Targeting and Public Expenditure Margaret Grosh

Themes General Issues –Goals –Measurement –Stylized facts Applications to social safety nets –Comparison of instruments

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

Benefits of targeting 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 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 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

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?

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

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)

Conventional measures Errors of inclusion/exclusion –Simple –Discrete –Weighting issue

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

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

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

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

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

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

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

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

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

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

Table 4.2 Types of Subsidized Social Programs in Grosh's Sample TYPE OF GOVERNMENT SUBSIDIZED PROGRAM NUMBER OF PROGRAMS IN THE SAMPLE Delivery of food commodities or subsidies 8 Delivery of school lunches 3 Delivery of food stamps 5 Delivery of free or reduced- cost health services or health insurance 3 Delivery of student loans or fee waivers 3 Delivery of cash 3 Provision of jobs 2 Delivery of day care 2 Delivery of mortgages 1 Total30 Source:Grosh 1995.

PERCENT HIGHMID 75 LOW 100 GENERAL FOOD SUBSIDIES, N = 7 TARGETED PROGRAMS, N = 18 PRIMARY HEALTH CARE, N = 11 PRIMARY EDUCATION, N = 11 Share of Benefits Accruing to the Poorest 40 Percent, by Sector

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

GROUP CHARACTERISTICS (9) TARGET GROUP

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

PERCENT HIGHMID 75 LOW 100 INDIVIDUAL ASSESSMENT, N = 9 GEOGRAPHIC ASSESSMENT, N = 5 SELF- ASSESSMENT N = 4 Share of Benefits Accruing to Poorest 40 Percent, by Targeting Mechanism

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

GEOGRAPHIC ASSESSMENT, N = 5 SELF- ASSESSMENT N = PERCENT HIGHMID 30 LOW INDIVIDUAL ASSESSMENT, N = 9 Total Administrative Costs as a Share of Total Costs, by Targeting Mechanism

GEOGRAPHIC ASSESSMENT, N = 6 SELF- ASSESSMENT PERCENT HIGHMID 30 LOW INDIVIDUAL ASSESSMENT, N = 7 Targeting Costs as a Share of Total Costs, by Targeting Mechanism

Figure 9: Targeting Cost Share and Benefits Accruing to Poorest 40 Percent Share of Targeting Costs (%)

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

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

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

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

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

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