Targeting and Public Expenditure

1. Targeting and Public Expenditure Margaret Grosh

2. Themes • General Issues • Goals • Measurement • Stylized facts • Applications to social safety nets • Comparison of instruments

3. Targeting • Goal -- to concentrate benefits among the neediest • Implication • some people benefit and others do not AND/OR • needier get bigger benefit than less needy

4. Assumptions 15 million population 3 million poor $150 million budget No targeting everyone gets $10 80% of funds go to the non-poor Benefits of targeting

5. Assumptions 15 million population 3 million poor $150 million budget No targeting everyone gets $10 80% of funds go to the non-poor Targeting - Option I only poor receive $50 same budget Benefits of targeting

6. Assumptions 15 million population 3 million poor $150 million budget No targeting everyone gets $10 80% of funds go to the non-poor Targeting - Option I only poor receive $50 same budget Targeting Option II only poor receive $10 budget reduced to $30 million Benefits of targeting

7. Stepping back • What is the role of broad-based vs targeted programs in poverty reduction? • Where is the distributional instrument placed? • How private is the good? • Is goal (only) poverty reduction? • What is the concept of poverty – utility, income, capabilities?

8. Measurement (the usual morass of detail) • The counterfactual: pre-intervention welfare • Usual measurement problems • Recording and valuing consumption • Comparing across time and space • Equivalence scales • Behavioral change in response to provision • Labor supply • Consumption of goods/services • Private transfers

9. Measurement (the usual morass of detail) • The value of the benefit • Cost is not value (vaccines) • Costs hard to measure (data problem) • Values not same across hh (schools) • Quality differences (data problem)

10. Conventional measures • Errors of inclusion/exclusion • Simple • Discrete • Weighting issue

11. TARGETING ERRORS AND ACCURACY INCORRECTLY GIVEN BENEFITS ACTUAL STATUS POOR NON-POOR GOOD TARGETING Error of Inclusion Type II POOR CLASSIFIED AS CORRECTLY DENIED BENEFITS Error of Exclusion Type I NON -POOR INCORRECTLY DENIED BENEFITS

12. Conventional measures • Errors of inclusion/exclusion • Simple • Discrete • Weighting issue • Full distributional analysis of incidence and coverage / concentration coefficients and curves • Extended Ginis (Clert and Wodon, 2000) • Average vs marginal incidence

13. Stylized facts • Health, education as whole sectors usually mildly progressive • Progressive as % of welfare • Less so absolutely • Primary > secondary > tertiary • Demographics of measure • Pyramid effect • Self-selection into private market • Food price subsidies absolutely regressive, relatively progressive • Transfers > health, education

14. Share of Benefits Accruing to the Poorest 40 Percent, by Country and Sector

15. Applications to social safety nets What are reasonable expectations? What do we know about options?

16. Benefits lower costs greater impact Errors of exclusion (undercoverage) Costs administrative political economy incentive Errors of inclusion (leakage) Targeting is a tool, not goal(I.e. must balance tradeoffs)

17. Administrative costs • Targeting costs only a portion of total administrative costs • Usually more exact targeting imposes higher administrative costs • Just because costs exist doesn’t mean they aren’t worth paying

18. Incentive Effects • OECD literature worries about work disincentives from means tests, measures them • May be less important in some of our programs because: • not based on means test • eligibility • benefit level • incentive more to conceal income than reduce it • low level benefit, so incentives remain

19. Political Economy • Can affect: • support and budget for safety net • mix of programs • details of each • Reasons to support program • own present benefits • future benefits • benefits for others you care about • altruism, externalities • suppliers • Coalitions

20. Quantifying the Tradeoff • Study of 30 Latin American programs, late 1980s early 1990s (not contradicted to date) • Tried to measure • errors of inclusion • errors of exclusion • administrative costs • total • of targeting • qualitative information on requirements, options

21. Table 4.2 Types of Subsidized Social Programs in Grosh's Sample TYPE OF GOVERNMENT NUMBER OF PROGRAMS SUBSIDIZED PROGRAM IN THE SAMPLE Delivery of food commodities 8 or subsidies 3 Delivery of school lunches 5 Delivery of food stamps Delivery of free or reduced- 3 cost health services or health insurance 3 Delivery of student loans or fee waivers 3 Delivery of cash 2 Provision of jobs Delivery of day care 2 1 Delivery of mortgages Total 30 Source: Grosh 1995.

22. 100 75 PERCENT 50 25 0 GENERAL FOOD SUBSIDIES, N = 7 TARGETED PROGRAMS, N = 18 PRIMARY HEALTH CARE, N = 11 PRIMARY EDUCATION, N = 11 HIGH MID LOW Share of Benefits Accruing to the Poorest 40 Percent, by Sector

23. DO NOT MEET CRITERION MEETS CRITERION INDIVIDUAL ASSESSMENT (15) TARGETING

24. GROUP CHARACTERISTICS (9) TARGET GROUP

25. STIGMA LONG WAITING LINES USE OTHER PRODUCTS WORK REQUIREMENT SELF-TARGETING (6)

26. 100 75 PERCENT 50 25 0 INDIVIDUAL ASSESSMENT, N = 9 GEOGRAPHIC ASSESSMENT, N = 5 SELF- ASSESSMENT N = 4 HIGH MID LOW Share of Benefits Accruing to Poorest 40 Percent, by Targeting Mechanism

27. Errors of exclusion • Lacked data on participation rates • Unclear interpretation • self-targeting (good) • errors of exclusion (bad) • budget, outreach, communications, logistics, etc. appear more important than mis-identification due to screening

28. 30 25 20 15 PERCENT 10 5 0 INDIVIDUAL ASSESSMENT, N = 9 GEOGRAPHIC ASSESSMENT, N = 5 SELF- ASSESSMENT N = 4 HIGH MID LOW Total Administrative Costs as a Share of Total Costs, by Targeting Mechanism

29. 30 25 20 PERCENT 15 10 5 0 INDIVIDUAL ASSESSMENT, N = 7 GEOGRAPHIC ASSESSMENT, N = 6 SELF- ASSESSMENT HIGH MID LOW Targeting Costs as a Share of Total Costs, by Targeting Mechanism

30. Figure 9: Targeting Cost Share and Benefits Accruing to Poorest 40 Percent 100 80 60 40 20 0 2 3 4 1 Share of Targeting Costs (%)

31. Conclusions • progressivity of incidence • administrative costs not prohibitive • no a priori ranking by mechanism

32. Self-Targeting • Good or service available to all, but only the poor choose to use • Examples • hard physical labor for low wages • broken rice, coarse bread, etc. • waiting times • stigma • May be difficult to find vehicle suitable for large transfers • Costs to beneficiaries reduce net benefits

33. Categorical targeting • Age (child allowances, non-contributory pensions) • Disability, unemployment • Ethnicity (scheduled castes in India, Natives in Canada) • Easy to medium administratively • May not be very precise

34. Geographic • More accurate the smaller the unit used • But a limit based on data, service delivery system, politics • More viable for services used daily than yearly • New tool merging census and survey data may make more accurate

35. Proxy means test • Increasingly popular • A synthetic score calculated based on easily observed characteristics (household structure, location and quality of housing, ownership of durable goods) • At the complex end of requirements • Indicators tend to be static

36. Community-Based Targeting • Use existing local actor (teacher, nurse, clergyman) or new civic committee to decide who gets what • local actor may have best information, but • structure may impinge on actors’ performance in their original local roles, • may generate conflict • capture by local elites still possible • little empirical evidence to date