On Assessing Pro-Poorness of Governments Programs: International Comparisons

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1 On Assessing Pro-Poorness of Governments Programs: International Comparisons By N. Kakwani Director International Poverty Centre Brasilia Brazil

2 Different kinds of government programs Cash programs: Safety net in industrialized market economies Conditional cash transfers in Latin America In-kind programs: Food subsidies Food vouchers Public works Government services: Education : Schools Health : Hospitals Sanitation and clean water

3 What is pro-poor policy? A government policy can be said to be pro-poor if it benefits the poor more than the non-poor. It means that with a fixed cost to the government, a pro-poor policy should achieve greater poverty reduction compared to a counter-factual situation when everyone receives exactly the same benefit from the policy. Policy A will be more pro-poor than policy B if for a given cost, policy A leads to a greater poverty reduction than policy B..

4 Additive and decomposable class of poverty measures ( ) = z dx x f x z P 0 ) (, θ α = z x z P x) (z, = = = α α α H e a Headcount ratio Poverty gap Severity of poverty

5 Pro-Poor Policy (PPP) Index b(x): benefits received by an individual with income x = 0 ) ( ) ( dx x f x b b = mean benefit per person % change in total poverty due to a universal targeting of b η b where is the percentage change in poverty if everyone receives one unit of currency (i.e. absolute elasticity) η = z dx x f x P b d 0 * ) ( θ θ θ = z dx x f x b x P d 0 ) ( ) ( 1 θ θ θ : % change in total poverty due to b(x) =

6 Pro-poor Policy Index 1 P λ = b( x) f ( x) dx bηθ x Example: (i) λ = 1.20 : a programme reduces poverty 20% more compared to a counterfactual universal targeting (ii) λ = 0.70 : a programme reduces poverty 30% less compared to a universal targeting

7 Setting a Benchmark for PPP index Imperfect targeting: worst scenario b ( x) = 0 if x< z b ( x) 0 if x z Perfect targeting: best scenario b( x) = k( z x) if x< z b ( x) = 0 if x z * Note: for incentives, k should be always < 1

8 PPP index under perfect targeting Single poverty line - poverty gap ratio: 1/H s - severity of poverty: 2 g g=poverty gap ratio s=severity of poverty index. Needs adjusted poverty lines λ m = 1 ηθ z b 0 P x ( z x) f ( x) dx

9 The pro-poor policy index for the whole country is the weighted average of the total-group PPP indices for the individual groups, with weight proportional to shares of benefits received by each group. PPP index by socioeconomic groups Within group PPP index λ k = 1 P x Total group PPP index λ * k = z bkη kθ k 0 z 1 P ηθ x bk 0 b( x) f b( x) f k k ( x) dx ( x) dx

10 Welfare programs : Thailand 2000 Table 1: Pro-Poor Policy Index for welfare programs in Thailand: 2000 Welfare Schemes Poverty gap ratio Severity of poverty Social pension for the elderly Low-income medical cards Health insurance cards Free school lunches Perfect targeting Universal social pensions (for elderly over 65 years of age)

11 Welfare programs: Thailand 2000 Table 2: Pro-Poor Policy index by urban and rural areas: Thailand 2000 Total-Group PPP index Within-Group PPP index Welfare Schemes Urban Rural Urban Rural Poverty gap ratio Social pension for the elderly Low-income medical cards Health insurance cards Free school lunches Severity of poverty Social pension for the elderly Low-income medical cards Health insurance cards Free school lunches

12 Russian welfare system Table 3: The Russian welfare system: 2002 Beneficiaries Per month cost (Rubles) in million % share in billion % share Old-age pension Disability pension Loss of breadwinner pension Social pension Care for children under 18 m Children allowance Unemployment benefits Other benefits Scholarship All benefits Total Population

13 Old-age pension Disability pensio Loss of breadwi Social pension Care for childre Children allowa Unemployment b Other benefits Scholarship All benefits Perfect targeting PPP index for Russian welfare system The PPP index for Russian Welfare System Poverty gap Severity of poverty

14 Table 3: Pro-Poor Policy Index for health services in Vietnam: , poverty gap ratio Total-Group PPP index Within-Group PPP index Health facilities Vietnam Urban Rural Urban Rural Poverty gap ratio Government hospitals Commune health centres Regional polyclinics Eastern medicine facilities Pharmacies Private doctors Health insurance Perfect targeting 2.86

15 PPP index for education : Vietnam97-98 School Types Primary Lower Secondary Upper Secondary Poverty gap ratio Public Semi Public Sponsored Severity of poverty Public Semi Public Sponsored Universal Education Poverty gap ratio Severity of poverty Primary Lower Secondary Upper Secondary

16 Targeting children in Africa Figure 1: Pro-Poor Policy indices under universal transfers and perfect targeting (poverty gap ratio) Burkina Faso Cote d'ivoire Cameroon Ethiopia Ghana Guinea Gambia Kenya Madagascar Mozambique Malawi Nigeria Uganda Zambia Universal (rural children) Universal(all children) Perfect targeting Brundi

17 Brundi 98 Burkina Faso Cote d'voire 9 Camroon 96 Ethiopia 00 Ghana 98 Guinea 94 Gambia 98 Kenya 97 Madagascar 0 Mozambique Malawi 97 Nigeria 96 Uganda 99 Zambia Targeting Unemployed in Africa Male Female Brundi 98 Burkina Faso 9 Cote d'voire 98 Camroon 96 Ethiopia 00 Ghana 98 Guinea 94 Gambia 98 Kenya 97 Madagascar 01 Mozambique 96 Malawi 97 Nigeria 96 Uganda 99 Zambia Targeting unemployed in Africa Rural Urban

18 Zambia 98 Uganda 99 Cote d'ivoire 98 Cameroon 96 Ethiopia 00 Ghana 98 Guinea 94 Gambia 98 Kenya 97 Madagascar 01 Mozambique 96 Malawi 97 Nigeria Food subsidies in Africa Poverty gap Severity of poverty Burundi 98 Burkina Faso 98

19 Burundi 98 Burkina Faso Cote d'ivoire Cameroon 96 Ethiopia 00 Ghana 98 Guinea 94 Gambia 98 Kenya 97 Madagascar 0 Mozambique Malawi 97 Nigeria 96 Uganda 99 Zambia Food subsidies targeted at the poor PPP index for food subsidies targeted at the poor Poverty gap Severity of poverty

20 Children in Brazilsuffer more severe poverty than the rest of the population Table 1: Poverty in Brazil 2003 Percenatge Poverty Severity of poor Gap ratio of poverty The W hole Polulation Metropolitan Urban Rural Brazil Children 5-17 years old Metropolitan Urban Rural Brazil

21 The poor have greater access to Bolsa-Escola than the Non-poor. Figure2: Percentage of children receiving benefits by poverty status Poor Non-poor

22 Bolsa-Escola does not necessarily favor the girls in terms of access. Figure1: Percentage of children receiving benefits by sex Boys Girls

23 Bolsa-Escola has large exclusion error Exclusion error: probability of not receiving benefits when poor Inclusion error: probability of receiving benefits when non-poor 50 Figure 3: Exclusion and inclusion errors Exclusion Inclusion Total

24 Bolsa-Escola reduces the gap between poor and non-poor in school attendance Percentage of children attending school who are non-beneficiery Poor non-beneficiery Non-poor non-beneficiery Percentage of children attending school who receive benefits Poor beneficiery Non-poor beneficiery

25 Bolsa-Escola has greater impact on school attendance among the poor than the non-poor. Percentage of poor children attending school Poor beneficiery Poor non-beneficiery Percentage of non-poor attending school Non-poor beneficiery Non-poor non-beneficiery

26 Bolsa-Escola is generally pro-poor Table 2: PPP index for beneficiaries PPP index for beneficiaries Universal targeing 5-17 years Gap Severity Gap Severity Metropolitan Urban Rural Brazil Table 3: PPP index for applicants PPP index for beneficiaries Gap Severity Metropolitan Urban Rural Brazil

27 Bolsa-Escola is generally pro-poor Table 2: PPP index for beneficiaries PPP index for beneficiaries Universal targeing 5-17 years Gap Severity Gap Severity Metropolitan Urban Rural Brazil Table 3: PPP index for applicants PPP index for beneficiaries Gap Severity Metropolitan Urban Rural Brazil

28 Targeting efficiency is higher in rural areas Table 4: PPP and TE Indices (5-17 years). PPP index TE Index Gap Severity Gap Severity Actual beneficiaries Metropolitan Urban Rural Brazil Applicants Metropolitan Urban Rural Brazil

29 Santa Catar São Paulo Rio de Janei Rio Grande d Paraná Rondônia Distrito Fede Mato Grosso Goiás Espírito Sant Minas Gerais Mato Grosso Roraima Acre Amapá Pará Amazonas Tocantins Sergipe Rio Grande d Paraíba Pernambuco Ceará Bahia Piauí Maranhão Alagoas The poorer states generally have greater targeting efficiency Fig: Targeting Efficiency of Bolsa-Escola

30 Inequity in Brazilian education system is very high Table 5: Pro-poor index by levels of grades G rade P overty S everity of gap poverty P rim a ry - re g u la r P rim ary-regular public P rim ary-regular private S econdary - regular S econdary-regular public S econdary-regular private A dult prim ary A dult secondary Tertiary Tertiary public Tertiary private A dult literacy Child care P re-s c hool P re-vestibular (pre-tertiary) P ost-graduation

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