18.7 n.a. 17.1 17.4 16.1 1.7 3.3 n.a* 1.3 2.0 0.9

10.0 8.2 n.a* 6.5 6.3 4.9

poverty (data not tabulated).

Ta -

Poverty headcount National Metropolitan Lima Urban Rural Extreme poverty National Metropolitan Lima Urban Rural I 41.5 40.0 44.4 35.6 I 46.3 42.4 n.a. 36.8 37.9 37.1 Source: INEI . *The methodology for estimating the poverty rate in Peru was changed in 2001; as a result the estimates for 2001-2006 are not comparable with earlier estimates; in addition, poverty rates between 2001-2003 are not comparable to 2004-2006.

10. Progress in combating malnutrition has also stalled. According to DHS data, a quarter o f children under-five are malnourished on the height-for-age indicator (chronic malnutrition) and there i s a strong correlation between stunting and income poverty (Figure 1-1).

1 1. The World Bank’s Poverty Assessment (2006) identifies four main reasons for the limited progress in reducing poverty in Peru:

Since 2000, growth and investment have not been sufficiently strong and broad-based to bring the overall poverty rate down. They have been biased towards capital-intensive sectors, limiting

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employment creation, and have had only a modest impact among the poorest households, especially in rural areas. In urban areas, low productivity among small f i rms in the informal, labor-intensive sectors has limited employment and real wage growth. Recent improvements in employment and wage levels in urban areas were mostly concentrated among medium and large f i r m s and among the highly skilled. In rural areas employment has increased, especially in the agricultural sector, although due to low productivity levels in the sector, wage levels have remained flat. L o w asset endowments (human and physical capital) and poor access to financial and insurance markets and to effective safety nets increase the exposure o f poor people to shocks, limiting the effectiveness o f their coping strategies. As a result, they are more vulnerable to economic downturns, such as the 1998 crisis, and less able to benefit from the opportunities generated by periods o f growth. Limited access to public services, infrastructure and public institutions, particularly in rural areas, has reinforced inequalities in social and economic opportunities between the poor and the non-poor.

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Figure 1-1: Malnutrition by expenditure quintile, 1996 and 2001

45 - 40 -

Share of stunted children % ofchildren under 5 whose height for age IS e-2 sd z-score

50 45 40

r: 35 0

30

25 9 20 0 % 15

10

5 0

Q1 Q2 Q3 Q4 Q5 Total I ea 1996 2000 I

_,

Q1 Q2 Q3 Q4 Q5 Total

1 1996 IB 2000 1

Source: Gwatkin Rutstein Johnson, Suliman, Wagstaff, and Amouzou, “Socioeconomic Diferences in Health, Nutrition, and Population in Peru”, 2nd ed. Washington, D.C.: The World Bank, forthcoming. Note: Wealth quintiles based on an index o f household endowment with assets.

12. Economic growth has now recovered strongly and looks set to stay high. In this setting, the critical challenge for Peru i s to ensure that this recovery o f economic growth leads to sustained poverty reduction and improved equity. Output in the economy has been growing for five consecutive years, reaching 6 percent in 2005, the fastest rate since the mid-1980s and around 4.5 percent in 2006 (INEI, 2006). Growth has been driven by investments and improved export performance in extractive industries, with Peru benefiting from high world prices for minerals. However, the links from growth to poverty reduction in Peru have been relatively weak, as growth and investment have been biased towards sectors with low labor intensity (such as mining). In addition, historically volatile growth rates have resulted into high levels o f uncertainty and low levels o f entrepreneurial confidence on the sustainability o f growth (Peru Poverty Assessment, 2005).

Urban economy: The main beneficiaries o f urban growth are those working in larger companies, where wages are higher and workers have access to social security benefits. For example, pay in companies with more than 50 workers rose by 6.3 percent in 2004, whereas pay in the smallest f i r m s (with fewer than 10 workers) increased by 1.3 percent. However, three-quarters o f urban workers are employed in small and medium-sized f i r m s and barely a quarter are in f i r m s with 50 or more employees.

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Rural economy: Some dynamic sectors o f agriculture have taken advantage o f rising domestic consumption and strong overseas demand for asparagus, mangoes, lemons and other f ru i ts and vegetables. However, the growth areas are concentrated mostly on the coast, and only account for a small proportion o f the rural workforce. As a result, rural poverty levels remain stubbornly high (about 70 percent), and extreme poverty stands at 37.1 percent (Table 1-1).

13. The present report provides an in-depth assessment o f ways in which Peru’s social safety net could be made better targeted and more effective. This complements the 2005 Poverty Assessment which estimated the potential impact on poverty levels o f a broad set o f policies, including a more efficient social safety net, but also including adequate taxation policies and well-targeted, effective programs in health, education, basic infrastructure and utility services.

1.3 Who Nee& SSN Programs? A profile of vulnerable groups in Peru. 14. Consumption-poverty in Peru correlates strongly with other dimensions o f poverty, such as malnutrition, child labor, school drop-out, and illiteracy. The “life-cycle approach” developed by Hal l and Arriagada2 i s commonly used to identify key vulnerable groups. Under this approach, the population i s classified into age-groups: early childhood, school-age, youth, adulthood and old age. For each age-group, the circumstances that lead to or aggravate poverty and deprivation3 are identified. Finally, the prevalence o f specific deprivations (such as malnutrition, child labor, illiteracy or unemployment) i s presented by consumption or wealth quintile, to assess to what degree it i s concentrated among the extreme poor. Using this approach, Table 1-2 presents data on the incidence o f different r isks in Peru, by age group and consumption quintile; and Table 1-3 shows the number o f individuals who are affected. The information was derived from the most recent surveys available, ENAHO 2003 for material poverty, and DHS 2000 for malnutrition or health risks, and classified into age groups and quintiles4.

15. The main risks identified in this analysis are as follows: 0 For the 0 to 5 age range; malnutrition (deficient height for age, or stunting, affects 26 percent

o f all children under five, and 47 percent in the lowest quintile, Q1, compared with only 5 percent in the richest quintile, Q5); child mortality (64 per thousand in Q1, compared to only 14 for Q5); lack o f access to preschool education (only 39 percent o f children 3 to 5 years old in Q1 are enrolled, compared to 75 percent in Q5). For children aged 6 to 16: low school enrollment (1 1 percent o f children aged 6 to 1 1 in Q 1 are not in school); high school dropout among older children (26 percent o f children aged 12 to 16 in Q1 are out o f school, compared to 8 percent in Q5); late entry to the secondary cycle (affecting 33 percent in Q1) and a high incidence o f child labor (affecting 53 percent o f those aged 10 to 14 in Ql). For youth aged 17 to 24: low rates o f school enrollment, particularly among the poorest quintile (76 percent o f youth in Q1 are not in school compared to 50 percent in Q5); relatively high youth unemployment rate (15 percent, compared to 8 percent for al l adults) and high inactivity rates among the urban youth. For the adult population between the ages of 25 and 64, the lack o f social insurance protection i s the main issue. Ninety nine percent o f the extreme poor (Q l ) do not have social insurance.

0

0

Hall and Arriagada (2001) in Mexico: A comprehensive development agenda for the new era, World Bank, Washington DC.

Poverty i s defined in a multidimensional sense, encompassing such variables as consumption, nutrition, education, health, child labor and employment.

The indicators derived from ENAHO 2003 are classified using quintiles of real consumption per capita, while those derived from DHS 2000 are based on wealth quintiles. For DHS information, see Davidson R. Gwatkin, Shea Rutstein, Kiersten Johnson, Eldaw Abdalla Suliman, Adam Wagstaff, and Agbessi Amouzou, “Socioeconomic Diferences in Health, Nutrition, and Population in Peru”, 2nd ed. Washington, D.C.: The World Bank, forthcoming.

4

4

Employment in poor quality jobs (unremunerated household work or paid employment at very low wages) i s also a key issue. Illiteracy stands at 22 percent in Q1, compared to 12 percent national average). Among the over 65 age group, income insecurity i s the main problem: overall, only 22 percent o f the elderly have a pension and this falls to less than 5 percent in Q1. This may explain the high share o f elderly who work (51 percent o f the elderly in Q1 work, compared to only 27 percent o f those in Q5).

0

16. The life-cycle analysis presented in Table 1-2 and Table 1-3 suggests that the group with the highest risk o f poverty and other forms o f material deprivation are children living in extreme poverty. Children are the age group with the highest incidence o f poverty, and constitute the largest group o f poor (children under 14 represent 47 percent o f the extreme poor). A majority o f poor children are also affected by forms o f deprivation other than consumption poverty, such as high rates o f infant mortality, malnutrition, school dropout, or low academic achievement. Infant mortality reaches 64 per 1,000 in the poorest quintile, more than twice that in the richest quintile (average o f 28 per 1,000 in the region).

17. Of particular note i s the extremely high rate o f chronic malnutrition (stunting) in Peru. Chronic malnutrition currently affects over a quarter o f the under-five population nationwide (around 750,000 children) an extremely high level o f incidence i s extremely high for a middle income country such as Peru. The stunting rate rises to 47 percent among children from extreme poor households; such children accounted for 53 percent o f the total cases in the country in 2000. Chronic malnutrition brings in i t s trail irreversible lifelong consequences, in the form o f physical and cognitive deficits in human capital accumulation, and engenders a vicious circle o f inter-generational reproduction o f poverty, vulnerability and exclusion. A significant reduction in chronic malnutrition would therefore have enormous benefits for the affected households and communities, reducing poverty and vulnerability and improving distributional equity. And Peru as a whole would benefit from improved quality labor supply and stronger growth potential.

18. Access to education services, although improved substantially in recent decades, also fails the poor. About one-third o f the students from the poorest quintile (in extreme poverty) do not complete primary education by age 14. There i s a marked difference between the school enrollment rate for children from the poorest quintile and other children (Figure 1-2). The poorest children jo in primary school later, repeat grades more often, and drop out earlier. This may be indicative that the efforts o f the Government o f Peru on the supply side (better school infrastructure, and better supplies) are not enough - there i s also a need to address the issue o f demand-side constraints to the accumulation o f human capital in the poorest households.

5

Figure 1-2: School Enrolment by Age and Quintile, 2003/04

100%

90% - 0 z 80% v1 p 70%

c 5 60%

3 50% E

40% s

30%

I

U

c

20% I

6 7 8 9 10 11 12 13 14 15 16 17 18

Age

--e I-poorest -1)- 2-4 5-richest

Source: Author’s estimations based on ENAHO 2003/04.

19. Lower school participation o f children from extreme poor households i s correlated with high prevalence o f child labor. According to the Inequality in L A C Flagship Report, child labor i s substantially higher in Peru than the L A C region average: more than a quarter o f children work in Peru, compared to only 11 percent in LAC. Even more striking i s the high incidence o f child labor in extreme poor households, where 53 percent o f children work, compared to the L A C average o f 17 percent (Figure 1-3).

Figure 1-3: Prevalence of Child Labor, Peru and LAC

Child labor is widespread in Peru

Peru LAC Average

Source: “Inequality in Latin America: Breaking with History”, World Bank (2004).

6

m a

v w C $ . u m In

20. For rural girls, the phenomenon o f child labor i s often compounded by other forms o f exploitation. Many are sent at a very young age to work as domestic employees in the cities, where they work long hours, are severely underpaid and are often physically abused (Vega, 2001). In an effort to address this problem the Government has signed international agreements protecting children rights, introduced legislation that prohibits child labor and created a special department within MIMDES and an inter- sectoral commission to enforce the legislation. However, since the causes o f child labor are mainly economic, legal prohibition, alone, i s unlikely to end it.

Table 1-4: Incidence of Extreme Poverty

(Total I 8.0 I 37.9 I 18.3 I 8.1 I 42.9 I 20.8 I 8.0 I 40.2 I 19.4 I Source: Author’s estimation based on ENAHO 2003, annual sample.

21. The second largest group o f extremely poor people in Peru i s the working poor (37 percent o f the total). Among this group, the incidence o f extreme poverty highest in rural areas, especially in the informal sector, such as independent workers and non-salaried household labor (see Table 1-4). The main circumstances leading to extreme poverty for this group are low-wage jobs coupled with high ratio o f dependents to working adults in the household. In contrast, extreme poverty i s virtually absent for non- manual workers, and i s also low for manual workers in urban areas. Rural and female wages are substantially lower compared to urban or male wages.

22. The two largest vulnerable groups - children and working-age adults in extreme poverty - overlap substantially in the same households, so programs to support children would also help their working parents, and vice-versa. About 94 percent o f the extreme poor (Ql ) live in households with children and where at least one adult i s working; and in 68 percent o f Q1 households, all adults in the household are working. However, 1 percent o f the extreme poor live in children-only households which need Government assistance through special programs (Table 1-5).

Table 1-5: Distribution of Extreme Poor by Type of Household Type o f Household YO Adults, all working, with children Adults, not all working, with children

68 26

2 Adults only, all working 4 Adults only, not a l l working Children-only households 1 Total 100 *) Children are defined as 14 years old or younger

Source: Author’s estimation based on ENAHO 2003 (INEI), annual sample.

9

2 THE SOCIAL SAFETY NET IN PERU

23. This chapter provides an overview o f the main social safety net (SSN) programs in Peru. Section 2.1 describes the programs that constitute the social safety net in Peru. Section 2.2 shows that the SSN spending i s low, compared to other countries in the L A C region. S S N spending i s also small compared with the poverty gap o f the extremely poor households in Peru. The last section (2.3) highlights some o f the weaknesses in the design o f SSN programs.

2.1 Main Components of the Peruvian Social Safety Net 24. Historically, the Peruvian SSN has been built around three types o f program: (a) a large and disparate set o f feeding programs, with diverse target groups and varying objectives; (b) a social fund, FONCODES, which finances basic social infrastructure and income-generating projects in poor rural communities; and (c) workfare programs, which offer temporary employment. In 2005 a new program - Juntos - was introduced in the poorest districts in rural Sierra in four departments to provide conditional cash transfers to poor families with children. Table 2-1 summarizes the main programs’ expenditure, number o f beneficiaries and benefit levels in 2006. In all, SSN spending totaled S 1,898 mill ion Soles, amounting to 0.68 percent o f GDP. Fourty six per cent o f the total (0.3 1 percent o f GDP) was for food programs, 10 per cent o f the total (0.07 percent o f GDP) was for workfare, 35 per cent o f the total (0.24 percent o f GDP) was spent on social funds and 9 percent o f the total (0.06 percent o f GDP) was for the Juntos CCT program.

25. Two striking characteristics o f the Peruvian S S N are the existence o f programs controlled by community entities - often without strong targeting or accountability frameworks - and the high level o f programmatic disintegration: in a diagnostic undertaken in 2006, the Government identified 82 separate social programs. Box 2-1 provides a summary o f the historical roots o f the Peruvian SSN model, which explains the origin o f community-run programs as a response to a vacuum left by the lack o f government- led social programs in a context o f distrust engendered by dictatorial governments in the 1990s. This, in turn contributed to programmatic disintegration, as governments sought to meet the demands o f as many interest groups as possible. Another factor in program disintegration in past years was donor funding: in the face o f poor accountability frameworks, there was a tendency for donors to propitiate new delivery agencies, instead o f funding established national programs. The following paragraphs summarize the main elements o f the modern SSN’.

26. Food-based Programs. In 2004, 27 food-based programs were in operation in Peru (a full l i s t i s given in Annex 1). The largest programs in terms o f budget and number o f beneficiaries are the municipally-run Vas0 de Leche (glass o f milk) program for pre-school children; the school feeding programs (school breakfast and school lunch), and the community kitchen (Comedores Populares) for children and adults. There are several nutritional programs for infants and pregnant and lactating mothers but none i s very big. These programs reach, altogether 6.7 mill ion beneficiaries, or 25 percent o f the population, but the average subsidy per beneficiary i s only US$3.3 per month6. About 70 percent o f food programs’ resources reach the poor (the bottom 55 percent o f the population); and 30 percent goes to the extreme poor (the poorest consumption quintile).

27. The Social Fund. The National Compensation and Social Development Fund (FONCODES) was created in 1991 to finance small local investment projects. I t s stated objectives were: to generate

’ This study concentrates on the larger programs, which account for the lion’s share of SSN spending. The Peruvian SSN also includes important smaller programs, such as those for street children and disabled Peruvians, mainly operated by MIMDES.

The exception to the pattern of very low per capita food program benefits, spread very thinly, i s the Wawawasi program, which has much higher benefits (US$23 per month) but reaches relatively few children (40,000 nationwide). See Table 2- 1.

10

employment, help alleviate poverty, and improve access to social services. The projects financed by FONCODES are demand driven and involve the community in execution and supervision. The most popular projects are the construction or rehabilitation o f schools, health posts, water and sanitation systems, rural roads, secondary electrification schemes, and small-scale irrigation works. The social fund has been used to reach the poorest rural communities using poverty-map allocation methods and, in the past, it absorbed more resources than those channeled through programs that provide direct transfers to households (meals in the case o f food programs, or wages in the case o f workfare programs). At i ts peak, FONCODES’ annual budget stood at around 0.3 percent o f GDP. I t s relative importance has since declined somewhat, but it s t i l l amounted to 0.2 percent o f GDP in 2006. It remains the single biggest SSN program (30 per cent o f the total, S.567 million). However, i t s future i s now in question.

28. Worvare Programs. Two workfare programs have operated in Peru in recent years: A Trabajar Urbano and A Trabajar Rural. A Trabajar Urbano provides temporary employment opportunities for unskilled workers in poor areas, at relatively low wages. The program provides work for up to six months on temporary public projects undertaken to renovate social infrastructure and perform general community maintenance work. In 2006 it had a budget o f S/.187 million, which accounted for 10 percent o f SSN expenditure, and about 0.07 percent o f GDP. It reached 57,000 beneficiaries (about 0.2 percent o f the population). Program participants in A Trabajar Urbano obtain a monthly wage o f S/.300 (or US$91). This i s set considerably below the minimum wage o f S/.427 (US$129) per month in order to discourage the crowding out o f other employment. Nevertheless, it i s by far the largest benefit package o f any S S N project. In contrast, A Trabajar Rural i s a budget umbrella used to bundle ad-hoc interventions.

29. Conditional Cash Transfers. The recently introduced conditional cash transfer program, Juntos, provides a monthly benefit o f 100 Soles (about US$30) to poor families with children under 14 years old, conditioned on their take-up o f preventive health care visits, nutrition supplementation, school attendance, and obtaining birth registration and identification documents. The program started in the poorest 1 10 rural districts in the departments o f Huanuco, Huancavelica, Apurimac, and Ayacucho, benefiting about 70,000 households. By the end o f 2006, it reached 210 more districts in five additional departments, reaching about 160,000 households in all. The program’s cost was S/. 173 mil l ion in 2006, representing 9 percent o f SSN spending or 0.06 percent o f GDP. In 2007 it wil l cover 638 districts and over 400,000 households.

11

Table 2-1: Social Protecl

rota1 Social Protection Total Social Insurance, of which:

Pensions (SNP) Other pensions

Food-based programs Total Social Safety Net, of which '':

Glass o f Milk (Vas0 de Leche) Wawa Wasi (day care) School lunch (Almuerzos escolares) School Breakfast (Desayunos escolares) CEIPRONOEI (food supplement for preschool children) PACFO (food supplement for at risk children) PANFAR (food supplement for at risk family) Community Kitchen, food for work and shelters ' Others 3'

Total Workfare, of which A Trabajar Urbano

Total Social Fund I Community Driven Development FONCODES - basic social infrastructure investments ' PRONAMCHCS - natural resources management

JUNTOS 4'

Conditional Cash Transfers program

'ro Memoria '' Average monthly wage, urban area 2006 Average net wage - unskilled worker, urban area 2006 Minimum monthly net wage (SI.) 2006 GDP, mill. SI. 2006 " Population, 2005

n Spending 2006 Spending

mill. S.1 % o f GDI

10,522 3.76 8,624 3.08 3,837 1.37 4,788 1.71 1,898 0.68

877 0.31 363 0.13

46 0.02 26 0.01

182 0.06 37 0.01 49 0.02 13 0.00

105 0.04 56 0.02

187 0.07 187 0.07 661 0.24 567 0.20

94 0.03 173 0.06 173 0.06

2 8 0,2 0 5 7,219,264

lumber o f beneficiarie thousands % o f pop.

469 1.7 n.a

2,959 10.9 48 0.2

485 1.8 1,926 7.1

433 1.6 295 1.1

79 0.3 n.a n.a

57 0.2

n.a n.a

270 1 .o

tge benefivn s.1 US$ 6'

682 207

10 3 80 24

5 1 8 2 7 2

14 4 13 4

300 91

100 30

2600 781 32 1(

500 15:

Source: Based on data from INEI, SlAF - MEF (National and subnational government), DGAES - MEF, I / Administrative expenditures are not included (exception: Glass of milk, and FONCODES program executed by sub national governments) 21 Expenditures executed by National and Sub National Governments. 3/ It includes the following programs: Comedores infantiies, piloto subprograma infantil, equipos para el programa infantil y escolar, PEBAL, PROMANR, fundaci6n por 10s ninos, acta de compromiso, PANTBC, convenios, subsidios a comedores, situaciones de emergencia y programa de cooperaci6n internacional. 4/ Expenditures executed by PCM. 5/ INEI. 6/ Exchage rate: S1.3.3 7/ Own estimates based on historic growth.

12

Box 2-1: The historical roots of Peru’s SSN M o d e l Peru’s SSN model has strong roots in the community-based development initiatives and political mobilizations of the 1960s and 1970s. In this period, community based organizations (CBOs) grew up to occupy a vacuum le f t by the weak public sector, in a setting o f centralized dictatorship and endemic economic crises. Later, in the 1980s, they were institutionalized and co-opted into the political process.

Programs such as Vas0 de Leche and the community kitchens (comedores populares) started as informal initiatives o f poor communities, in the absence o f assistance from the government. The creation o f the comedores populares coincided with a social movement organized during the crisis o f 1976-1979. Following economic mismanagement by the Velasco Government, in 1976 a structural adjustment package was implemented, resulting in increased unemployment, inflation and reduced real wages. This reinforced popular opposition to the dictatorship and resulted in turmoil and strikes. In this context, hundreds o f community kitchens were set up in poor neighborhoods to feed the strikers.

The community kitchens continued operating into the 1980s, when Peru returned to democracy, but economic revival remained elusive. In 1983, a new crisis led to a 10 percent fal l in GDP and three-digit inflation. Against this backdrop, political parties competed for popular support by offering funding for the CBOs. Wh i le First Lady Violeta Correa offered support to the “cocinas populares”, Alfonso Barrantes, the left-wing mayor o f Lima, promised a mil l ion o f glasses o f milk for the children o f Lima, to be delivered through an extended network o f “comi tb de vas0 de leche”. The administrations o f Fernando Belaunde (1980-1985) and Alan Garcia (1985- 1990) strengthened government support to the community kitchens. Under the Direct Support Program (PAD) started by the f r s t Garcia administration, the “clubes de madres” in L ima and Callao were given a cash subsidy, in addition to the food transfers available to other community kitchens, a privileged status s t i l l maintained today. International donors were also supportive o f community-based initiatives.

In 1992, under the Fujimori administration, the National Food Assistance Program (PRONAA) was created to provide food assistance to rural and marginalized urban areas, and poverty alleviation was centralized under the Ministry o f the Presidency (PRES), leading to considerable political discretion in support to the different programs. This, however, did not resolve the problems o f fragmentation and overlap o f social programs and the decade o f the nineties saw growing corruption and clientelism.

As a result o f this complex historical process, a movement that had originated in the poor neighborhoods, founded on principles o f reciprocity common among indigenous communities, came to depend heavily on assistance f?om the national and local Government or national and international ONGs. As a well-organized mass o f people that could be mobilized quickly, the CBOs become a powerful political instrument and governments have nurtured their relationship wi th them. At the same time, the CBOs themselves have sought to cultivate their relationships wi th the government o f the day. This has become an accepted strategy for CBOs in modern Peru. Groups that do not receive state support do not condemn those receiving it, rather, they commend and envy their ability to hook up with public funding.

In recent years, the government has sought to reform the food programs and clarify their role within the social safety net. However, this has proved a daunting task, in the face o f resistance from long-time beneficiaries, mayors and the food producers who supply them. In 2001, wi th support from the IDB and the World Bank, the transition government improved the transparency and accountability o f food programs, and began unifying them by transferring the FONCODES’ infant and school feeding to the National Institute o f Health. In 2002, the Toledo government brought al l the central government food programs under one organization - PRONAA - and established a multi-sectoral Board o f Directors to improve l i nks wi th the education and health sector. The reform path set in 2002 included plans to further consolidate programs, improve their design by introducing health and nutritional components, to carry out impact evaluations and to develop a conditional cash transfers. However, t h i s centrally-led trajectory was interrupted in 2003, when Peru decided to pursue the decentralization o f food programs and basic social infrastructure investments. Now, the Garcia administration has launched a new program consolidation and optimization process for the social sectors, led by the Technical Secretariat o f the Inter-ministerial Commission for Social Affairs (ST-CIAS), which aims to consolidate programs and promote results-based-budgeting,

Adapted from Franke, P (2005) and A. Linder (2005).

13

2.2 Public spending on the Social Safety Net 30. Total social sector spending in Peru has been relatively stable in the last decade, averaging around 9 percent o f GDP. In 2004 Peru spent 3 percent o f GDP on education, 1.5 percent on health, 3.9 percent on social protection (which includes pensions and the social safety net, SSN). Within Social Protection, pensions’ spending predominates, accounting for 80 percent o f the total, leaving only 20 percent for the SSN.7 As well as being small, the SSN has shown a worrying tendency to be pro-cyclical. The economic crisis that hit the country in 1998 and the recession that followed found Peru unprepared to protect SSN spending, and the structure of social spending shifted strongly against the SSN. Wh i le spending on health, education and social insurance al l raised, SSN spending fe l l from 0.96 percent o f GDP in 1999 to 0.76 percent in 2004. (Table 2-2). This relative and absolute decline in SSN spending after 2002 i s attributable to reduced spending on workfare and in the food programs operating in the rural sierra. The reduced financing programmed for the social funds in 2007 should be offset by higher municipal and regional investment, in the context o f decentralization (Figure 2- 1).

Table 2-2: Public Spending on Social Sectors, 1997-2007 (YO of GDP) 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006* 2007*

Actual Actual Actual Actual Actual Actual Actual Actual Actual Actual Budgeted I. EDUCATION 2.53 2.65 2.96 2.87 2.88 3.04 3.11 3.00 3.06 3.07 3.06 11. HEALTH 1.27 1.34 1.39 1.35 1.37 1.45 1.51 1.50 1.52 1.67 1.58 111. SOCIAL PROTECTION 3.41 3.37 3.89 3.92 4.02 4.10 3.82 3.90 3.89 3.76 3.63

A. Pensions 2.52 2.63 2.93 3.16 3.25 3.35 3.17 3.10 3.18 3.08 2.97 B. Social Safety Net 0.88 0.74 0.96 0.76 0.77 0.75 0.65 0.76 0.71 0.68 0.66

B 1. Food-based Programs 0.40 0.36 0.41 0.40 0.48 0.43 0.39 0.40 0.37 0.31 0.31 B2. Workfare - 0.05 0.14 0.11 0.06 0.06 0.07 0.05 B3. Social Funds 0.48 0.38 0.55 0.36 0.24 0.18 0.15 0.30 0.24 0.24 0.17 B4. Conditional cash transfers 0.04 0.06 0.13

TOTAL 7.21 7.36 8.24 8.14 8.27 8.59 8.44 8.40 8.47 8.50 8.27

Source: Based on data fiom INEI; SIAF- DNPP (MEF); Pronamachs web; Perti en Ntimeros 1997 - 2004; PRONA; PAAG (MINSA), BCRP. * Uses estimates o f GDP based on historic growth.

3 1 . SSN spending in Peru i s low compared to other countries. Social spending i s lower in Peru than the average for Latin America in each of the three sectors: health, education and social protection. (Figure 2-2). The largest difference, though, i s that for social safety net spending. SSN spending in Peru i s among the lowest in LAC and well below that o f other regions. Peru spends barely half o f the LAC region average of 1.3 percent o f GDP and about one third o f the 2.2 percent o f GDP registered for OECD or Europe and Central Asia region (Figure 2-3). But, although it spends less, Peru’s S S N programs cover a much larger fraction o f the population than those of other countries in the region. This implies that the limited funds are diluted across a large number o f beneficiaries, resulting in average transfers which cover only a fraction o f the consumption deficit of poor households (Figure 2-4).

’ Almost 85 percent o f pension spending (about 2.6 percent o f GDP) i s subsidized with transfers fiom the central government. In 2004 the government undertook a Constitutional reform that will reduce the h ture liabilities o f the civil servants pension regime, gradually reducing the amount o f public subsidies required to fmance the public pension system deficit.

14

Figure 2-1: Recent trends in SSN spending in real terms

Social safety net spending f997 - 2006 (2004 constant prices)

80 I , 2000000

70

60

50 9

3

XI 40

5 30

20

10

0

v)

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1800000

1600000

1400000 2 0

Ly 1200000 5 1000000 ; 800000

2 600000 zf 400000

200000

0

0 Conditional cash transfers

Social Funds

Workfare

GK3 Food-based Programs

+Social safetynet spending per capita

Source: Based on data .from INEI; SIAF- DNPP (MEF); Pronamachs web; Perd en Nzimeros 1997-2004; PRONA; PAAG (MINSA), BCRP.

Figure 2-2: Public Spending on Social Sectors in the LAC Region Spending on health, education, social protection (social insurance and social assistance) as a share o f GDP, most recent year

Public Social Spending as a share of GDP: LAC, OECD

35 0%

30 0%

25 0%

20 0%

150%

100%

5 0%

0 0% GTM-OO DOM02 PER-03 MEX-03 COL-04- CHL-00 ARG-03 BRA-04- LAC U S -01 OECD-01 Continental

cons cons Average Europe41

Source: Lindert, Skoufias and Shapiro (2005).

15

Figure 2-3: Peru’s SSN Spending as % of GDP, with regional and global comparators

L..

8 - Morethan

= ? I 2 Between 2 P, a 19% and :$ $ 24% a n & ’ k Under

* * E 24%

a * C P

19% k m

32.

Share o f Total Public Spending going to SOCIAL ASSISTANCE (Fiscal Priority)

Less than 4.5% Between 4.5% and 7% More than 7% Colombia (0.9) Venezuela (1 .O) Nicaragua (1.1) Brazil (1.4) Uruguay (4.7)

Paraguay0.4) Costa Rica (1.1) L A C (1.3) Chile (1.7) Honduras (1.7)

Ecuador (1 .O)

Mexico (1.1)

Dominican Republic (1 .O)

Peru (0.7) Argentina (1.2) Guatemala (1.1) El Salvador (2.4)

2.5 .............................

2.0

1.5

1 .o

0.5

Social Safety Net Spending, %of GDP most recent year 2000-2006

................................................

.............................................

OECD Europe and Middle East and Latin America South Asia Peru (2006) Central Asia North Africa and the

Caribbean ~

Source: Own estimates for Peru; Lindert, Skoufias and Shapiro (2005) for LAC; based on Blank and others (forthcoming) for other regions.

Peru’s low SSN spending compared with other countries reflects the low overall level o f public spending, coupled with the low priority assigned to SSN programs. L o w social sector spending in Peru i s partly the result o f low taxation and weak tax collection. In 2006, Peru’s central government current revenues in Peru totaled only 17 percent o f GDP. Although this reflects a noteworthy increase from the level o f 14 percent observed in 2002, Peru’s tax effort remains inferior to that o f more developed countries and o f many less developed countries, too. As a result, fiscal space i s limited. What i s more, within the available space, the priority assigned to S S N programs i s also relatively low.

16

34. The vertical axis categorizes countries according to total spending as a share o f GDP; and the horizontal axis does the same for the share o f total public spending devoted to social assistance (non- contributory programs). Brazil and Uruguay have high levels o f social assistance spending as a share o f GDP because they have high spending levels overall and devote large shares to social assistance programs. As a result, social spending accounts for more than 1.4 percent o f national income. Other countries, such as Guatemala and Salvador, have low levels o f government spending overall, but place a high priority on social assistance programs. But Peru i s among the countries with the lowest level o f public spending in Latin America and among the group o f countries who attach a very low priority to social assistance spending (less than half o f the average for the region).

35. SSN spending i s low relative to the poverty gap but fairly large relative to the extreme poverty gap. In the absence o f SSN spending, total poverty gap (the difference between the present consumption o f poor households and the amount they need to consume to escape from consumption poverty) i s estimated at about 7 percent o f GDP. At 0.7 percent o f GDP, total SSN spending could cover only 10 percent o f that gap. However, SSN spending represents a much bigger proportion o f the extreme poverty gap (the amount o f resources needed to take all households out o f extreme poverty). In the absence o f SSN transfers, the extreme poverty gap would be about 1.3 percent o f GDP.

36. The reduction in poverty achieved by SSN spending i s below i t s potential, because part o f the resources leaks to non-poor beneficiaries. About a third o f the SSN spending reaches the extreme poor and 70 percent reaches either the extreme or moderate poor; while 30 percent goes to non-poor households. As a result, it i s estimated that in practice, SSN spending in Peru reduces the poverty gap from 6.8 percent to 6.3 percent o f GDP, and the extreme poverty gap, from 1.32 percent to 1.1 percent o f GDP. Perfect targeting o f the existing S S N resources on the extreme poor would halve the extreme poverty gap. Under a more realistic scenario, where leakage i s reduced by 50 percent (that is, that only 34 percent o f the funds go to households who are not extremely poor), the extreme poverty gap would fal l by one third o f i t s pre-transfer level (Figure 2-4).

Fig .e 2-4: Modeled impact on the poverty gap o f increased targeting of SSN spending toward extreme poor Poverty Gap vs SSN Spending

in 2003 I 7.0

6.0

5.0

3 4.0

' 3.0

2.0

1 .o

B

Re-transfer] ~ - t r a n ~ , e r l transfer ~~ SSN I

Total poverty gap &trem poverty, gap spending

Simulated Change in ktrerne Poverty Gap under2 scenanosoffmpmvedfargetmg

100

90 ; 80 70

60

50

40

4 30 : 20

s 10

In the absence of Current (leakage of lnproved targeting Perfect targeting SSN spending 58% of funds) (reduce leakage to (elimnate leakage)

34%) (Scen 1) (Scen 2) ~

Note: The left Dane1 presents the total and extreme poverty gap before and after SSN transfers. Note that the reduction in poverty gap after SSN transfers i s lower than the S S N spending, because part o f the resources does not reach the poor. The rieht Dane1 presents the simulated poverty gap for households in extreme poverty under two scenarios. Scenario 1 assumes 66 percent of the resources are received by the extreme poor (compared to only 32 percent in 2003). Scenario 2 assumes perfect targeting, i.e. al l resources reach only the extreme poor. Author's estimation based on ENAHO 2003104 data. Source:

17

37. The structure o f social protection agencies within the Peruvian public sector i s shown in (Figure 2-5). The following sections review the four largest SSN programs (which between them account for about 70 percent o f al l SSN spending) to suggest ways to improve their performance, covering: (i) Vas0 de Leche; (ii) workfare programs; (iii) the social fund, FONCODES; and (iv) the Juntos CCT program.

18

r I 1

r

g 5 5 3 3

I r ,r 1

L

E a, a, c rn -0 C m

c -

$ 3 ,o L

U 0 0 LL

a, c i

Y Y .- 5 C

i 5 0

2.3 Vas0 de leche 38. Vuso de Zeche spends $1 10 million a year, which i s over 40 percent o f the overall budget for food assistance, and has almost 5 million beneficiaries. It has been criticized for having high leakages towards the non-poor or non-intended beneficiaries (Vazques 2005; Alcazar 2003). However, analysis undertaken for the present report shows that a large proportion o f the resources are received by poor households: over 45 percent o f the beneficiaries in urban area and 65 percent in rural areas are from the bottom two quintiles (Figure 2-5). The fact that the program i s better targeted in rural areas i s not surprising, given the higher incidence o f poverty there.

39. Given Vuso de Leche’s considerable coverage of children in extreme poverty, it could become an effective instrument, given feasible improvements in i t s design and implementation. The program has a number o f strengths to build upon:

Beneficiaries’: The program targets children from zero to six years old, expectant and lactating mothers. All these groups have poverty rates above average, and constitute the key vulnerable group in Peru. As illustrated in Figure 2-6, children in the priority group have a higher probability o f benefiting from the pro gram. Coverage: The program has a large coverage among the poor population: 44 percent o f poor households with children in urban area and 73 percent in rural area have one or more beneficiaries o f Vuso de Leche. Gender neutral: Survey data show no gender bias in the program. Social capital: 23 percent of Peruvian households participate in comitis de vas0 de Zeche; this i s by far the largest CBO structure in the country. In contrast, the second largest association movement (usociucidn vecinul) attracts only 7 percent o f households. The comitis de vuso de Zeche therefore constitute an important part o f Peru’s social capital and contribute to women’s empowerment. With the right incentives, this network could play an important role in poverty reduction in Peru. Targeting: The program uses simple targeting mechanisms: demographic (age) and self- selection (mothers have to pick up the food rations in the morning and have to contribute some o f their time). Graduation: The program has an automatic exit ru le - or would, if the age eligibility criteria were to be enforced.

40. The main issue with Vuso de Leche i s that, over time, the program’s implementation has deviated from the original idea o f providing infants and pre-school children with a glass of milk seven days per week. Many beneficiaries (80 percent in rural areas) receive the benefit in bulk once per month or even at larger intervals (Figure 2-7), commonly in the form o f evaporated milk. This i s more expensive and increases the likelihood that it wi l l be shared with others in the household (as documented by the 2003 public expenditure tracking survey) or bartered for other goods or labor, as revealed by discussions in focus groups. Circumstantial evidence suggests that there may be a problem in some places with “phantom beneficiaries” who are manipulated to allow VdL committee members to benefit from their rations. The Comptroller General’s Office reported that 47 percent o f the VDL budget in 2004 was spent on evaporated milk, up from 34 percent in 200 1. The large milk companies dedicate considerable effort to securing a share o f the Vas0 de Leche market.

4 1. The second major issue i s the crowding out, over time, o f the priority group of children up to six years old by other age-groups. In 2003, administrative data shows that only 58 percent o f the beneficiaries are aged 0-6 years old, compared to 69 percent in 2001 (Figure 2-8).Given the clear evidence that chronic malnutrition in Peru i s often linked to inadequate complementary feeding in the age range from 6 to 24

The data source i s ENAHO 2003/2004.

20

months, VdL cou ld potential ly have a m u c h bigger nutr i t ional impact if it were even more tightly focused on that age range.

Figure 2-5: Distribution of Vas0 de leche beneficiaries by quintile and area o f residence Share o f beneficiaries fiom a given quintile

I Targeting performance of VdL by Area

. . . . . . . . . . . . .

. . . . . . .

. . ..

Rural Urban

Source: Author’s estimation based on ENAHO 2003/04 Survey, annual sample, INEI.

Figure 2-6: Probability of receiving Vas0 de Lecke by age and area of residence

Probability of Receiving Vaso de Leche by welfare status, age and area of residence

1

8

.6

.4

.2

0

-6- 1 year old, rural + 1 year old, urban + 6 year old, rural + 6 year old, urban t 13 year old, rural -B- 13 year old, urban

0 1 2 3 Welfare ratio: Per capita consumption I Poverty line Based on ENAHO 2003/2004. INEl

Note: Predicted probabilities after controlling for household characteristics; on the x axis the population i s ranked according to the welfare ratio; 2 vertical l ines correspond to total and extreme poverty lines.

Source: Author’s calculation based on ENAHO 2003/2004 annual sample.

21

Figure 2-7: Frequency of delivery of Vas0 de Leche benefits in rural and urban areas

M3st VdL beneficiaries in rural areas do not receive their glass of milk on a daily basis

distribution of beneficiaries by the frequency of receiving the

Urban Rural Total

Daily-Weekly Nbnthly

Source: Author’s estimation based on ENAHO 2003/2004.

Figure 2-8: Trends in the composition of VdL beneficiaries, 2001-2003

j Distribution of beneficiaries by categoly

I 2001 2002

j Q Children under 6 Pregnant and nursing mothers Secondary target group I Source: Comptroller General’s Office, Informe Macro del Programa VdL, 2003. Source: Author’s estimation based on ENAHO 2003/04 Survey, annual sample, INEI.

42. To improve the poverty reduction impact o f the program the government should consider the following measures: (i) amend the legislation to exclude children over 6 years old from eligibility; (ii) eliminate the earmarking o f one third o f program resources to Lima and Callao; (iii) provide benefits sufficient to cover 7 days per week (in 2003 less than 50 percent o f the districts were able to cover 26-30 days o f supply per month); if necessary , to make this fiscally feasible, the age range o f beneficiaries could be further restricted to those under 24 months o f age; (iv) integrate the program with health and nutrition services, making the glass o f milk conditional on human capital investments such as health visits, child growth monitoring, health and nutrition education.

2.4 Workfare programs

43. Peru has considerable experience with workfare programs that provide short te rm assistance and also build physical assets for the poor. Two workfare programs, A Trabajar Urbano and A Trabajar Rural, were initiated in the early days o f the Toledo administration, in response to the economic recession

22

o f 1998 to 2001. They provide temporary employment for unskilled workers, at relatively low wages. In rural areas workers were hired for up to 6 months, to renovate social infrastructure and do maintenance work. However, today, A Trubajur Rural has no well-defined programmatic form and i s used as a convenient fiscal umbrella for ad-hoc interventions.

44. In A Trubujur Urbano, the period o f assistance i s up to 4 months. Program beneficiaries obtain a monthly wage o f S/.300 (or US$91), below the minimum wage o f S/.427 (US$129) per monthg. In 2006 A Trubujar Urbuno spent Y.187 million, which i s 10 percent o f SSN spending and 0.07 percent o f GDP, and reached 57,000 beneficiaries (about 0.2 percent o f the population). The budget for the workfare programs has been decreasing over time". This reflects the fact that the Peruvian economy has now recovered from the economic crisis o f 1998 and the recession that followed". However, it would be recommendable to maintain in place a minimum workfare program capacity to facilitate a quick response during future economic downturns or natural disasters. International experience suggests that it i s hard to build up well-designed workfare programs from scratch in crisis situations.

Figure 2-9: Distribution o f beneficiaries o f A Trabajar Urbano by consumption quintile, 2003 r

A Trabajar Urbano Share o f beneficiaries from each quintile

. . . . . . . . . 30

.. .... . . 25

20

15

10

5

I Q1 Q2 43 4 4 Q5

Source: Author's estimation based on ENAHO 200312004

45. A Trubujur Urbuno has many good design features, in line with international best practice. The principles for a good workfare program are that it should be counter-cyclical, should be self-targeted and should avoid distorting the labor market (See Box 4.3). A Trubujur Urbuno does well on these tests, being characterized by: (i) reasonable labor intensity (share o f the labor costs in the total cost o f the projects i s about 60 percent); (ii) good targeting mechanisms that combine poverty maps with self-selection, through paying less than the minimum wage; in 2003 65 percent o f the beneficiary households belonged to Q1 or Q2; (iii) competitive selection o f projects at community level; (iv) emphasis on projects that improve the livelihoods o f the extreme poor, such as roads, schools and health posts; (v) community involvement in project supervision.

46. However, the wage level o f S/.300 (US$91) per month may be set a l i t t le too high. It i s by far the largest benefit o f any S S N program in Peru. Although it i s 22 percent below the legal minimum wage, it i s more than what workers in the poorest quintile in Lima earn. This sets up incentives to try to remain in the program after the crisis has passed, and there i s evidence that many workers on the scheme were already employed beforehand in informal sector activities.

This minimum wage was in place in 2005; it was increased to SI. 500 (USrS152) in 2006.

A Trabajar Urbano covered 0.5 percent o f the urban population in 2003. lo A Trabajar Urbano created 169,000 jobs with duration o f 4 months from January 2002 to April 2004.

23

47. To improve the workfare program, some fine-tuning i s suggested: (a) set the level o f wage rate below the prevailing market wage for unskilled labor to promote self-selection; (b) align the workfare programs in the framework o f decentralized basic social infrastructure investments to ensure the quality and maintenance o f assets created; and (c) fund employment in social services (caregivers, health promoters) to increase the participation o f women.

Box 2-2: Workfare Programs - Key Design and Implementation Issues

Public works programs have been demonstrated to work both in middle income (Chile, Argentina, South Africa) and low income countries (Senegal, Kenya, India and Bangladesh) and not to work in many others. This international experience offers several lessons in the design and implementation of workfare programs:

Wage Rate: The key to ensuring self-targeting i s setting the wage rate low enough -- no higher than the market wage for unskilled manual labor in agriculture or the informal sector during a normal year. Wh i le determining the precise level of the wage rate may not be easy, it i s better to err on the side of starting with a wage rate that i s too low - if there i s no demand at the offered wage rate, it can be raised. Setting the wage rate at a low level not only ensures that the workfare scheme will be well self-targeted, it also maintains the incentive to take up regular work when it i s available, and it helps ensure that the program can reach as many of those in need as possible. Eligibility conditions and other means of rationing should be avoided; ideally the only requirement should be the willingness to work at the offered wage. If rationing i s unavoidable, (for example if the demand for employment at the wage set exceeds the available budget), then explicit secondary criteria should be used - the program may targeted to poor areas, work offered only in seasons of greatest need, the length of employment o f any individual limited, and/or additional targeting devices such as community-based selection o f the neediest. Least desirable i s rationing and entry determined by foremen or political figures. Women’s participation can be enhanced through non-discriminatory wages, the provision of on-site daycare and adequately private latrines. Labor intensity: The labor intensity, that i s the share of the wage bill in total costs, should be higher than normal for similar projects in the same setting. There i s a trade off between immediate income gains through employment of the poor, and gains to the poor from the quality and durability of the assets created. In a crisis situation, where current transfers to the poor have high weight, high labor intensity i s likely to be desired. Illustrative average labor intensities range from 0.5-0.65 percent in low income countries, and somewhat lower (0.4) in middle income countries, though labor intensities often vary significantly by sub-projects Administration and Implementation: Administering and implementing an effective scheme i s hard - involving the selection and management of a plethora of small projects over a wide geographic area and many administrative entities. Ideally, public works schemes require a menu of works that i s well- integrated into the local planning process yet elastic in size and timing. This can be difficult in low capacity settings because o f the forward planning and inter-agency coordination needed. In high capacity settings, fitting many small labor intensive projects into the sophisticated and often capital- intensive infrastructure plans of large and middle cities can be hard. Moreover, ensuring that the workfare program i s poverty focused i s often difficult because of conflicting pressures from alternate target groups (for example, the skilled unemployed).

Source: Subbarao (2003).

2.5 FONCODES 48. The future o f the Peruvian Fund o f Social Development (FONCODES) i s uncertain. In the context o f the decentralization process and the social programs restructuring exercise, the Garcia administration has announced that it wi l l be closed - but has also announced the need for a new entity to support small scale social sector infrastructure.

49. FONCODES was originally established in 1991 with the aim o f generating employment, alleviating poverty and improving access to social services. The government passed special legislation that allowed

24

FONCODES to circumvent the rigidities o f planning and executing public investment through line ministries. The innovative modus operandi o f FONCODES included targeting using a “poverty map” to assign resources to rural nzicleos ejecutores, demand-driven sub-project choice from a menu o f possible investments, and simplified procurement rules. This translated into over 40,000 projects for the construction or rehabilitation o f schools, health posts, water and sanitation systems, rural roads, secondary electrification schemes, and small - scale irrigation works for a total o f more than US$2 bil l ion over 14 years o f operation’*.

50. Evaluation studies show that FONCODES expanded access to basic social services and i t s investments reached the poor districts and poor households within those districts and have had positive effects on school attendance rates for young children. Schools that received FONCODES resources for school improvements experienced an increase in enrollment, which benefited poor children (Instituto Apoyo, 2000, Paxon and Schady 2002, and Schady 2005). FONCODES’ geographic targeting i s also more progressive than that o f social funds in Bolivia, Nicaragua, Honduras, Zambia, or Armenia (Figure 2-10), largely because o f i ts predominantly rural focus and the use o f poverty maps in selecting the districts.

Figure 2-10: FONCODES’s geographic targeting progressiveness, compared with other social funds

-+-Line of equality Arrrenia -w- Bolivia ++ Honduras --e Ncaragua -I- Peru + Zanbia

100

90

80 ui 2 70

f 60 ’ 50

v) 40

$ 30

t

z 5 20

c

10

0

’’ In addition, FONCODES has executed a series o f centrally-designed “special” projects which have included, among others, a school breakfast program, the distribution of uniforms for school children, shovels for farmers, and motorized canoes.

25

52. The flexibility, discretion and centralization which enabled FONCODES to reach the poor also made it vulnerable to political interference. Schady (2001) showed that between 1991 and 1995, FONCODES’ spending was boosted before elections, and that projects were channeled to provinces where the political returns were expected to be large.

53. In the last six years FONCODES underwent important changes to address some o f these issues. In 2001, it was relocated within MIMDES (re-branded as the National Plan for Compensation and Social Development), and in 2003, it began decentralization to district municipalities. However, decentralization was conducted in an ad-hoc manner without developing f i rs t the fundamental elements o f a new model o f decentralized provision o f small-scale infrastructure. The accreditation o f municipalities for decentralized administration o f FONCODES resources was complicated and bureaucratic, but provided no guarantee o f adequate local capacity. Some questioned the rationale for any accreditation process, in a context in which many municipalities already administered much larger investment funds from FONCOMUN. FONCODES represented only 2 percent o f transfers to municipalities from the Central Government in 2005 (Figure 2-1 1). The monitoring arrangements for the decentralized framework were also deficient: the management agreements (convenios de gestidn) between MIMDES and district municipalities did not include output indicators to monitor program performance.

54. The comparative advantage that allowed FONCODES to be an efficient manager o f small-scale infrastructure projects lay in the different systems it developed to manage the project cycle: systems and instruments for designing, appraising, disbursing, and supervising projects, and for hiring project designers, evaluators, supervisors, trainers, and so forth. Wh i le the introduction o f a decentralized project cycle gave district governments a few more responsibilities than before, most o f the know-how has remained in FONCODES zone offices; it has done relatively l i t t le to build the capacities o f district governments to forge strong partnerships with communities and local service providers for effective small-scale infrastructure provision

Figure 2-11: The distribution of Central Government transfers to sub-national governments, 2006

Other social programs 11, 50 Other

transfers, 432

anon, 2124

I/ Social programs : PROVIAS, Community Kitchen, Food for work, Shelters. Source: SIAF Local (MEF), mill S/. (2006).

26

55. During the Toledo administration, funding for FONCODES was stabilized and reduced by around 50 percent, partly due to budgetary constraints and partly due to the transfer o f the Desayuno Escolar program to PRONAA. The cut in financing for the social fund was expected to be compensated by higher investment by municipalities and regions, in the context o f decentralization. However, in 2005-2006 spending recovered.

Figure 2-12: FONCODES investment in real terms

FONCODES spending, 1991-2006 2004 constant prices

900 - ................................................................................................................

100

...... .............................................................................................

.................................................................................................................

Source: Perli en Nlimeros 1997; Direccidn Nacional de Presupuesto Pliblico (MEF); SIAF-SP (MEF); INEI; BCRP.

2.6 The Juntos CCTprogram

56. In 2005 the government introduced a conditional cash transfer (CCT) program-Juntos-that provides US$30 per month to families with children under the age of 14 or pregnant mothers living in extremely poor communities. Receipt o f the transfers i s subject to compliance with conditions regarding school attendance, obtaining birth certificates and identity cards, and attending nutrition education sessions and use of preventive health care. The program started with a pilot phase covering about 70,000 households in the poorest 1 10 districts o f the departments o f Apurimac, Ayacucho, Huancavelica, and Hubnuco. In 2006 the program expanded into five more departments, covering 200,000 households in 320 rural districts and inner-city neighborhoods, in nine o f Peru's 27 departments. By the end of 2007 the program wi l l reach 400,000 households in over 638 districts across 14 departments, or about 2.5 million individuals representing 9 percent o f total population. The total cost o f the program in 2006 was W.173 million, which i s 9 percent o f SSN spending and 0.06 percent o f GDP, making it the fifth largest program after FONCODES, Vas0 de Leche, A Trabujar Urbano and the school feeding program.

27

rigure 2-13: Juntos targeting process: geographic selection, household assessment, and community validatii

Cornrn un ity validation

Household level

Select districts based on: 1. Extreme poverty 1. Children under 14 that have:

2. Povertygap wages 3. Unsatisfied Basic Needs 2. Pensioners 4. Chronic malnutrition 3. Shop/business owners 5. Political Violence 4. Alimony recipients

Identify poor households with Validate lists. Exclude households

incidence 2. Pregnantllactating mothers 1. Professionals earning monthly

5. Vehicles 6. A certain number of livestock 7. Residents living in other cities 8. Relatives of local authorities

n

57. Targeting ofJuntos, i s done in three steps, comparable to similar programs in Mexico and Colombia: (a) geographic targeting, (b) household assessments based on a proxy means test, and (c) community validation (Figure 2-13):

(a) Geographic targeting. In the f i rs t stage a l l 1828 districts in the country were ranked using a composite poverty index13. The departments selected for the pi lot phase (Phase 1) o f the program - Apurimac, Ayacucho, Huancavelica, and Huanuco - have among the highest incidences of poverty in Peru (Figure 2-14). The f ive departments included in 2006 (Phase 2) present a more mixed picture. Puno and Cajamarca have a high incidence o f extreme poverty; whi le Ancash, Junin, and L a Libertad are close to the national average. The program excludes departments that are sparsely populated or heterogeneous in terms o f poverty, to avoid dispersion o f effort and economize on administrative costs.

(b) Household assessment. Juntos i s the f i rst program in Peru to select beneficiaries using a proxy- means test14. Eligibility i s determined using a household questionnaire (Ficha Socioecondmica

l3 The index used the following component indicators: (i) extreme poverty rate (ii) total poverty gap based on the 2000 poverty map; (iii) percentage o f households with more than two Unsatisfied Basic Needs (UBN j r u n n i n g water, electricity, schools, health services-- based on the 1993 Census; (iv) chronic malnutrition rate among children 6 to 9 using the weight and height census o f 1999; and (v) the percentage o f population centers affected by political violence based on a special census done through the Resettlement Support Program (Programa de Apoyo a1 Repoblamiento). Although some o f these data sources are rather old, the ranking o f districts using data fiom the ENAHO 2004 for total and extreme poverty yields similar results. I t should be noted that the f r s t 70 districts in the pilot phase were selected using a composite index that excluded the extreme poverty rate.

The algorithm used by Juntos to identify the poverty status o f households i s detailed in Annex 2. It i s based on ENAHO 2001-2004 and uses a logistic regression with 8 predictors. Another program - Seguro Integral de Salud, a health fee waiver for the poor - plans to use a similar proxy-means test algorithm.

14

28

Unica - FSU) that collects data on demographic composition (including the presence o f children under 14 and pregnant mothers), education, dwelling characteristics, durable assets, livestock, and agricultural equipment. A score i s calculated for each household and i s compared to the pre- established cut-off point.

(c) Community validation. A community meeting i s held to validate the l i s t o f beneficiaries. At this stage, the fo l lowing households can be excluded: (i) those with members employed in the formal sector, pensioners, recipients o f alimony, business owners, money lenders, and relatives o f local authorities; (ii) owners o f livestock, cars or other large assets. The pi lot phase showed some flaws in this phase o f the process. Many are afraid to denounce others, whi le some believe the program should include everyone, to avoid dividing the community. The meetings are not always representative; and promoters sometimes dominate - rather than facilitating - the discussions.

Figure 2-14: Departmental poverty and extreme poverty rates, 2006

National poverty rate

Madre de Bios

0 0 100 200 3 0 0 400 500 600 700 800 900 1001 Percentage of population

Poverty 8 E t r e m poverty . --

Source: ENAHO 2006 (INEI).

58. Permanence in the program. A beneficiary remains in the program for four years; however this period i s l ikely to be extended given that the exit rules are not yet defined. This could result in a progressive decline in targeting accuracy as households’ poverty status changes, making it hard to accommodate those who have fallen into poverty or to exclude those who are n o longer poor. Some C C T programs have systematic recertification procedures to deal with this issue.

29

59. BeneJit level. The US$30 per month benefit given by Juntos i s adequate - equal to about 25 percent o f the consumption o f recipient household^'^. Whi le this i s eight times greater than that o f the existing food programs (3.5 percent on average), the benefit level i s comparable with that in Brazil’s Bolsa Familia and Mexico’s Oportunidades which give benefits o f about 20 percent o f mean household consumption. The value o f the Juntos benefit was not set (as in some other countries) based on the estimated costs o f complying with the program’s conditionalities. Rather, the program opted for a benefit that was simple to administer and related to the extreme poverty line o f $1 a day. The transfer i s the same, regardless o f household size or the number o f children. In this regard, Juntos differs f rom other CCT programs in Mexico, Brazil, Colombia, whose benefits vary according to the number o f children in the family and other criteria.

60. Conditionality. Juntos has adopted a relatively complex and ambitious set o f conditions for program eligibility, apparently in an effort to give polit ical legitimacy to the program. Beneficiaries must sign an agreement called the Convenio de Compromiso Voluntario. Children under 14 must be enrolled in primary school with an 85 percent attendance rate and must visit the health center periodically. Mothers must attend pre-natal and post-natal clinics. Adults must have national identification cards and ensure that their children have birth certificates (Table 2-4). The program has a long way to go to improve arrangements for monitoring compliance. The evidence from the field suggests that beneficiaries are required to personally collect certifications f rom schools and health posts on a periodic basis, generating a rush to collect official stamps (“sellos”) and interfering with the normal production o f services. This emphasis on filling forms rather then on providing the services can be detrimental for the impact o f program. A more sophisticated system would establish direct communication between Juntos and the service providing entities, in which institutional registers were used to verify compliance with program conditionality.

61. I t would be recommendable after the pi lot phase to consider simplifying the conditionalities and eliminate those which are not l ikely to have a major impact. For example, primary enrollment i s already very high in Peru. According to the 2005 Census, 92 percent o f children aged 6 to 14 years in rural areas in the first selected 110 districts are already in school. I t would make more sense to focus on increasing secondary enrollment, given that the ratio o f children o f secondary school age who are enrolled in school to the population o f the corresponding secondary school age i s only 69 percent16. T o encourage children in remote locations to attend secondary school a more substantial transfer could be envisaged, to cover commuting and/or boarding costs. At the same time it would make sense to strengthen the co- responsibilities related to nutrition, given that almost 35 percent children zero to f ive years old in the areas where the program operates suffer f rom chronic malnutrition. In July 2007, the Juntos Board decided to move in this direction, re-focusing Juntos on improving nutritional outcomes. This initiative was later endorsed by the national nutrition strategy, CRECER.

On average, Juntos benefit represents an increase o f 25 percent o f the consumption o f recipient households. The average consumption o f extreme poor rural households in the 4 departments where Juntos operates i s S/. 75, and their household size i s 5.4 members. Adequacy was determined as (100/(5.4*75) = 0.25.

15

According to World Development Indicators, World Bank, 2006. 16

30

Health

Education

Nutr i t ion and identity

Family co-responsibilities Enrollment in primary school o f children 6 to 14 School Attendance: 85 percent o f the time Families w i th children 6 months to 3 years participate in the nutritional program PACFO (papilla and education sessions)

. Chlorine Note: These conditionalities were revised in July 207 to focus more on nutrition actions for pregnant women and children under five.

62. Institutional arrangements. The institutional arrangements aim to involve the education and health sectors in decision making, to increase transparency, and isolate the program from political manipulation. The program i s controlled by the Presidencia del Consejo de Ministros. An Executive Council chaired by a President and including the ministers o f Education, Health, Women and Social Development, Finance and representatives o f the trade unions and civi l society approves the action plan, supervises and evaluates the program. The program has the status o f an executing agency with i t s own budget and i s responsible for the main operations. A supervisory body including representatives o f the church, private sector, regional and local government, and the Mesa de Lucha Contra la Pobreza i s responsible for social monitoring and transparency.

63. Supply side conditions. In the pilot phase, Juntos assigned a third o f i ts budget to strengthen the supply or relevant services and the program places a heavy emphasis on coordination at local level with the education and health sectors. This i s a welcome recognition that a demand-side program to enhance human capital among the poor wil l only work if the supply-side i s in place. However, to ensure that this i s effective it i s important to study the supply gap rather than giving the money to the health and education sector as fungible resources. However, to date, the line ministries have proved unable to use the additional funds supplied by Juntos effectively to improve supply conditions in Juntos areas (executing a very small proportion o f the total). The government i s presently analyzing options to improve this mechanism, as part o f the results based budgeting reforms.

64. Targeting accuracy. The program’s targeting outcomes and poverty impact was modeled, using the database o f the ENAHO 2004 survey.” In the departments included in Phase 1, the algorithm correctly selects 66 percent o f the extremely poor households as Juntos beneficiaries. However, given that 56 percent o f the population o f these four districts i s extremely poor, even a lottery system would select 56 percent. So the apparent success o f the algorithm i s largely due to the quality o f the geographical targeting. This raises the question o f what value i s added by the costly and problematic process o f household-level data collection. It i s also noteworthy that the precision o f the algorithm diminishes when

For each household, a score was estimated using the official proxy means test presented in Annex 2. Households with scores above the program threshold were “enrolled” in the program, if located in one of the 110 districts fiom Apurimac, Ayacucho, Huancavelica, and Huhnuco where the program was implemented in 2005 (Phase 1). The same method was used to identify those households enrolled in 2006 fiom another 210 districts fiom the departments of Puno, Cajamarca, Ancash, Junin, and La Libertad (Phase 2), as well as for the whole rural area.

17

31

the program expands to districts with less households in extreme poverty - if expanded to all rural areas, it would only correctly identify half o f the extreme poor as beneficiaries (Table 2-5). If Juntos i s to maintain such a system in place, it should consider developing a more sophisticated algorithm, using more indicators (see Box 2-3). Modeling results suggest that a more sophisticated algorithm could result in better coverage o f the extreme poor, and less funds leaking to non-extreme poor beneficiaries.” It should also be noted that in urban areas, the government i s implementing SISFOH (“Sistema de Focalizaci6n de Hogares”), a proxy means test which aims to identify households in extreme poverty. Due to the greater variance in household income, the case for investing in such a system i s stronger in urban areas.

Table 2-5: Juntos PMT Algorithm: Inclusion and Exclusion Errors

’* For example, adding two predictors known for their high correlation wi th poverty status to the Juntos algorithm (household size and departmental dummies) would increase the share o f extremely poor households covered by the program from 66 percent to 73 percent, reduces the fraction o f extreme poor not covered by the program f i om 49 percent to 40 percent, and reduces the leakage o f funds toward non-extreme poor households by about Sl.20 mil l ion per annum (Figure 2-15). Another good predictor i s the rate o f chronic malnutrition at the level o f the census unit. (The results o f the regressions are presented in Annex 4).

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Box 2-3: Improving Juntos household-level targeting instrument

The predictive power o f the proxy-means test algorithm can be improved by:

Using a larger set of predictors to predict poverty status. Juntos’ algorithm uses only 8 variables to predict the poverty status o f a household. In contrast, other CCT programs from Chile, Colombia, and Costa Rica reviewed by Castaneda and Lindert (2005) use between 13 and 16 variables. The FSU questionnaire includes many other factors strongly associated with poverty status, such as household size, location, the level o f education of the adults, crowding, and house or livestock ownership. B y not taking such variables into account, the official algorithm looses precision (see Annex 4).

Calibrate the model on extreme poverty, not on total poverty.

Using more flexible prediction models differentiated across regions or departments.

Avoid using data reduction techniques. Although Juntos collects a wide range o f household indicators though the FSU questionnaire, i t uses only a small fraction o f them to predict poverty status. INEI arrived at this parsimonious model with 8 variables after a process o f data reduction - instead o f using the raw information from the questionnaire; it grouped that information into fewer categories which, in turn, are used as predictors. However, some precision i s lost during the process o f data reduction; using the original variables wi l l generate a better fit.

Collect more relevant information in the FSU questionnaire. Juntos’ FSU questionnaire collects a total o f 36 variables, lower than in the CCT programs from Chile, Colombia, Costa Rica or Mexico, which collect between 50 and 115 variables. Among the variables used to predict poverty in other L A C programs, which are not collected in the FSU, are the occupation o f the household head or formal incomes.

Note: Simulation based on ENAHO 2004 (INEI) and Juntos administrative data. Phase 1 corresponds to the 110 districts in the departments o f Apurimac, Ayacucho, Huancavelica, and Huanuco; Phase 2 corresponds to another 210 districts in the departments o f Puno, Cajamarca, Ancash, Junin, and La Libertad.

Source: Authors’ estimation based on ENAHO 2004.

Figure 2-15: Reduction in Juntos’ Inclusion and Exclusion E r ro r with an Improved Prediction Model I

~

100 - I

70

60

Z 50

40

30

20

10

inclusion correctly classified as extreme poor exclusion extreme poor not cowred ~

Juntos m Improbed Model I L--_ _ _ _ _ ~ -,

Source: Authors’ estimations based on ENAHO 2004 (INEI)

65. Juntos’ impact on extreme poverty is likely to be large, due to the size of the benefit and good targeting accuracy. The modeling exercise suggests that in Phase 1 and 2 Juntos could reduce the extreme poverty gap by 19 percent in the departments where it intervenes; and this will reduce the national poverty gap by 2 percent in Phase 1 and by 5 percent in Phase 2. If the program were expanded to all rural areas, the extreme poverty gap would fa l l by 14 percent. (Figure 2-16 and Table 2-6). These

3 3

impacts could be roughly doubled if the precision o f the targeting system could be perfected. They could also be increased by distributing benefits on a per capita basis rather than a household basis and redistributing program resources accordingly.

Figure 2-16: Juntos' Simulated Impact on the Extreme Poverty Gap

Phase 1 Phase 2 Phase 3

Before Juntos After Juntos I _ _ ~ ~

Note: Phase 1 covers 110 districts in Apurimac, Ayacucho, Huancavelica, and Huanuco; Phase 2 includes Phase 1 districts and another 210 districts in the departments o f Puno, Cajamarca, Ancash, Junin, and La Libertad. Author's calculations based on ENAHO data (200312004). Source:

34

Poverty gap Poverty severity

Phase 2: 320 Districts in Poverty headcount 0.523 0.470 Poverty gap 0.165 0.134 Poverty severity 0.070 0.053

Phase 3: All Rural Poverty headcount 0.402 0.360 Poverty gap 0.1 17 0.098 Poverty severity 0.048 0.038 Note: Phase 1 corresponds to the 110 districts in the departments o f Apurimac, Ayacucho,

Huancavelica, and Huanuco; Phase 2 includes Phase 1 districts and another 210 districts in the departments o f Puno, Cajamarca, Ancash, Junin, and L a Libertad.

Source and methodology: Author’s calculations based on ENAHO data (200312004). Beneficiary households (in the third column) are those which would qualify for Juntos participation based on their poverty status, as registered in the survey.

66. Juntos’ potential to impact chronic malnutrition i s also very high. In Peru there are over 500,000 chronically malnourished children age zero to five. Of those, almost 40 percent l ive in districts where Juntos operates. The prevalence o f chronic malnutrition in these areas i s as high as 36 percent - compared with 13 percent in areas not covered by Juntos. If al l chronic malnutrition were eliminated in the Juntos districts, the national stunting rate would be reduced by 3 8 percent; even if ha l f o f it were eliminated, the national rate would be reduced by almost 20 percent. To achieve this effect, Juntos could strengthen incentives for families to participate in growth promotion programs, to seek micronutrients and other services offered by the health system, which are important for nutrit ion results. Engaging families into a growth measurement and counseling system would provide them with information about their child’s nutritional status, and how to improve it. The income transfer will also help families to afford better nutrition for their children. (Figure 2-1 7).

Table 2-7: Chronic malnutrition rate, children zero to five (Weighted statistics, weights =population of children less than 5 years old)

Juntos Areas Average Min P25 Median P75 Max Areas not in Juntos 13.2% 1.6% 6.2% 9.5% 18.7% 63.2% Juntos Phase 1 & 2 (320 districts) 36.4% 6.5% 28.4% 36.3% 44.3% 61.7% Expansion Juntos 2007 35.2% 8.2% 29.7% 35.4% 41.3% 60.1% Total 17.6% 1.6% 6.6% 14.7% 25.4% 63.2%

Source: Authors’ calculation based on SIEN 2005 and Juntos administrative database.

67. To achieve a strong nutrition impact, it i s important for Juntos t o continue focusing on rural areas with high malnutrition rates and to improve the design o f co-responsibilities to include a minimum o f important elements for diminishing malnutrition (for example, periodical growth monitoring visits, participation in counseling and health and nutrition education, pre-natal controls, institutional births, etc). At the same time, it i s important to improve the quantity and quality o f primary health care services including guaranteeing a minimum protocol o f monitoring ch i ld growth until age two, providing

35

micronutrients and food supplements, improving the training o f health personnel and community agents, improving the growth control and measurement systems.

Figure 2-17: Juntos’ Simulated Impact on Reducing Chronic Malnutrition

6 0.35

0.30

5 0.25

:E - m

._ c g 0.20 0 ,E 0.15 0 ._ c 2 0.10 u

0.05

0.00 a?

... . .

scenario 1: 100% of scenario 2: 80% of scenario 3: 50% of malnourished malnourished malnourished

children in Juntos children in Juntos children in Juntos

Source: Authors’ calculation based on SIEN 2005 and Juntos administrative database

68. Monitoring and Evaluation. Juntos also needs to develop a coherent Monitoring and Evaluation system to ensure that good evidence i s produced about the program’s results and fed back into the decision process as the program expands. This should include a rigorous evaluation, to help decide whether the program should be confined to rural area only or widely adopted. The M&E system should include the following elements (a) outcome/impact evaluation (did the conditional cash transfer achieve the desired goals?); (b) implementation analysis (Are al l parts o f the program in place? Are the health and education interventions implemented in all regions?); and (c) process analysis (How i s the program being delivered? What benefits do participants receive? H o w do they get them?). The development o f a monitoring and evaluation system covering all these elements i s one o f the priority challenges facing Juntos. The monitoring system should include the mothers DNI and the unique personal identification numbers (CUI) which are being included in the birth certificates all o f children under new ru les issued by RENIEC .

36

3 THE REDISTRIBUTIVE AND POVERTY IMPACT OF PERU'S FOOD PROGRAMS

69. This chapter measures the effectiveness of food programs in redistributing income and reducing poverty in Perulg. It investigates coverage and benefit adequacy, presents a benefit incidence analysis, and simulates their impact on poverty and inequality. The findings show that despite pro-poor distributional patterns, the small unit subsidies limit the redistributive, poverty, and inequality impacts o f even the best targeted programs. Their impact on reducing malnutrition i s also modest.

70. The chapter i s organized in four sections. Section 3.1 presents the criteria used to assess program effectiveness and efficiency. Section 3.2 looks at coverage and the level o f the benefits. Section 3.3 deals with targeting. The overall impact on poverty and malnutrition i s summarized in section 3.4.

3.1 Criteria for Assessing the Redistributive Role of Food Programs

7 1. In contrast to public spending on health and education-services with substantial externalities that may justify their universal provision-SSN transfers are privately consumed goods which should normally be targeted to the poor households or areas. The main rationale for safety net transfers i s promoting equity, so they should be focused, especially, towards the extreme poor and it i s important to assess how much they contribute to poverty reduction. This chapter focuses on the food programs, the largest component o f the SSN sector in terms o f budget and numbers of beneficiaries. Their impact on poverty reduction i s assessed using three complementary criteria:

What share of the target group receives the program? To be effective, a program should cover a l l or a large share o f i t s target group. To capture this dimension of program performance, we estimate what proportion of individuals/households in the target group in each quintile receives the program.

How adequate is the benefit offered by the program? Substantial coverage of the target group i s a necessary, but not sufficient condition to make a program effective. Using a public health analogy, to be effective, programs should provide adequate treatments. The subsidy channeled by these programs i s compared to the pre-transfer consumption o f the beneficiaries, especially the poor beneficiaries.

How well are the program resources targeted to the poor and extreme poor? To assess how efficiently transfers are focalized, a benefit-incidence analysis i s undertaken*'. Estimates are presented o f the share of the subsidy that reaches the extreme poor (Ql) and other quintiles. Previous studies have analyzed the incidence o f food programs in Peru based on the distribution of program beneficiaries across quintiles. However, this approach i s only valid if similar benefits are received by everyone. Peru's food programs are complex, with variations in the number o f rations consumed per month and the amount o f subsidy given (some get free meals, while others pay a contribution, which differs from program to program). In addition, subsidies differ substantially across departments. The distribution o f public spending across quintiles in this study i s estimated by adjusting the program participation with the take-up rate, the level o f subsidy from each region, and the subsidization rate. The analysis covers the seven largest SSN programs for which there are data in the ENAHO 2003

The chapter does not evaluate other possible impacts of food programs. Most programs in Peru have a multitude of objectives. For example most food programs aim enhancing food security, improving nutrition, improving school attendance and academic performance, offering support to local farmers and domestic producers, developing social capital, or promoting community based organizations. However many times these objectives are not clearly specified and measurable goals are not established. Given that most programs claim that their main objective i s to help the poor children and their families, it seems justified to assess how they achieve this objective. *' Benefit incidence identifies who i s benefiting fiom public services, and describes the welfare impact on different groups of people or individual households of government spending (Demery 2004). I t does this by combining information about the unit subsidy transferred by a program (obtained from administrative data) with information on the participation in the programs (obtained from household survey data).

37

survey, which account for 80 percent o f SSN beneficiaries and spending: (i) Vas0 de leche; (ii) Comedores populares; (iii) Desayuno escolar; (iv) Almuerzo escolar; (v) Comedor infantil; (vi) A Trabajar Rural; and (vii) A Trabajar Urbano. Full details are reported in Annex 1.

3.2 Food program coverage and benefit levels

72. Compared to the L A C region, Peruvian food programs have high coverage, but transfer extremely small benefits (Figure 3-1). Over 40 percent o f Peruvian households benefits from some type o f food program. The coverage o f Peru’s food programs, alone, surpasses the overall coverage o f social assistance programs in Argentina, Brazil, Chile, and Columbia, al l o f which have relatively well-developed social assistance systems. However, Peru’s spending on such programs i s lower than in other countries in the region, so that the average value o f transfers per person i s between 5 times and 20 times smaller in Peru than in other countries (Figure 3-1; right panel). The value o f the food programs benefits i s less than two percent o f the total consumption o f beneficiary households. The most popular program, Vas0 de Leche, transfers, on average, less than US$2 per month per beneficiary, the equivalent o f 5 percent o f the extreme poverty l ine o f S/.115/month (about US$1.2 per day).

Figure 3-1: Coverage and benefit levels of Peru’s SSN Programs compared with LAC Coverage - A! Social Assistance

Share of Papulation N m g in Households Receiving at least one Benefit

!. 40% g 30%

1 20%

10%

0% Peru LAC Argentina Brazil Chiis Columa Guatemla

Average Value of Transfers (uS$pFp)- Social Assistance ..........................................................

40 t ............ ~~ .............................. ~~~~~ .....

30 L a = 20

10

Peru LAC Argsnbna Erarii Chile C o b h a Guatemla

Source: Based on Lindert, Skoufias, and Shapiro (2005).

73. Peru scores high on coverage o f the poor with SSN programs, compared to other L A C countries, and this i s almost entirely due to two programs: Vas0 de Leche and Desayuno Escolar (Table 3-1). All other programs cover less than 5 percent o f the population. Consolidating some o f these tiny programs may economize on scarce human and financial resources, and help to capture economies o f scale.

74. Rural residents are better covered than urban residents. This i s a positive feature o f the Peruvian S S N system, given the higher incidence o f poverty and extreme poverty in rural areas (Table 3-1). However, reaching the remaining 22 percent o f extremely poor children in rural areas with no access to feeding programs could prove a challenge, given the country’s complicated geography.

75. The best way to analyze how effective the food programs are in reaching their beneficiaries i s to analyze the coverage relative to the target group o f each program. For example, the primary target o f Vas0 de Leche i s children under age seven, Almuerzos and Desayunos Escolares targets school-aged children in poor areas, and Comedores Populares targets al l poor households.

76. With the exception o f Vas0 de Leche and Desayuno Escolar, which cover 44 percent and 17 percent o f their target groups, respectively, all other food-based or workfare programs are not effective in covering their target group (Table 3-2). To cover i t s target group o f “all poor households,” the budget o f Comedores Populares would have to increase 1 0-fold-clearly an unfeasible scenario. If programs are small compared to their target groups, they fail to accomplish their objectives, and the selection o f beneficiaries i s prone to political manipulation.

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Table 3-1 : Household-level coverage of Peru’s food programs

Note: The target group for Vas0 de Leche i s children aged 0 to 6 and pregnant and lactating mothers; for Comedor Popular it i s poor families; for Desayuno and Almuerzo Escolar it i s children aged 7 to 13. The category “other” includes PACFO, PANFAR, and WAWAWASI which target younger children.

Source: Author’s estimates based on ENAHO 2003/04 Survey, MEI.

77. The main food programs transfer very small amounts relative to household consumption. On average, the subsidy represents less than 2 percent o f the consumption o f a beneficiary (Annex 1 describes how the subsidy was estimated). This varies l i t t le with the type o f program. The most “generous” program i s the comedor popular for which, on average, the subsidy represents 2.2 percent o f the consumption o f a beneficiary. In relative terms, such transfers are more important for the poorest. For example, the subsidy from Vas0 de Leche represents 3.9 percent o f the consumption o f those in the poorest quintile, and only 0.7 percent o f those from the upper quintile. This reflects the fact that per capita consumption in the poorest quintile i s one ninth o f that o f the richest quintile. However, even for the extreme poor, subsidy from the four largest food programs i s only a tiny fraction o f their consumption deficit (the gap between their consumption and the poverty line).

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Programs

Vas0 de Leche Comedor Popular

Almuerzo Escolar Total

Desayuno Escolar

3.3 Food Programs ’ Targeting Performance

78. Peru’s food programs are better targeted than i s sometimes thought. Many previous analyses o f the food programs in Peru have pointed to inadequate targeting and large leakages toward unintended beneficiaries (Vasquez 2005; Alcazar 2003). Using household-level data, the present study, however, finds that a large part o f benefits go to the poor (either moderate or extreme). In 2003, 30 percent o f total spending of W.816 million reached the poorest quintile and another 24 percent reached the 2nd poorest quintile (Table 3-4). Peru’s food programs also have better targeting performance than other countries in LAC, outperforming similar programs in Colombia and Guatemala (Figure 3-2). This comparatively good performance i s due mostly to high-quality geographical targeting. However, targeting performance varies significantly from one program to another; desayuno escolar (with 71 percent o f benefits going to the bottom two quintiles) and Vas0 de leche (with 55 percent) are better targeted than the comedores populares (which achieve only 41 percent, almost exactly pro-rata with the population share).

Total Consumption quintiles Poverty status Area I I1 I11 I V V PX PNX NP Urban Rural

2.0 3.9 2.2 1.8 1.3 0.7 4.0 1.8 1.3 1.5 2.7 2.2 4.5 2.4 2.6 1.3 1.4 4.3 2.5 1.4 2.0 2.7 1.7 3.3 1.6 1.1 0.6 0.5 3.2 1.5 0.8 1 .o 2.2 0.9 1.7 0.9 0.6 0.4 0.1 1.7 0.8 0.4 0.6 1.0 1.8 3.5 1.9 1.6 1.2 0.7 3.5 1.7 1.1 1.4 2.3

40

Table 3-4: Targeting accuracy: Share of public transfers reaching each quintile By Quintile Spending

Total Q1 Q2 Q3 Q4 Q5 mil SI. Vaso de leche 100% 29% 26% 22% 17% 7% 3 56 Comedorpopular 100% 20% 21% 28% 22% 9% 98 Desayuno escolar 100% 44% 27% 18% 8% 3 yo 117 Almuerzoescolar 100% 45% 33% 15% 6% 1 Yo 24 Comedorinfantii 100% 43% 32% 14% 9% 3 yo 26 Other 195 Allfoodprograms 100% 30% 24% 23% 16% 6% 816

Source: Based on Lindert, Skoufias, and Shapiro (2005).

Figure 3-2: Targeting Derformance of selected Latin American food Drograms I - -.

Benefit hcidence of School Feeding Rograms % of Benefits Received by the Poorest Two Cluintiles

80%

70%

60% 50%

40% 30% 20% 10%

.. . . . .

. .. ..

1 Colombia I Guatemala I R r u 1

. - Benefit Incidence of Conplerentary Food Rograms

% of Benefns Received by the Foorest Two Quintiks 1 80% ................ ~ . . ~ ~ ............... ~~.~ ....... ..

70% 60%

50%

40%

30%

20%

10%

0%

j102

m r u I

79.

Source: Based on Lindert, Skoufias, and Shapiro (2005).

Nevertheless, Peru's feeding programs are less well-targeted than cash transfer (CT) programs in LAC, in Europe and Central Asia, and in OECD countries (Figure 3-3). There are two factors that might explain this. First, by design, the relative income threshold used to target benefits i s substantially higher in Peru's S S N programs than i s the norm in cash transfer programs in OECD, ECA, and some L A C countries. Peru's programs target the poorest 50 percent o f the population. In contrast, most C T programs in OECD and ECA countries target the poorest 10 percent o f the population, while the other L A C comparators focus on the poorest 20 percent. Second, few programs in Peru use individual or household- level targeting methods, which are normally associated with better targeting performance, such as means or proxy means tests.

41

Figure 3-3: Targeting Performance of selected Cash Transfer programs and Peru’s food programs - - - - -

Share of Resources Reaching the Poorest Quintile

100 ~.~

go ..~........... 1 80

70

60

50

40

30

20

10 0

~

LAC Countries 1 ECA Countries 1 USA I Peru - Food-based Rogram I I Note: GMI=Guaranteed minimum income, TANF= Temporary assistance for needy families, Source: Based on Lindert, Skoufias, and Shapiro (2005); Castaneda and others (2005) for L A C countries and US; and Tesliuc and others (2005, forthcoming) for the ECA region.

3.4 Food Programs ’ Impact on Poverty and Malnutrition

SO. Impact on reducingpoverty. To estimate the impact on poverty reduction, w e simulate the level o f poverty that would prevai l if food-based programs were suddenly stopped. The results are presented in Figure 3-4.21 Despite reasonable targeting and extensive coverage, food programs have only a modest impact on poverty and inequality. In the absence o f food programs the poverty headcount would increase from 54.7 percent t o 55.2 percent; this change i s not statistically significant. The impact o f food programs i s s l ight ly larger on those in extreme poverty; in the absence o f the programs the extreme poverty headcount would increase by 4 percent. Food-based programs also have l i t t le impact on inequali ty (they reduce the consumption Gini by only 0.5 percent). The l i ke l y reason for this disappoint ing outcome is that the ma in programs distribute very smal l benefits which have l i t t le effect on the consumption def ic i t o f their beneficiaries. As noted above, the biggest program, Vas0 de Leche, transfers less than U S $ 2 per month per beneficiary - the equivalent o f 5 percent o f the extreme poverty l ine.

21 The counterfactual consumption i s estimated as observed consumption minus the value o f the transfer. This simulation does not take into account the behavioral response o f households to the reduction in public transfers. Confronted with a reduction in public transfers, households might be expected to react by working more, mobilizing other productive assets they have, and only as a last resort, by reducing their consumption. However, given that food-transfers are relatively small compared to the consumption o f the recipient households, the counterfactual consumption used here i s probably close to the true one.

42

Figure 3-4: The Simulated Impact of SSN Programs on Poverty reduction

Poverty Gap with and without Food Programs I I I

I I

40% I

35% I

30%

25%

20%

15%

10%

5%

0 %

30 5% 2 9 0 % ~

6 4 % 7 0 %

I

All population Beneficiaries All population Beneficiaries ~

I P o ~ r t y Gap Extreme Powrty Gap I

I Powrty gap in 2003 Simulated Powrty gap without Food programs 1

I

__.__

____ -I

Source: Author’s estimates based on ENAHO 2003/04 Survey, INEI.

81. Impact on malnutrition. There i s no evidence that Peru’s food programs are contributing much to the reduction o f non-monetary dimensions o f poverty in Peru. Malnutr i t ion remains high, especially among the poor. In 2000, 26 percent o f children s t i l l suffered from chronic malnutrition (deficient height- for-age), and this rose to 47 percent o f the children in the poorest quintile.

82. One reason why so much malnutrition can co-exist with so many food programs i s that few o f the programs target children under 2 years o f age, which i s the “window o f opportunity” where malnutrition can be combated effectively. School feeding programs intervene too late in the life-cycle. Moreover, Peru devotes a disproportionate amount o f i t s food and nutrition program budget to purchasing and distributing food, instead o f supporting strategies that focus on prevention, promotion, and sustainable behavior-based solutions. I t i s well-established that food transfers are unlikely to have a significant nutritional impact, when little attention i s given to feeding and health care practices, to micronutrient deficiencies, and to the rigorous monitoring o f individual children’s growth curves, to identify at-risk individuals and devise adequate responses.

83. A handful o f nutritional programs offer more meaningful benefits but cover only a tiny fraction o f their target group hence do not make a dent in the national malnutrition rate.22 One program-the Supplementary Food Program for Groups at Risk o f Malnutrit ion (PACFO)---focuses on the under-two age group in rural areas. PACFO’s impact evaluation revealed excellent targeting performance and relatively good nutrition outcomes (Maximize and Cuanto 2003). The program, however, has a small budget and operates only in eight departments, which implies that many poor children at risk o f malnutrition are not covered. In addition, it appears that the transfer o f the program from the National Institute o f Health to P R O N A A has weakened the program’s health education component.

22 The rich literature on the performance o f Peru’s food programs i s summarized in Annex 2.

43

4 THE W A Y FORWARD

4.1 Key issues facing Peru’s SSN system

84. Due to the lack of a clear accountability structure, and political economy factors, most of Peru’s traditional SSN programs contribute little to reducing poverty or malnutrition. There i s a generalized “low quality equilibrium” in the social assistance and nutrit ion sector, rooted in the lack o f clear objectives and measurable goals. This has opened the way for the “capture” o f programs by interest groups, and for their polit ical manipulation. As a result o f such polit ical economy dynamics, there are major problems with the effectiveness o f decentralized programs such as Vas0 de Leche and Community Kitchens, and few o f Peru’s SSN programs reflect best practice in their technical design. For instance, the nutrition interventions generally lack a focus on children under two years old, where they would have the greatest effect. M a n y programs also have overlapping beneficiaries and the prevalence o f small programs leads to relatively high administrative costs. The Government has now begun to address this issue through the social program optimization process, which has already managed to reduce the number o f social programs in Peru to a third o f the previous level, and through plans to develop a Single Beneficiary Register for the social programs.

85. There is a vicious circle of poor performance and low funding. SSN spending i s l o w compared to national needs and regional standards. Peru spends 0.7 percent o f GDP on the SSN, substantially below the region’s average o f 1.3 percent o f GDP. The level o f spending i s also small compared to the pre- transfer poverty gap (6.8 percent o f GDP), but represents slightly more than ha l f o f the pre-transfer extreme poverty gap (1.3 percent o f GDP). Without doubt, the mediocre performance o f Peru’s social assistance programs has reinforced the l o w overall level o f social assistance spending. MEF has become skeptical o f approving “more o f the same”, setting up a vicious circle o f poor quality and insufficient funding.

86. Although they are generally targeted on the poor, most SSNprograms attempt to cover too many beneficiaries, resulting in benefits that normally are too small to make a diference. Most SSN programs aim to target poor households, that is, the bottom 44.5 percent o f the income distribution in Peru23. But when this broad target group i s coupled with l o w overall spending, the inevitable result i s very small subsidies for a large number o f people. This limits the SSN’s impact on poverty and inequality. The food programs illustrate this well. In 2003, they covered an estimated nine m i l l i on beneficiaries (a third o f the total population) with an average transfer o f only $2/month, equivalent t o only 3 percent o f the per-capita income needed to surpass the poverty l ine or 6 percent o f that needed to surpass the extreme poverty line.

87. Peru ’s spatial poverty maps are used below their potential. The country has a long history o f using poverty maps to target expenditures to poor areas, and geographical or categorical targeting i s presently used to channel about 80 percent o f the SSN spending24. The first map was produced as early as 1977, based on an index o f unmet basic needs (UBN). Since 1991, FONCODES developed district-level poverty maps based on UBN techniques, and used them to redirect social expenditure toward the poor areas. After 1996, the Ministry o f Economy and Finance (through the statistics institute, INEI) developed improved poverty maps based on census and survey data to be used by to allocate pro-poor spending toward the poorest rural areas. However, although the legislation requires a l l public spending on SSN to be allocated using a pro-poor allocation index, in practice, the most spending i s distributed based on

23 . Following normal practice, income estimations used throughout this paper are based on ENAHO data for household expenditure, which i s considered the best proxy for income in survey data.

A recent international review o f the accuracy o f different targeting methods by Coady, Grosh and Hoddinott (2004) finds household-level targeting (means- or proxy-means test) and workfare have the highest targeting accuracy, judged by the degree o f focalization o f program resources toward the poor. Geographical targeting occupies the median place in terms o f targeting accuracy. However, there are other factors to consider in chosing targeting mechanisms -including cost-efficiency in administering the mechanism, maximizing the coverage o f the poor, and transparency to enhance credibility, perceptions o f fairness, and reducing fraud.

24

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historical allocation. Moreover, the program-specific legislation on resource allocation sometimes conflicts with poverty map formulas, as in the case o f Vas0 de Leche, where a third o f the budget i s earmarked by law for the relatively rich regions o f Lima and Callao.

88. Reliance on community-based organizations leads to problems of exclusion. Many SSN programs in Peru rely on CBOs to deliver the benefits. Initially, implementation by CBOs brought substantial advantages: it avoided the creation o f a large public apparatus, “crowded” in community resources, and contributed to social capital and to the empowerment o f women. With time, however, this model reached i t s limits, and many poor people remain underserved, while some programs have been “captured” by the beneficiaries who gained access to the subsidies early on.

89. Reliance on in-kind transfers may impair the eflciency of the SSN. Apart from workfare schemes and the recently established CCT program, Juntos, all Peru’s social assistance programs distribute food. Food provision has been politically more acceptable than cash transfers, due to the bel ief that men might use cash to buy alcohol. However, there i s no clear evidence that food distribution increases food consumption by more than an equivalent cash transfer. Food transfers also have disadvantages, from the point o f view o f economic efficiency, as they restrict consumer choice and involve high transaction costs.

Box 2-4: Municipal accreditation and performance agreements for the accountability of decentralized SSN programs in Peru: lessons learned

In June 2004, as a prior step for the decentralization o f food programs, Congress approved an Accreditation Law, under which the National Decentralization Commission (now abolished) would certify the management capacity of local governments (provincial and district) and MIMDES negotiates performance agreements to regulate their management of the programs. However, the criteria for the transfer o f responsibilities are stated in very general terms, and the law fails to specify the consequences o f non-compliance with the targets included in performance agreements.

The fmdings o f a qualitative study of the accreditation process in 18 provincial and district municipalities in the departments of Piura, Cusco and San Martin, undertaken as background for this paper, suggest that accreditation o f municipalities alone i s no guarantee o f better service delivery. It needs to be accompanied by municipal capacity building. The study highlighted several weaknesses: First, the process focuses on verifying the existence of documents and plans, and not on validating capacity to assume the new responsibilities. Second, the accreditation i s not linked to corrective actions to strengthen the identified weaknesses. Third, accreditation i s perceived as a “rubber - stamping” process: many municipalities which fel t they were unprepared to assume new responsibilities were accredited anyway. As one municipality in the department o f Piura said: “...there was no problem obtaining the accreditation- we were only asked to present papers”.

Among the positive experiences arising from decentralization reported in the study are: the adaptation of the food basket to local preferences, the introduction of procurement from local producers, the creation of municipal associations to execute procurement and distribution, and enhanced accountability through the comitb de gestidn and comith de adquisicidn, and community and civil society oversight.

(Based on qualitative data research on participation and service delivery carried out by Propuesta Ciudadana group).

90. Institutional disintegration undermines accountability and eflectiveness. Peru’s social protection programs-pensions, labor market policies, and social safety net programs-are scattered across diverse ministries, agencies, and levels o f government. The Ministry o f Economy and Finance (MEF) i s in charge o f the pension system and the largest food program, Vas0 de Leche. The Ministry o f Labor and Employment i s in charge o f the urban workfare program and other labor market interventions. The Ministry o f Women and Social Development (MIMDES) i s responsible for all the food-based programs (other than Vas0 de Leche), for FONCODES (the social fund for basic infrastructure investments), and for programs for children and youth at risk, internally displaced people and the elderly. MINSA i s responsible for nutrition but other agencies such as MIMDES, Juntos and the P C M (through the new Plan CRECER) also play an important role. Other ministries (housing, energy, and mining) operate subsidy schemes (housing, energy) that also, conceptually, belong to the social protection sector.

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9 1. Decentralization has led to a rapid shgt in responsibility for program implementation to sub- national governments but has not yet established clear, workable accountability frameworks for Peru ’s social protection programs. Decentralization o f SSN programs started in the ‘80s with Vas0 de Leche. More recently, three food programs -- Comedores populares, Albergues y hogares, Alimentos por Trabajo - were transferred to provincial municipalities. FONCODES’ small scale infrastructure program i s being transferred to district municipalities; and PRONAA’s feeding programs, to provincial government In 2005, the lion’s share o f SSN spending remained centrally controlled: in 2005 only 15 percent o f PRONAA’s and 26 percent o f FONCODES’ budgets were decentralized. However, in 2006 a much larger share o f funds i s budgeted for decentralization26. As the decentralized S S N model i s further developed, it will be critical to establish equitable resource allocation rules at a national level: ceteris paribus, individuals should have equal opportunities to benefit from safety net programs, wherever they live. To ensure that decentralization leads to improved outcomes for beneficiaries, it will also be critical to establish a clear accountability framework, giving local government reasonable discretion in program implementation and clarifying the role o f central government in negotiating goals and monitoring the performance o f the sub-national agencies which are to be charged with program implementation and service delivery. One instrument that has been applied to this end are municipal accreditation and performance agreements; however (as was detailed in Box 2.4), much work remains to be done to ensure that the decentralization process produces better outcomes for the beneficiaries. A differentiated strategy should be developed, which takes account o f the different levels o f capacity in larger and smaller municipalities.

25 In 2006 the government started a pilot in six provinces to consolidate school feeding and nutritional programs, prior to their transfer to provincial municipalities. The plan i s to form two programs, one for children 6 months to three years old and pregnant and lactating mothers; and one for school age children, to replace the present set o f over 20 programs. 26 The budget for 2006 planned to transfer 70 percent o f the FONCODES funds to 1149 district municipalities (out of 1647 municipalities eligible to receive FONCODES funds).

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Box 4-1: Overcoming the political economy constraints to the reform of existing programs One option for improving the performance of the SSN sector i s the reallocation of funds to better performing programs. But in Peru, about half of SSN resources are implemented by community-based organizations (CBOs) which enjoy considerable political legitimacy and have a record o f successfully opposing reallocations of funding. Thus, a major challenge for SSN policy in Peru i s to fmd ways to improve the performance of such programs by improving their design and implementation and strengthening the accountability framework

As outlined in Box 2-1, the implementation o f food-based programs via CBOs brought substantial advantages in the early stages. CBOs provided a service delivery administration to reach the poor in a given area, allowing the government to focus on the geographical allocation of resources using poverty maps, which could be monitored easily in Lima, without the need for a large public administration. However, more recently some programs have been effectively “captured” by their beneficiaries. The government has not enforced exit policies, fearing loss o f political support, and has even legislated loopholes, such as the Vuso de Leche norm that allows children aged 7 to 13 to continue benefiting, although the program i s intended for those aged 0 to 6. Since the program budget i s fixed, the low exit rate prevents others from entering. Such constraints mean that only the marginal increase in the program budget that can be assigned to poorer areas, as happened during 2001-04.

To improve the performance of the CBO-operated programs, the SSN system should promote transparent beneficiary selection procedures and should resist rule changes that permit individuals to stay in the program beyond the appropriate time. I t should also promote administrative mechanisms which tend to “self-select” appropriate beneficiaries. For example, the daily delivery o f benefits increases transactions costs and discourages the non poor - whose time has a higher opportunity cost - from seeking the benefit. As appropriate, the CBOs should also be used as a bridge between the primary health and education systems and the communities which they organize.

To achieve these outcomes, clear accountability frameworks should be established, with goals for the number and characteristics of beneficiaries, for unit costs, and for outcomes (such as improved nutritional status), which should be negotiated with each program. Once such a framework i s in place, the resource-allocation rules of the system should tie future funding to acceptable outcomes on these goals and indicators.

4.2 Recommended strategv

92. CZarijy the structure of the SSN system. Peru needs an articulating framework for i ts poverty reduction and SSN strategy, in which the goals o f each program - and the system as a whole - are properly defined and understood by the relevant actors. This should include a clear assignment of responsibilities within the Central Government, and between Central Government and municipal authorities with regard to regulation, financing, implementation, and program monitoring and evaluation. The Garcia administration i s starting to address this need through the process o f fusion, integration and articulation o f social programs, which aims to clarify objectives and increase effectiveness. The Inter- ministerial Commission for Social Affairs (CIAS) has prepared an inventory o f 81 programs in 12 broad programmatic areas, which have scope for fusion, rationalization or improved coordination - including 10 dedicated to food distribution and a further 9 linked to nutrition. It has estimated that 80 percent o f these programs have administrative costs greater than 10 percent o f their budgets.27 During 2007, it will develop detailed proposals to implement this strategy, to be incorporated in the 2008 budget proposal. In each sub-sector a coordinating sub-committee o f CIAS will be established to oversee the process. The goal i s to improve coverage, reduce leakage o f resources to unintended beneficiaries, reduce administrative costs, improve transparency and optimize impacts. This will be further reinforced by the development o f a Single Beneficiary Register for social programs, underway in MIMDES.

*’ This i s an estimation made by MEF consultants. Although i t i s being strengthened, the Integrated Financial Administration System (SIAF) s t i l l contains incomplete information on the breakdown between administrative costs and direct service provision costs for some programs.

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93. Anchor the program optimization process to a coherent national social safety net (SSW and poverty reduction strategy, dwferentiated for rural and urban areas. The program optimization process will produce the best results if it i s informed by a clear vision o f the overall strategy o f the government to tackle poverty and vulnerability in Peru. The strategy should be differentiated between the 30 largest cities and the rest of the country (small towns and rural areas), to reflect the very different nature o f their needs and potentials. There are vast differences in capacity between the municipal administrations in the major cities and the rest o f the country, so the implementation arrangements for the SSN strategy should be differentiated. In the 30 biggest cities, S S N programs should be decentralized, to ensure better responsiveness to local needs and improved transparency. In the rest o f the country, for the foreseeable future, strong national agencies wil l be needed to ensure that S S N programs are effective, but they should work with local governments, as appropriate.

94. As well as differentiating implementation arrangements, SSN interventions themselves should also be differentiated between the urban and rural parts o f Peru. For instance, workfare programs to deal with cyclical unemployment only make sense in urban areas; and a nationally-led small-scale infrastructure program (such as FONCODES) only makes sense for rural areas. However, a central goal o f S S N programs, in both urban and rural areas, should be to tackle child nutrition, working in close liaison with MINSA. The SSN's standards and accountability system should place a heavy emphasis on this theme. The relevant programs (including Juntos and all the feeding programs) should be focused on nutrition outcomes. They should be held accountable for what they achieve to improve the quality and effectiveness o f growth monitoring, improve diets and reduce malnutrition among children under-five in their respective target populations.

95. The rural SSN strategy should focus on chronic malnutrition among children under five and needs a strong national leadership, anchored on the Juntos CCT Program Due to the limited capacity o f municipal administrations in small towns and rural areas, there i s a continuing need for a strong leadership from national programs, working in liaison with provincial governments. The central goal o f the rural strategy should be to reduce chronic malnutrition. At present, about a quarter o f Peru's children are stunted. Changing this outcome will require changed feeding and health care practices; which in turn will depend on increased parental awareness o f the problem; improved understanding o f good nutrition; and the economic wherewithal to turn this into improved feeding practices. Juntos could have a major impact on all these fronts and could thus play an important role in transforming nutritional outcomes in i ts target communities. In the f i rst place, it offers substantial cash benefits (about $30 per month) to beneficiary families, significantly improving their consumption capacity. Juntos i s also well targeted on communities with high malnutrition rates. During 2007, it will reach more than 600 districts nationwide. These cover some 10 percent o f the national population - but almost 40 percent o f stunted children. Juntos i s working with the health system (MINSA) to ensure that regular monitoring o f children's nutritional status and effective counseling are offered to all Juntos beneficiaries. This wil l also require the development o f nutrition standards which are comprehensible to parents28.

96. I n the 30 biggest cities, where municipal capacity is greater, SSN and poverty reduction programs should be decentralized. The financing o f decentralized S S N programs should be supported by fiscal transfers, based on transparent, equitable criteria (poverty and population statistics). The government should encourage transparent decision-making by the municipalities, through requirements for budget consultation, participatory monitoring o f budget execution and the strengthening o f local poverty maps. A decentralized administration, coupled with a strong accountability framework, will open up spaces for the reform o f existing programs (such as Vaso de Leche) where political economy factors have made sweeping national-level reform difficult to achieve. Once some local governments have

28 The World Bank's Recurso program o f studies and technical assistance - o f which this report forms a part - i s supporting the reorientation o f Juntos to concentrate on nutrition through a TA program, and i s also supporting MINSA and CENAN in the development o f easy-to-understand nutrition standards, through a new video.

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decided to improve the targeting of their programs and can show better outcomes, the demonstration effects o f benchmarking those results will generate increasing pressure on other municipal governments to do likewise. And at a local level, the authority and credibility o f municipal governments may offset opposition to reform from the entrenched interest groups.

97. At a programmatic level, the strategic foci o f the urban SSN should be (a) re-distributional food transfers focused on poor children, to alleviate poverty and improve nutrition outcomes, and (b) an effective safety net mechanism to deal with labor market shocks. The urban SSN should aim to provide effective food transfer programs targeted on poor children, and to keep in place a safety-net mechanism to tackle cyclical unemployment. SSN programs for the 30 largest cities should be operated by municipal governments, with financial support from fiscal transfers. This should be coupled with the strengthening o f transparency requirements, to promote community involvement in municipal budgeting and participatory monitoring o f budget and program implementation - as mandated in the 2007 Budget Law. This would provide a basis for benchmarking and the promotion o f best practices.

98. For both centralized and decentralized SSN program, strengthened accountability frameworks are the key to improved outcomes. To break out o f the low quality equilibrium, the SSN system needs clear objectives and quality standards, and targets for improved outcomes, with a particular emphasis on chronic malnutrition. This line o f action i s now being pursued by the Results Based Budgeting (RBB) office in MEF. The accountability and results management process should focus first on the major programs (such as Vas0 de Leche, Comedores Populares, School Breakfasts, FONCODES and Juntos, which account for over 70 percent o f SSN resources). These programs have many strengths. FONCODES compares well on a global scale with similar programs on several indicators. A Trabajar Urbano i s also in line with world-wide best standards. Vas0 de Leche has strong community roots that vitiate against crude political manipulation from the centre, and i s better targeted than i s sometimes thought. Juntos has incorporated cutting-edge design features from Mexico’s Oportunidades program, and i s well targeted. However, in each program, important gains could be achieved through pragmatic, feasible reforms in program design and implementation arrangements.

99. Juntos, as was argued above, should be the central program in the rural SSN. This CCT program couples large income subsidies with incentives to investment in human capital, and - working in effective liaison with MINSA - could have a major impact on chronic malnutrition. Juntos should give special priority to promoting attendance at growth monitoring and counseling sessions, supporting MINSA to offer improved nutritional and health services. Juntos ’ expansion should be limited to rural areas, giving continued priority to places with high rates o f chronic malnutrition. I t should also continue to support RENIEC’s efforts issue identity documents. However, to ensure the expansion i s effective, the beneficiary identification system, system o f conditionality and the monitoring and evaluation system should all be strengthened. Among the issues to address are: a) whether the household-level component o f the beneficiary selection system i s adding enough value to justify i t s cost; b) the choice o f appropriate conditions (l i t t le i s gained by the education conditions, given the level o f enrollment) and establishment o f an efficient conditionality monitoring system; c) the adequacy o f the supply-side arrangements in nutrition and health; ad d) the need for a robust monitoring and impact evaluation system. If these issues are successfully addressed, Juntos could become a key articulating element o f Peru’s social sector in low income rural areas.

100. Vas0 de leche i s the key food program by size and importance. I t s impact on reducing malnutrition in urban areas could be improved by (i) focusing resources on the legally defined group o f beneficiaries (children 0-6 years old) - and preferably concentrating on children under 24 months; (ii) improving procurement and using fresh instead o f more expensive evaporated milk and ensuring on-site consumption; (iii) providing a service seven days a week instead o f the actual practice o f giving milk on fewer days to cover more beneficiaries; and (iv) providing complementary health and nutrition education. The targeting performance could be improved by enforcing the oversight over the Vas0 de leche

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committees and by eliminating legislation that confines one third o f the resources to Lima and Callao provinces.

10 1. Socialfind. In recent years, a process has been underway to decentralize FONCODES and lower i t s funding in the expectation that municipalities would increase investment to compensate. The present government has announced that FONCODES will be closed. However, many rural municipalities lack the capacity to develop and implement projects. In the face o f such constraints, Peru s t i l l needs to reach closure on the definition o f a system for small-scale rural infrastructure investments, which: (a) assigns resources using poverty targeting techniques; (b) provides adequate support to district municipalities; (c) establishes effective accountability mechanisms; and (d) ensures adequate coordination with the appropriate line agencies. FONCODES or i t s successor agency could make a vital contribution to building the capacities o f district governments to forging strong partnerships with communities and local service providers for effective small-scale infrastructure provision.

102. A Trabajar Urbano has achieved effective self-targeting o f the poor and good impacts on household income earning and community assets. Although the economy i s presently buoyant, Peru should keep the program operating, maintaining a minimal program that can be scaled up during recessions or natural disasters in a countercyclical manner. To improve implementation, some fine-tuning i s required: (a) ensure that the wage level i s set with reference to real market conditions in the low-income informal sector; (b) consider the option o f integrating the workfare programs with municipal investments to ensure quality (in terms o f supplementary resources needed to complement the labor production factor) and maintenance o f assets created; and (c) consider as possible projects not only the construction o f physical assets but also the provision o f social services (caregivers, health promoters) that might increase the participation o f women.

103. Move towards a high-quality equilibrium, increasing SSN financing towards the average in middle-income countries of 1.5 percent of GDP. Finally, for the reformed SSN programs to have a greater impact on reducing present and future poverty, more resources wil l be required. To move Peru’s SSN system from the existing “low quality equilibrium” towards a “high quality equilibrium”, as well as ensuring improved program quality and measurable outcomes on key goals, such as chronic malnutrition, it will also be necessary to reverse the erosion o f fbnding which has flowed from the historic failure o f existing programs to generate such outcomes. As part o f the implementation o f results-based budgetary management in Peru, the process o f enhancing resources for the SSN should accompany - and provide incentives for - the reform process itself. Additional resources should be channeled towards those interventions that can demonstrate success in establishing robust accountability frameworks and documenting strong impacts.

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BIBLIOGRAPHY

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Castaiieda, Tarsicio, and Kathy Lindert, with BBnBdicte de la Briere, Luisa Fernandez, Celia Hubert, Osvaldo Larraiiaga, M6nica Orozco, and Roxana Viquez. Forthcoming 2005. “Designing and Implementing Household Targeting Systems: Lessons from Latin America and the United States.” Washington, D.C.: World Bank.

Chacaltana, Juan. 2003. “El Impacto del Programa A Trabajar Urbano.” Mimeo.

Chacaltana, Juan. 2005. “La pobreza no es como lo imaginabamos.” Mimeo.

Cueto, Santiago, and Marjorie Chinen. 2001. “Impacto educativo de un programa de desayunos escolares en escuelas rurales del Perk” Lima.

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Gajate, Giselle, and Marisol Inurritegui. 2002. “El impacto de 10s programas alimentarios sobre e l nivel de nutrici6n infantil: una aproximacih a partir de la metodologia del ‘Propensity Score Matching’,” Lima: Grupo de Andlisis para el Desarrollo, April.

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Lindert Kathy, Emmanuel Skoufias, and Joseph Shapiro. 2005 forthcoming. “How Effectively do Public Tranfers in Latin America Redistribute Income.” Washington, D.C.: World Bank.

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ANNEX 2: ESTIMATING THE INCIDENCE OF PUBLIC SPENDING FOR FOOD PROGRAMS

In assessing the incidence o f public subsidy distributed through food programs, we recognize that simply looking at the incidence o f beneficiaries may be misleading. Program beneficiaries differ with respect to the monthly take-up rate (number o f portions consumed per month) and the rate o f subsidization (some get free meals, others pay). In addition, the level o f subsidy differs substantially across departments. To estimate the distribution o f public spending across quintiles, we multiply the (monthly) distribution o f beneficiaries with the take-up rate, the level o f subsidy from each region, and the subsidization rate

Many benefit-incidence studies use as a proxy for the distribution o f the public subsidies the distribution o f program beneficiaries across quintiles. The majority o f benefit-incidence studies o f food programs in Peru follow the same approach. However, the distribution o f beneficiaries reveals the distribution of public subsidy only for programs that give the same “treatment” to all beneficiaries, i.e. they provide a uniform benefit per individual or per households at regular intervals. The food programs operating in Peru are more complex.

In the case o f food programs, the distribution o f beneficiaries i s a poor proxy for the distribution o f public subsidy, for three reasons:

0 First, for some programs, the utilization o f food based programs varies across beneficiaries. For instance, 37 percent o f the beneficiaries o f the comedores populares receive meals daily, another 29 percent only few days per week, 16 percent only once a week and the rest at longer time intervals. To estimate the true incidence o f the public subsidy, we need to correct for the frequency with which beneficiaries use these programs.

Second, food programs have are two trpes o f beneficiaries: a f i rst group does not pay for the good or services received (get the full subsidy), while others are charged a partial co-payment. For instance, only one in fifth beneficiaries o f comedores populares receives meals free-of-charge.

Food-based programs produce food and deliver food-rations for free, or at subsidized prices (Figure 1). The ENAHO survey does not collect information on the level of public subsidy enjoyed by those who consume free or subsidized food-rations. Instead, the survey asks if somebody was benefiting from the program, with what frequency, and if they had to pay something for the food. From qualitative work, we know that the price o f a ration for paying beneficiaries i s 50 percent subsidized. With this information, we can estimate the amount o f public subsidy captured by each beneficiary.

Figure 1 Share of beneficiaries who receive food ration without co-payment, 2003

0

I

I --1

I mso de leche cornedor desayuno club de almueno comedor popular escolar madres escolar infantil

Source: Author’s estimation based on ENAHO 2003/04 Survey, INEI.

To estimate the level o f public subsidy enjoyed by a beneficiary of a food program, we used the following algorithm: First, we determined how many rations per month were received by each beneficiary. Second, we estimated the gross consumption by multiplying the unit cost o f a food ration (from administrative data) with the

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number o f rations consumed per month (reported in the ENAHO survey). For beneficiaries who enjoyed f iee rations, this i s the level o f subsidy they received. Finally, for beneficiaries who made direct contributions (cash, labor, or food) for their food, the value of subsidy was assumed to be 50 percent o f the gross consumption

Third, the unit subsidy varies substantially across the 24 departments o f Peru for many o f the programs under consideration. When computing benefit incidence using an average unit subsidy, we assume that the benefit i s homogenous for all beneficiaries or departments o f the country. In reality, in the case o f desayuno escolar, the annual unit cost varied from 143 Soles in L ima and Callao to only 87 Soles in Tacna. To estimate the true incidence o f the public subsidy, we need to correct for the variation in the level o f average subsidy distributed in different departments.

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ANNEX 3: ALGORITMO PARA EL CALCULO DE L A PROBABILIDAD DE POBREZA

A partir de un pool de hogares entre 10s aiios 2001 y 2004 (utilizando la Encuesta Nacional de Hogares), se hizo la siguiente regresi6n logistica:

donde la variable dependiente, Y, se construye a partir de la linea de pobreza de la siguiente manera: Logit: Y = a + PX + p

Y = 1, s i e l hogar es considerado pobre; Y = 0, s i e l hogar no es pobre

Por otro lado, a es una constante, p representa e l error y X esta constituida por la siguiente relaci6n de variables ex6genas (las cuales seran detalladas en pasos mas adelante):

1. analf-m: porcentaje de mujeres adultas analfabetas dentro del hogar. 2. edu-men: porcentaje de menores de edad que asisten a algun programa de enseiianza regular

dentro del hogar. 3. combusto: acceso a fbentes industriales de combustible industriales para cocinar (gas,

electricidad, kerosene). 4. no-equip: numero de artefactos ausentes en e l hogar 5. serv3 : tenencia de servicio de alumbrado, agua y servicios h ig ih icos en el hogar. 6. tipom2: grupo de tipos de vivienda 2. 7. tipom3: grupo de tipos de vivienda 3. 8. tipom4: grupo de tipos de vivienda 4.

Los resultados de la regresi6n son:

Variable Coeficiente analf-m 1.1832

[ 12.661 * * * edu-men 0.2276

[5.13]***

[ 12.841 * * * no-equip 0.4446

[27.40] ** * [3.23]***

[ 5.5 51 * * * [ 14,861 * * * [ 17.53]***

[ 12.48]*** Observaciones 17980 Pseudo R2 0.182

Valor absoluto del estadistico Z en corchetes * significativo a1 10%; ** significativo a1 5%; *** significativo a1

combust0 -0.7624

serv3 -0.3769

tipom2 -0.2593

tipom3 -0.8584

tipom4 -1.3172

Constante ( 0 ) -1.3461

56

Dentro de la base de Caracteristicas de la Poblaci6n (Cuestionario 100) se crean las siguientes variables: Objetivo: Toma e l valor de 1 s i cumple: “edad menor a 14 afios” 6 “Mujer embarazada entre 12 y 49 afios ”, y 0 en otro caso, a partir de la pregunta 115. Analfabetismo de Mujeres Adultas: Toma e l valor de 1 s i se trata de una persona de sex0 femenino, mayor de 18 aiios y que no sabe leer y escribir, s e g h la pregunta 108. Toma e l valor de 0 en otro caso. Asistencia de Menores: Con e l valor de 1 s i es el cas0 de una persona menor de edad que asiste actualmente a algun centro o programa de enseiianza regular, dad la pregunta 1 10, y e l valor de 0 en otro caso.

Se agrega la base de datos por hogar, teniendo en cuenta la suma de adultos, de menores de edad, de mujeres analfabetas y de menores que asisten a algun programa escolar. Posteriormente, se filtra esta nueva base por aquellos hogares que cumplan con e l Objetivo de contar con algun menor de 14 aiios o alguna mujer embarazada.

Se construyen 10s ratios de: 9 Mujeres adultas analfabetas como porcentaje del total de adultos en e l hogar, y 9 Menores que asisten a algun centro o programa educativo como porcentaje del total de menores

de edad en e l hogar. A continuaci6n, se imputan 10s ratios anteriores, en e l cas0 de encontrar vacios o valores perdidos, con e l promedio de 10s hogares del distrito en cuestibn.

D e la base de Caracteristicas de la Vivienda y del Hogar (Cuestionario 200), se obtienen las siguientes variables:

N o equipo: Indica la cantidad de equipamiento con 10s cuales no cuenta un hogar. Toma valores entre e l 1 y e l 7, que se identifican con 10s siguientes artefactos: televisor a blanco y negro, televisor a color, refiigeradora, plancha elkctrica, cocina a gas, vehiculo motorizado y vehiculo a pedal. Servicios: Toma valores entre 1 y 3, dependiendo de s i el hogar cuenta con e l servicio de alumbrado conectado a red elkctrica, agua de red publica y servicios higidnicos con saneamiento. Combustible: Toma e l valor de 1 s i el combustible que mLs utiliza en e l hogar para cocinar alimentos es de origen industrial, y 0 en otro caso.

P A S 0 6

Se juntan esta base de vivienda resultante con la de poblaci6n que habia sido agregada por hogares. Luego se filtran aquellos hogares que cumplan con e l Objetivo y que cuenten con “encuestas completas”. Posteriormente se procede a imputar las variables No Equipo, Servicios y Combustible con e l promedio de 10s valores por distrito, en e l cas0 que existan valores perdidos o vacios en la base resultante.

57

SE A ~ ~ ~ A D E N las variables de tipo de vivienda obtenidas a partir de 10s materiales predominantes en las paredes, techos y pisos (preguntas 203, 204 y 205, respectivamente). Despuis de realizar todas las 294 combinaciones posibles de dichos materiales, se escogieron 22 que engloban e l 9 1 , l percent, las cuales se agruparon en las siguientes variables:

Pared Adobe Adobe Estera

Piedra c/barro Adobe

Quincha Adobe

Quincha Madera Estera Adobe Adobe

Piedra dbarro Madera Adobe Madera Adobe

Variable I TiDo Techo Teja Paja Paja Paja Caiia Paja

Calamina Calamina

Paja Calamina

Caiia Teja

Calarnina Calamina Calamina

Paja Calamina

I 102

Grupo de Tipos de

Vivienda 2

126 294 21 0 114

Grupo de Tipos de

Vivienda 1

150 252 276 113 101

I 168 108

Grupo de Tipos de

Vivienda 3

Grupo de Tipos de

Vivienda 4

107 250 106 24 232 23 5

233

Ladrillo Calamina Ladrillo Concreto

Piso Tierra Tierra Tierra Tierra Tierra Tierra Tierra Tierra Tierra Tierra

Cemento Cemento

Tierra Tierra

Cemento Entablado Entablado

Tierra Entablado Cemento Cemento Cemento

De encontrarse valores perdidos o vacios en estos Grupos de Tipos de Vivienda, se procede a imputarlos con e l promedio del distrito.

P A S 0 8

A todas las variables anteriormente generadas (ver lista en Paso 1) se les multiplica por sus respectivos coeficientes encontrados en la regresidn del Paso 1 , para despu6s hallar su distribucidn logistica, expresada como campo Y en la base, lo cual indicaria la probabilidad que tiene un hogar de ser pobre.

A partir del resultado de la regresidn del Paso 1 se realiza una prediccidn de la probabilidad de pobreza de 10s hogares. Luego se 10s ordena en base a dicha probabilidad. Sabiendo que la pobreza en e l area rural es de 65.9 por ciento en e l pool de hogares 2001-2004, el umbral que se obtiene asociado a ese porcentaje es de 0.7567447. Aplicando e l umbral, se obtiene e l porcentaje de hogares pobres y no pobres dentro de cada distrito.

END

58

0 . 0

N 3 3 N

0 0

8 3 5 L &

0 .

8 g 5 & &

ANNEX 5: IMPROVED PROXY MEANS TEST MODEL: AN ILLUSTRATION

Model (1) (2) (3) (4) (5) (6) (7) (8) Dependent Variable lcpc lcpc lcpc lcpc i of pobreza xpoor xpoor xpoor Share of illiterate female -0.308 -0.156 -0.148 -0.151 0.779 0.559 0.394 0.418

ANNEX 5: IMPROVED PROXY MEANS TEST MODEL: AN ILLUSTRATION

Model (1) (2) (3) (4) (5) (6) (7) (8) Dependent Variable lcpc lcpc lcpc lcpc i of pobreza xpoor xpoor xpoor Share of illiterate female -0.308 -0.156 -0.148 -0,151 0.779 0.559 0.394 0.418

Share of children attending school

Access to industrial fuel for cooking

Number of missing appliances

Access to water, sewage

Housing conditions 2

Housing conditions 3

Housing conditions 4

Total number of HH members

% malnourished children < 5 years old

Area

departamento==5

departamento==6

departamento==7

departamento==8

departamento==g

departamento==lO

departamento==l 1

departamento==l2

departamento==l4

departamento==l5

departamento==l6

departamento==l7

departamento==l9

depaitamento==20

departamento==Zl

departamento==22

departamento==24

departamento==25

Constant

(24. IO)** -0.065

(4.62)". 0.218

( I 7.37)- -0.119

(33.71)'" 0.169

(36.70)-

(7.71)" 0.003

0.025 (2.29)'

-0.087

-0.23

(13.34)" -0.062

(4.96)" 0.222

(19.65)" -0.138

0.16 (38.67)""

(7.22)** 0.025

(1.96)* 0.049

(4.91)**

(68.89)'"

(43.49)-

-0.073

-0.117

(1 2.72)" -0.068

(5.44)" 0.152

(1 3.08)''

(41.09)** 0.135

(31.80)" -0.072

(7.10)" 0.019

-1.5 0.01

-1.02 -0.115

(67.50)"

(24.14)'"

-0.131

-0.95

(1 3.43)"

(7.19)" 0.165

-0.084

(1 2.10)" -0.15

(48.81)'* 0.145

(30.53)"

(6.12)" -0.063

-0.029 (2.18)'

(9.12)" -0.084

-0.094 (62.31)"

0.039 (3.11)"

0.082 (3.47)" -0.031

-1.81 0.183

(7.71)"

-0.301

-0.088 (4.14)"

0.07 (2.90)-

(2.99)" 0.095

(4.86)" 0.218

0.071

0.379

0.047 -1.34 0.028 -1.73 -0.29

(1 1.45)"

-0.056

(19.88)"

(3.44)"

(5.77)-

(15.97)" 0.032

0.322 (7.72)"

0.089 (2.95)"

5.597 6.157 6.366 6.123

-1.36

(14.01)"' 0.162

(3.02)'*

(1 1.66)"" 0.42

(29.46)"

(1 7.17)" 0.031 -0.64

-0.021 -0.35 0.065

-0.59

-0.322

-1.59

(10.01)** 0.285

(4.06)-

(21.07)*' 0.363

(17.21)"

(1 6.59)". -0.065 -1.34

-0.236 (3.32) **

-1.381

-0.383

-0.549 (7.39) **

(6.73)" 0.323

(4.46)"

(20.42)" 0.386

(17.84)" -0.39

( I 6.22)'" -0.08 -1.59

-0.289 (3.94)" -0.608

-1.391

(7.96)" 0.239

(27.29)"

(6.90)** 0.389

(5.21)**

(10.85)" 0.396

(17.60)"

(14.44)""

(2.36)'

-0.934

-0.397

-0.125

-0.447 (5.89)"

(7.83)" -0.613

0.258 (28.35)"

0.103 -1.48

-0.513 (4.24)"

-1.42 (4.69)" -0.159 -1.57 0.993

(8.41)'* 0.437

(4.39)" -2.161

(5.76)"

-1.04 (7.86)"

(7.40)" -0.622

-2.104 (2.9 1 )**

-0.637 (7.21)**

1.027 (1 1.92)"

-3.305 (3.86)"

-0.805 -1.961 -3.417 -3.715 (243.42)" (277.67)" (266.71)*' (265.00)" (8.70)" (15.28)*' (23.69)" (24.15)"

Observations 19590 19590 19248 19590 19590 19590 19590 19590 R-squared 0.36 0.49 0.5 0.56 0.19 0.25 0.29 0.32 Absolute value o f t statistics in parentheses * Significant at 5%; ** significant at 1%

61