targeting and benefit incidence

Benefit incidence PEP and UNDP June 2010 – 1 / 16

Benefit incidence

Abdelkrim Araar, Sami Bibi and Jean-Yves Duclos

Workshop on poverty and social impact analysisDakar, Senegal, 8-12 June 2010

Outline

Outline

Objectives

The context

Main statistics ofinterest

Benefit incidence inDASP

Conclusion


The context

Main statistics of interest


Conclusion

Objectives


� Understand the usefulness of doing benefit incidence analysis;� Assess what type of information is needed for benefit incidence analysis;� Define various statistics used in benefit incidence analysis;� Illustrate how these statistics are generated byDASP.

The context

Outline

Objectives

The context

Main objective

Basic notation



Conclusion


Main objective


� The main objective of making benefit incidence analysis is toset thedistribution of benefits derived from public expenditures against thedistribution of living standards (see for instanceLanjouw and Ravallion (1999) and Demery (2000)).

� Two main sources of information are normally used:

1. The first is access to and use of public services. This information canbe found in many household surveys.

2. The second deals with the level of total public expenditures ondifferent types of services. This information is usually available atthe national level and sometimes at a more disaggregated level, suchas at regional and local levels.

Basic notation


Formally, let

� νi : be the sampling weight of observationi;� yi: be the living standard of those individuals belonging to observationi

(e.g., per capita income);� em

i: be the number of “eligible” members of observationi, i.e., those

members of observationi that “need” the public service provided bysectorm. There areM sectors;

� um

i: be the number of members of observationi that effectively receive

the public service provided by sectorm;

Basic notation


Formally, let

� li: be a subgroup indicator for observationi (e.g., 1 for a rural resident,and 2 for an urban resident). Usually, we use the socio-economic groupof the eligible members of observationi is used (defined by incomepercentiles, for instance). Eligible members can thus be grouped intopopulation-exclusive subgroups;

� Em

a: be total public expenditures on sectorm in areaa. There areA

areas. An area refers here to a geographical division for which one canhave reliable information on the level of total public expenditures for agiven public service;

� Em: be total public expenditures on sectorm: Em =A∑

a=1

Em

a.

Main statistics of interest

Outline

Objectives

The context


Various incidencestatistics


Conclusion


Various incidence statistics


� The share of groupl in sectorm is given by:

SHm

l=

n∑i=1

νium

iΥ(i ∈ l)

n∑i=1

νium

i

Note that:L∑l=1

SHm

l= 1.

� The rate of participation of a groupl in sectorm is defined as follows:

CRm

l=

n∑i=1

νium

iΥ(i ∈ l)

n∑i=1

νiem

iΥ(i ∈ l)



� The unit cost for observationi of a benefit in sectorm — referring toindividuals living in areaa :

UCr

i=

Em

a

na∑i=1

νium

i

wherena is the number of households in areaa.� The benefit of observationi from the use of the benefit in sectorm is:

Bm

i= um

iUCm

i



� The benefit of observationi from the use of theM public sectors is:

Bi =M∑

r=1

Bm

i

� The average benefit among those eligible to a service from sector m andfor those observations that belong to a groupl is defined as:

ABEm

l=

n∑i=1

νiBm

iΥ(i ∈ l)

n∑i=1

νiem

iΥ(i ∈ l)



� The average benefit for those that use the servicem and belong to a groupl is defined as:

ABFm

l=

n∑i=1

νiBm

iΥ(i ∈ l)

n∑i=1

νium

iΥ(i ∈ l)

� The proportion of benefits from the service from sectorm that accrue toobservations that belong to a groupl is defined as:

PBm

l=

Bm

l

Em

whereBm

l=

n∑i=1

νiBm

iΥ(i ∈ l). These statistics can be restricted to

specific socio-demographic groups (e.g., rural/urban).


Outline

Objectives

The context



BIA and DASP

BIA of spending oneducation in Peru

Conclusion


BIA and DASP


Thebian.adomodule allows the computation of these different statistics.

� Possibility of selecting between one and six sectors.� Possibility of using frequency data approach when information about the

level of total public expenditures is not available.� Generation of benefit variables by the type of public services (ex:

primary, secondary and tertiary education levels) and by sector.� Generation of unit cost variables for each sector.� Possibility of computing statistics according to groups ofobservations.� Generation of statistics according to social-demographicgroups, such as

quartiles, quintiles or deciles.

BIA and DASP


� Public expenditures on a given service often vary from one geographicalor administrative area to another. When information about publicexpenditures is available for “local” areas, it can be used by thebianmodule to estimate unit cost more accurately.i hh size Eligible Frequency Area Total level

hh members indicator regional publicexpenditures

1 7 3 2 1 140002 4 2 2 1 140003 5 5 3 1 140004 6 3 2 2 120005 4 2 1 2 12000The unit cost in area 1 equals: 14000/7=2000The unit cost in area 2 equals: 12000/3=4000

BIA and DASP


� By default, the area indicator is set to 1 for all households.When thisdefault is used, the variable “Regional public expenditures” (the fifthcolumn that appears in the dialog box) should be set to total publicexpenditures at the national level. This would occur when the informationon public expenditures is only available at the national level.

i hh size Eligible Frequency Area Total levelhh members indicator regional public

expenditures1 7 3 2 1 260002 4 2 2 1 260003 5 5 3 1 260004 6 3 2 1 260005 4 2 1 1 26000The unit cost at national level equals to: 26000/10=2600

BIA of spending on education in Peru


� Using the peredu94I.dta file, estimate participation and coverage rates oftwo types of public spending on education when:

� The standard of living is exppc;� The number of household members that benefit from education is

fr_prim for the primary sector and fr_sec for the secondary one.� The number of eligible household members is el_prim for the

primary sector and el_sec for the secondary one.� Social groups are quintiles.



� Typedb bian in the windows command and set variables and options as follows:


Benefit incidence PEP and UNDP June 2010 – 11 / 16� To estimate total public expenditures on education by sector at the



Using this information, the following variables are generated:

� Total public expenditures on primary sector : pri_pub_exp� Total public expenditures on secondary sector : sec_pub_exp� Total public expenditures on university sector : uni_pub_exp� Estimate the average benefits per quintile and generate the benefit

variables.

Conclusion

Outline

Objectives

The context



Conclusion

Summary

RelevantDASPcommands

Exercises with StataandDASP

References


Summary


� Benefit incidence analysis is useful to contrast the distribution of benefitsderived from public expenditures against the distributionof livingstandards in a society.

� Benefit incidence analysis can help assess whether the distribution ofpublic expenditures helps offset disparities in living standards.

� Benefit incidence analysis normally requires information on access toand/or use of public services as well as information on the level of totalpublic expenditures expended on different types of services.

� Thebian.adomodule inDASP allows the computation of variousstatistics, such as benefit indicators by type of public services and bysector, unit cost variables for each sector, decompositionof such statisticsaccording to groups of observations, and computation of thestatisticsaccording to social-demographic groups and according to quartiles,quintiles or deciles.

RelevantDASP commands


� DASP and Benefit Incidence Analysis (bian).

http://132.203.59.36/DASP/help/DASP_MANUAL_V2.1.htm#_Toc247593997

Exercises with Stata andDASP


� 23.14 BIA of public spending on education in Peru (1994).

http://132.203.59.36/DASP/help/DASP_MANUAL_V2.1.htm#_Toc247594025

References


DEMERY, L. (2000): “Benefit incidence: a practitioner’s guide,” Tech.report, Poverty and Social Development Group. Africa Region, The WorldBank.

LANJOUW, P. AND M. RAVALLION (1999): “Benefit Incidence, PublicSpending Reforms, and the Timing of Program Capture,”World BankEconomic Review, 13, 257–73.

targeting and benefit incidence

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