Poverty-Growth Links

Applied Inclusive Growth Analytics

Kenneth Simler and Roy Katayama (PRMPR)

June 30, 2009

Outline1) Why look at poverty with growth?

2) Website: “Measuring growth-poverty links”

3) Five tools for measuring poverty-growth relationships

4) Summary

Why look at poverty? General consensus that:

Poverty reduction is meaningful goal of development Growth is necessary for sustainable poverty

reduction However, the extent to which growth translates

into poverty reduction varies across countries. Benefits of growth may not be reaching the poor Distributional changes can offset growth effects

BangladeshBolivia

Brazil

Burkina Faso

El Salvador

GhanaIndia

Indonesia

Romania

Senegal

TunisiaUganda

Vietnam

Zambia

-10

10

-3 6

Annual GDP per capita growth, 1990s (%) Source: Pro Poor Growth in the 1990s. Country Case studies

Ann

ual c

hang

e in

pov

erty

hea

dcou

nt (

%)

Growth and poverty reduction

Growth spells and poverty reduction

Source: Bourguignon (2002)

Poverty-growth-inequality triangle

Poverty reduction= f (growth, Δdistribution) What are effects of growth on distribution? What are effects of inequality on rate and

pattern of growth?

Source: Bourguignon (2004)

Poverty-growth-inequality triangle

Ex-post analysis of this relationship can: Inform ex-ante analysis of poverty and

distributional impacts of policies Help policymakers in evaluating policy options

Source: Bourguignon (2004)

Looking beyond averages Inclusive growth analysis requires:

Good understanding of growth at the mean, …but also the incidence of growth across the

distribution, ... and changes to the distribution and poverty.

Review of ESW indicated: Many could have been strengthened by utilizing

existing tools on growth-poverty links.

Overview of website and contents

WEBSITE: “MEASURING THE GROWTH-POVERTY LINK”

Useful growth-poverty tools Website: Measuring the Growth-Poverty Link

(http://go.worldbank.org/J70VTQSAK0)

Purpose: Make tools that explore growth-poverty links more accessible and results easier to understand

5 existing tools to explore growth, distribution, and poverty Growth elasticity of poverty Growth incidence curve Rate of pro-poor growth Growth-Inequality decomposition of poverty Sectoral decomposition of poverty

Overview of each tool on website Definitions and Concepts Limitations and Extensions Quick Results

Data requirements Stata/ ADePT options Helpful tips

Annotated examples Stata commands Interpretation of results

References / Related Papers

With examples from Uganda case

FIVE TOOLS

1. Growth elasticity of poverty Indicates how effectively growth has

translated into poverty reduction.

Misnomer: Should be GDP elasticity of poverty

Initial conditions matter: Location of poverty line (initial poverty levels) Shape of the distribution (initial inequality)

pcGDPinchange

povertyinchange

___%

___%

Uganda: Growth elasticity of poverty

  1993 2003 2006

Poverty headcount 0.56 0.39 0.31

Per capita GDP (constant LCU) 270,267 375,829 399,978

Gini 0.37 0.43 0.41

 

Percent change 1993-2003 2003-2006

in poverty headcount -31.2% -19.8%

in per capita GDP 39.1% 6.4%

Growth elasticity of poverty -0.8 -3.1

Percentage point change in poverty headcount -0.18 -0.08

Growth semi-elasticity of poverty -0.5 -1.2

2. Growth incidence curves Illustrates growth rate of income (expenditure)

for each percentile of a distribution. Gives equal weight to people…rather than to

dollars Refers to anonymous percentiles

Individual at 10th percentile at t0 is not necessarily same individual at 10th percentile at t1

Uganda: GICs

1992-2002 2002-2005

Growth rate in mean =4.09Mean percentile growth rate =3.26Headcount poverty (1992) =56.43Rate of pro-poor growth =2.90

Growth rate in mean =3.61Mean percentile growth rate =4.73Headcount poverty (2002) =38.82Rate of pro-poor growth =4.44

Growth incidence curves -- example

Distribution neutral

Increasing inequality

Decreasing inequality

Pov line (2005/06)

0

1

2

3

4

5

6

7

8

An

nual

gro

wth

ra

te p

er c

apita

0 20 31 40 60 80 100Income percentiles - Poorest to Richest

3. Rate of pro-poor growth Represents the mean growth rate of the poor

Not to be confused with growth rate in the mean of the poor

Related to GIC: Area under GIC up to poverty line (also equals the change in the Watts index)

General definition:

RateGrowthneutralonallydistributiifRP

actualRPRPPG _*

)__.(.

).(.

<

= + +

4.Growth-inequality decompositionQuantifies the relative contribution of economic growth and redistribution to changes in poverty.

Changein poverty

Growthcomponent

Redistributioncomponent

Residual

0tt PPn );,( 0 rttG n );,( 0 rttD n );,( 0 rttR n

0.2

.4.6

.8D

ensi

ty

-4 -2 0 2 4 6ln(per capita expenditure/poverty line)

19922002growth with 1992 distribution constant

redistribution with 1992 mean constant

kernel = epanechnikov, bandwidth = 0.0880

Uganda: Growth-inequality decomp.

a) Base year 1 Base year 2 g) Average effect

-----------------------------------------------------------------------------

b) Poverty rate (P0)

56.427  38.819  

-----------------------------------------------------------------------------

c) Change in P0

-17.608 -17.608  -17.608

-----------------------------------------------------------------------------

d) Growth component

-25.134 -26.211 -25.672

-----------------------------------------------------------------------------

e) Redistribution component

8.602 7.526 8.064

-----------------------------------------------------------------------------

f) Interaction component

-1.076 -1.076 0.000

-----------------------------------------------------------------------------------------------------------------------------------

1992 as reference (base year 1)

Uganda: 1992-2002

5. Sectoral decomposition of poverty Quantifies relative contributions to changes in

aggregate poverty of: changes in poverty within sectors and inter-sectoral population shifts

= + +

Typical sectors for decomposition:

Urban/rural Regions Economic sectors

Changein poverty

Intra-sectoralcomponent

Inter-sectoralcomponent

Interactioncomponent

k

ktktktkt PPssnn

))((00

kktktkt Pss

n))((

00 k

ktktkt PPsn

))((000tt PP

n

Urban-Rural Sectoral Decomposition (Uganda 1992—2002)

Pop share (1) Pop share (2) Poverty (1) Poverty (2)Rural 0.8758 0.8624 60.35 42.72Urban 0.1242 0.1376 28.77 14.35Total 1.0 1.0 56.43 38.82

Rural -15.4404 87.7%Urban -1.79096 10.2%TOTAL intra-sectoral -17.2313 97.8%population shift -0.42317 2.4%interaction 0.043014 -0.2%

Total change (Headcount) -17.6115 100.0%

Uganda: Rural / urban decomposition (1992 – 2002) a) Poverty in 1992 (headcount) 56.4

b) Poverty in 2002 (headcount) 38.8

SectorPop’n share (period 1)

Absolute change

Contribution (%)

c) Rural 87.6 -15.5 87.7

d) Urban 12.4 -1.8 10.2

e) Total intra-sectoral -17.2 97.8

f) Population shift effect -0.4 2.4

g) Interaction effect 0.04 -0.2

h) Change in poverty (HC) -17.6 100.0

Summary Website: Measuring the Growth-Poverty Link

(http://go.worldbank.org/J70VTQSAK0)

These tools provide an initial look beyond averages at the poverty and distributional impacts of growth.

However, integration with growth story is necessary to get a fuller economic picture.