Growth elasticity of poverty
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Transcript Growth elasticity of poverty
Poverty-Growth Links
Applied Inclusive Growth Analytics
Kenneth Simler and Roy Katayama (PRMPR)
June 30, 2009
Outline
1) 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
Growth and poverty reduction
Annual change in poverty headcount (%)
10
Romania
Zambia
Indonesia
-3
Bolivia
Brazil
Ghana
Burkina Faso
Senegal
Bangladesh
India
Tunisia
Uganda
El Salvador
6
Vietnam
-10
Annual GDP per capita growth, 1990s (%)
Source: Pro Poor Growth in the 1990s. Country Case studies
Growth spells and poverty reduction
Source: Bourguignon (2002)
Poverty-growth-inequality triangle
Source: Bourguignon (2004)
Poverty reduction= f (growth, Δdistribution)
What are effects of growth on distribution?
What are effects of inequality on rate and
pattern of growth?
Poverty-growth-inequality triangle
Source: Bourguignon (2004)
Ex-post analysis of this relationship can:
Inform ex-ante analysis of poverty and
distributional impacts of policies
Help policymakers in evaluating policy options
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.
WEBSITE: “MEASURING THE
GROWTH-POVERTY LINK”
Overview of website and contents
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
Annotated examples
Data requirements
Stata/ ADePT options
Helpful tips
Stata commands
Interpretation of results
References / Related Papers
FIVE TOOLS
With examples from Uganda case
1. Growth elasticity of poverty
Indicates how effectively growth has
translated into poverty reduction.
% _ change _ in _ poverty
% _ change _ in _ pcGDP
Misnomer:
Should be GDP elasticity of poverty
Initial conditions matter:
Location of poverty line (initial poverty levels)
Shape of the distribution (initial inequality)
Uganda: Growth elasticity of poverty
1993
2003
2006
0.56
0.39
0.31
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
Poverty headcount
Per capita GDP (constant LCU)
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
Growth rate in mean
Mean percentile growth rate
Headcount poverty (1992)
Rate of pro-poor growth
2002-2005
=4.09
=3.26
=56.43
=2.90
Growth rate in mean
Mean percentile growth rate
Headcount poverty (2002)
Rate of pro-poor growth
=3.61
=4.73
=38.82
=4.44
Growth incidence curves -- example
Pov line (2005/06)
8
7
Decreasing inequality
6
5
4
Distribution neutral
3
2
Increasing inequality
1
0
0
20
31
40
60
80
Income percentiles - Poorest to Richest
100
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:
P.R.(actual)
RPPG
* Growth _ Rate
P.R.(if _ distributionally _ neutral )
<
4.Growth-inequality decomposition
Quantifies the relative contribution of economic growth and
redistribution to changes in poverty.
Pt n Pt 0
Change
in poverty
=
G (t0 , tn ; r )
Growth
component
+ D(t 0 , t n ; r )
Redistribution
component
+ R(t0 , tn ; r )
Residual
Uganda: Growth-inequality decomp.
Density
56.427
38.819
b) Poverty
rate (P0)
-----------------------------------------------------------------------------17.608
-17.608
-17.608
c) Change in
P0
-----------------------------------------------------------------------------25.134
-26.211
-25.672
d) Growth
component
----------------------------------------------------------------------------8.602
7.526
8.064
e)
Redistributio
n component
----------------------------------------------------------------------------f) Interaction
component
-1.076
-1.076
0.000
-----------------------------------------------------------------------------------------------------------------------------------
1992 as reference (base year 1)
.6
g) Average
effect
-----------------------------------------------------------------------------
.4
Base year 2
.2
Base year 1
0
a)
.8
Uganda: 1992-2002
-4
-2
0
2
ln(per capita expenditure/poverty line)
4
1992
2002
growth with 1992 distribution constant
redistribution with 1992 mean constant
kernel = epanechnikov, bandwidth = 0.0880
6
5. Sectoral decomposition of poverty
Quantifies relative contributions to changes in
aggregate poverty of:
changes in poverty within sectors and
inter-sectoral population shifts
Pt n Pt 0
Change
in poverty
= k (st k )( Pt k Pt k ) + (st k st k )( Pt k ) + (st k st k )( Pt k Pt k )
0
n
0
n
0
Intra-sectoral
component
n
0
k
k
Inter-sectoral
component
Interaction
component
Typical sectors for decomposition:
Urban/rural
Regions
Economic sectors
0
n
0
Urban-Rural Sectoral Decomposition
(Uganda 1992—2002)
Rural
Urban
Total
Pop share (1) Pop share (2)
0.8758
0.8624
0.1242
0.1376
1.0
1.0
Poverty (1)
60.35
28.77
56.43
Rural
Urban
TOTAL intra-sectoral
population shift
interaction
-15.4404
-1.79096
-17.2313
-0.42317
0.043014
87.7%
10.2%
97.8%
2.4%
-0.2%
Total change (Headcount)
-17.6115
100.0%
Poverty (2)
42.72
14.35
38.82
Uganda: Rural / urban decomposition (1992
– 2002)
a) Poverty in 1992 (headcount)
56.4
b) Poverty in 2002 (headcount)
38.8
Sector
Pop’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.