Targeting Outcomes, Redux

Coady, Grosh, and Hoddinott(forthcoming in World Bank Research Observer)

Presentation at Reaching the Poor Conference

Washington, DC. February 2004

Full paper at www.worldbank.org/safetynets

What is targeting?

A system for concentrating benefits among the neediest. Targeting may mean that some are not served at all, or that all are served but with different benefit levels.

For the transfer programs reviewed in this study “needy” refers to income poverty. In other applications, need might defined differently.

Targeting Involves Two Tradeoffs

Benefits vs Costs

Errors of inclusion vs errors of exclusionWhen information is imperfect actions that reduce

one usually increase the other

• Administrative• Incentive• Political economy• Private (e.g. transactions costs)• Social (e.g. stigma)

• Higher efficiency

Questions for Review

What are the targeting outcomes observed in practice?

Are there systematic differences across targeting methods or program types?

What are implications for design and implementation of targeted interventions?

New database122 programs from 48 countries

Search CriteriaDeveloping/transition country Principal objective is poverty reduction

Includes cash and in-kind transfers, targeted price subsidies, public works jobs, social funds

Excludes contributory SI (pensions/UI), micro-credit, supplementary feeding targeted by nutritional status; fee waivering, emergency feeding

Documentation includes method and outcomeRelatively recent (1985-2003)

Search StrategyJournals (90-03), books, “grey literature”

Targeting Options Considered

Individual Assessment Means (3rd party verification; in-office, none) Proxy means Community-based

Categorical/Group Geographic Demographic (kids, elderly, other) Other

Self-Selection By purchase of commodity Work requirement Community Bidding

Evaluation of Targeting Performance

The classic meta-analysis problem: defns, methods and presentation differ substantially Most studies reviewed have one of following

Proportion of transfers to bottom deciles Proportion of beneficiaries in bottom deciles Proportion of transfers/beneficiaries who are “poor”

Solution: construct an indicator of the ratio of “actual” to “neutral” Proportion of transfers accruing to target relative

to population share of this group

Definition of Indicator% of benefits

% of population

60% of benefits to poorest 40 percent 1.5

40% of benefits to poorest quintile 2.0

25% of benefits to poorest decile 2.5

Some summary statisticsMean number of targeting methods per program is 2, range is 1 to 5Performance ranges from .28 to 4.00Median is 1.25 Excluding food subsidies, median is 1.30

One quarter of programs regressive Excluding food subsidies, 16% of programs regressive

Theil’s – between group variation low: By method – 20% of total By region – 28% By program type – 36%

Table 4: Targeting performance by targeting method Targeting method Sample size Median targeting

performance Interquartile range

Interquartile range as percentage of median

All methods 85 1.25 0.68 54.4 Any form of individual assessment 37 1.50 0.75 50.0 Means testing 26 1.55 0.90 58.1 Proxy means testing 7 1.50 0.58 38.7 Community assessment 6 1.40 0.78 55.7 Any categorical method 58 1.32 0.64 48.5 Geographic 33 1.33 0.51 36.9 Age – elderly 12 1.16 0.81 69.8 Age – young 26 1.53 0.65 42.5 Other categorical 17 1.35 0.48 35.6 Any selection method 38 1.10 0.41 37.2 Work 6 1.89 0.30 15.9 Consumption 25 1.00 0.35 35.0 Community bidding 7 1.10 0.22 20.0

Notes on descriptive statistics

Hierarchy of “aggregate” methods Individual>Categorical>Self-selection

Lot of variation within “aggregates” Work requirement has highest median, but universal

food subsidy the lowest Some methods have both low medians and low iqr,

hence limited potential – universal food subsidies and community bidding

Rest have high iqr, so good potential, but uncertain outcomes

Conclusion - details of design and implementation extremely important

Regression Analysis

Identifying interesting associations in the data

Dependant variable: log (performance)

Independent variables Country GDPpc 1995 PPP: capacity Gini coefficient: potential gains, identification Voice/Governance: Kaufman et al (1999) Targeting methods (choices) Robustness: performance (order, levels, median) Robust t-stats

Findings from regression analysis

Methods with good results: Means testing, geographic targeting, work

requirement

Methods with good potential, high variance: Proxy means testing, demographic targeting to

children, community-based

Methods with low potential: Demographic targeting to elderly, community bidding,

self-targeting food subsidies

BUT implementation and circumstances matter a LOT

Caveats

Diversity of raw performance measures

Ignoring distribution of “leakage’

Possible bias in the sample of programs

Static measure: entry-exit rules

Welfare impact depends on more than targeting (coverage, other objectives)

Focus on benefit side

4 messages“targeting can work” – mean is 1.25, top ten from 2-4, wide range of circumstances

But doesn’t always one quarter of programs regressive,

No clearly preferred method 80% of variation within method

A weak ranking developed: Means, geographic, work requirement Proxy means, community based, demo to kids Demographic targeting to elderly, community bidding, self-

selection of commodities