Targeting of Public Spending

Menno PradhanSenior Poverty Economist

The World Bank office, Jakarta

Central Question

Who benefits from public spending?

and

How to improve the targeting of public spending?

Benefit Incidence Analysis

0

10

20

30

40

50

60

70

1(poor) 2 3 4 5(rich)

Consumption Quintile

Perc

enta

ge W

ho B

enefi

ts

Data Source

Derived from household survey data

Did you use facility?

Did you receive benefit?

and,

Welfare measure, usually per capita consumption

Does this answer the question?

No, because:

• Benefit incidence ignores administrative cost- Total program cost = benefit + admin cost

• Benefit incidence is based on ex-post welfare indicator

– should based on welfare before program

• Benefits may not be homogeneously distributed

– for example, quality of school may vary across location

Solutions

• Need more detailed information on service delivery and expenditure tracking (public expenditure tracking surveys)

- to identify leakage/administrative cost - to identify heterogeneity in benefits

Solutions (cont.)

• Needs to consider what welfare level would have been without program

- Simplest case for cash transferConsumptionbefore = consumptionafter – cash

transfer

- Too simple households are likely to have behaved differently if they had not received the benefit

- Impact evaluation

Marginal benefit incidence

• Policy question is often too scale up or down an existing program

• Standard benefit incidence compares situation with or without program

• Marginal benefit incidence ≠ average benefit incidence

Marginal Benefit Incidence

Marginal Spending is Pro-Poor while average spending is pro-rich

0

10

20

30

40

50

60

70

1(poor) 2 3 4 5(rich)

Consumption Quintile

Perc

enta

ge W

ho B

enefi

ts

Year 1 Year 2

How to predict marginal benefit incidence?

Exploit differences in coverage across regions

jqj incidenceAverageIncidence 10

tincidenceAverageIncidence jtjqjt 1

j = regionq = quintile t = time

Conclusion Benefit Incidence Analysis

• Benefit incidence analysis is useful and cost effective to assess targeting of programs/policies

• Does often not provide complete picture

- ignores leakage / efficiency

- does not provide impact of program

• Tools and techniques are available to address those issues

Targeting of Government Expenditures

How to ensure that the poor benefit ?

Outline

1. Targeting of expenditures – introduction

2. Decentralization and Geographic targeting of programs

3. Potential gains of regional targeting

4. Poverty maps

5. Concluding remarks

Targeting of Public Expenditures

Ways to reach the poor. Target using :

• Household income (means testing)

• Other household indicators of welfare

• Self-targeting

• Commodities (rice, basic education and health care)

• Empowerment of the poor

Geographic Targeting

• Of relevance during Decentralization- Central government allocates budgets to local

government - Local governments make local spending allocations

• Geographic targeting: Poorer regions get a larger share of the pie

Why do geographic targeting ?

• Stark regional differences in poverty - Indonesia

Head count ratio %(source: Susenas 99)

Poorest province 61.1

Median province 23.8

Richest province 2.8

Geographic targeting, cont.

• Pros– Leads to better

targeting of the poor– Cheap and simple– Promotes local

ownership– Local administrators

better informed about local conditions

• Cons– Less control of center

over final outcome – local capture

– Political opposition to regional allocations based on statistical estimates

– May be less fair. • The probability for a

poor to receive a benefit depends on the region that person lives in

– Incentive to move to poor region

Geographic targeting, Example

• Example: JPS scholarship program

JPS scholarships by province

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40

percent poorsc

hola

rship

s / e

nro

llmen

t

Implementation unit Scholarships

Allocation Per district

Allocation Per school

Allocation Per sub-district

Allocation Per school

Student selection

CPCU Jakarta

District committee

Sub -district committee

School committee

Operational issues in regional targeting

• At what level to do the regional targeting?– The smaller the area, the better the targeting– And, the higher the statistical error

• How far to go in regional targeting?– Exclude rich districts? In proportion to nr of

poor?– More extreme first stage targeting may yield to

worse performance, depending on the second stage targeting

Does more precise targeting lead to better targeting to the Poor ?

Hypothetical exampleA country with• 27% poor. • Program has

potential to reach 27% of population

• Second stage allocation is done randomly

0 10 20 30 40 50 60

Village

Sub-District

District

Province

Randomallocation

Percent poor reached

First Stage Allocation

The smaller the area – the higher the statistical error

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

natio

nal

prov

ince

district

sub-dis

trict

villag

e

Pove

rty

/ con

fiden

ce in

terv

al

poverty

lower boundModule

upper boundModule

lower boundCore

upper boundCore

How far to go in regional targeting ?

• Example: 250 poor, 250 scholarships

0204060

80100120140160180

200

1 2 3 4 5

region

Poor Non-poor

Percent of poor reached (100 percent is perfect targeting)

Second stage

Random Perfect

First sta

ge

In proportion to population

31% 88%

In proportion to poor 47% 100%

Extreme 59% 75%

Poverty Maps

• Provide estimates of welfare for small geographical area.

• Could be along any dimensions of poverty

• To improve regional targeting

• To increase understanding of regional dimension of poverty (causes and consequences)

Poverty maps: Project, cont..

Basic Procedure:

– Estimate a model of (log) per capita consumption, yh, using sample survey data.

– Restrict explanatory variables to those that can be linked to households in survey and census.

– Simulate expected level of poverty or inequality using their census-based characteristics for each population of interest, and the estimates from the “first-stage” model of y.

– Model thus provides empirical weighting scheme.

Concluding Remarks - Targeting

• Regional targeting be closely linked to decentralization

• Regional targeting is a convenient planning tool to improve targeting of public expenditures programs, but no panacea.

• There is potential for improvement of first stage targeting of programs, but much more in the second stage. So, incentive mechanism for pro-poor spending at the local level is more important than the regional distribution component.

• Poverty maps can improve first stage targeting by restricting expenditures by small geographic area

Thank you