Download Module 2 Poverty Dynamics

1. Measuring
poverty
2. Multidimensional
poverty
3. Poverty Dynamics
4. Panel Data
5. Inference with
Panel Data
Module 6
International
Poverty Comparisons
6. International
Poverty
Comparisons
7. Vulnerability
8. Tackling Poverty
JONATHAN HAUGHTON
j h a u g h t o n @ S u ffo l k . e d u
JUNE 2017
Objectives
1.
Explain how the World Bank computes world poverty rates, and
a.
b.
c.
d.
the role played by the initial choice of poverty line
the need to use purchasing power parity (PPP) exchange rates
the use of domestic CPIs to adjust local-currency poverty lines to the survey year
how the poverty rate and level is measured using a Lorenz curve and poverty line.
2.
Identify where poverty has fallen most quickly since 1981
3.
Evaluate the World Bank approach to measuring world poverty
4.
Explain why Dollar and Kraay conclude that growth is good for the poor, and why Ravallion argues
that inequality is bad for the poor
5.
Define “pro-poor” growth
6.
Explain how to decompose changes in poverty into growth and inequality effects
7.
Identify the ways in which macroeconomic shocks may affect poverty
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Why compare poverty internationally?
To target scarce resources
To judge progress toward key Millennium Development Goal: halve proportion living on < $1/day
between 1990 and 2015.
◦ Now Sustainable Development Goal of zero poverty by 2030!
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WB/Chen & Ravallion
1.
Pick poverty line
◦ Based on basic needs lines in poorest countries
◦ USD1.25/person/day in 2005 prices
2.
Use PPP exchange rate: get poverty line in local currency for some specified year
3.
Use CPI to create poverty line in nominal local currency, annually since 1981
4.
Measure poverty rate from survey data; if necessary estimate using Lorenz curves
5.
Interpolate poverty rates for intervening years
6.
Aggregate to get world poverty rate
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PovcalNet
2010 version uses data > 850 surveys in 127 LDCs; regularly updated.
◦ http://iresearch.worldbank.org/PovcalNet/index.htm
Headcount rate has dropped
◦ 52% in 1981, 21% in 2010 (84% to 12% in China)
◦ Change coming most slowly in Africa
See table; bubble graph
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Sample graph
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Poverty since 1981 by region
Headcount poverty rate (%) US$1.25
80
2013
60
40
20
LAC
0
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10.0
GDP/capita, 2005 PPP constant dollars, log scale
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Issues
What poverty line?
◦ $1.25 standard based on official poverty line in 15 poorest countries. Too arbitrary?
PPP exchange rate conversion
◦ Tries to reflect true prices; but not very accurate, and not based just on goods consumed by poor
Internal CPI adjustment
◦ Should reflect “basket” consumed by poor
Alternative: Cost-of-basic-needs in each country? (Pogge & Reddy 2003)
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Implications: Growth is good for the poor
Dollar and Kraay 2002
◦ 137 countries, 1950-1999
◦ 418 episodes (5-year intervals; measure income of poorest quintile)
◦ Ln(poor) = 1.07 ln(inc/cap) – 1.77 R2 = 0.88
◦ i.e. poor keep up with GDP growth in long-run
◦ Δln(poor) = 1.19 Δln(inc/cap) – 0.007 R2 = 0.49
◦ i.e. short-term link is weaker; policy can matter
◦ Robust results. Institutional variables don’t help.
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“Growth is good” illustrated
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Pro-poor growth?
Kraay (2004)
◦ Medium run: poverty tracks economic growth
◦ Hard to identify what else helps
Two definitions: Growth is pro-poor if:
– [Absolute] incomes of the poor are rising
Chile, India, Bangladesh, Brazil
– [Relative] incomes of poor are growing
faster than the population as a whole
Ghana, Zambia
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Datt and Ravallion (1991) decomposition
P*: Poverty in t=1 if no change in distribution
P**: Poverty in t=0 if distribution of t=1 held, same mean
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Decomposition: comments
Even if growth dominates in medium-term, distribution matters in short-term
Ravallion: Inequality is bad for the poor
◦ Poverty responds more slowly to growth in high-inequality countries
◦ He finds: no link between economic growth & inequality
Holy Grail of Poverty Analysis: Are there policies that can help the poor
directly? If so, what?
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Growth is good, inequality is bad for the poor
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Case: Recession and Poverty in Thailand
Links between external shocks and poverty are weak, unclear, country- and time-specific
Thailand: exports fell 19%, tourists 14%, GDP 2.3% due to “great recession”
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9.2
ln(real expenditure/capita), baht/month
Expenditure
maintained
9.4
Shock was sharp but short
◦ Recession kept some prices
in check
◦ Consumption smoothing
◦ Active government response
9
8.8
8.6
8.4
8.2
8
7.8
7.6
7.4
2007m1
2007m7
Bangkok
2008m1
Center
2008m7
South
2009m1
2009m7
North
2010m1
Northeast
Figure 6.1. Log of real per capita expenditure by region, Thailand, 2007:M1 – 2010:M6,
deseasonalized
Source: Thailand Socio-Economic Surveys of 2007, 2008, 2009, and 2010. Shaded area marks period of recession.
10
Losers: Young wage workers
in Bangkok
ln(real expenditure/capita), baht/month
9.5
9
8.5
8
7.5
7
6.5
2007m1
2007m7
2008m1
Top decile
2008m7
Decile 5
2009m1
2009m7
2010m1
Bottom decile
Figure 6.2. Log of real per capita expenditure by selected expenditure per capita deciles,
Thailand, 2007:M1 – 2010:M6, deseasonalized
Source: Thailand Socio-Economic Surveys of 2007, 2008, 2009, and 2010. Shaded area marks period of recession.
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Thai recession: Only Bangkok hurt
Table 3. Measuring the Impact of the 2008-09 Recession on Log Real Expenditure per capita by
region and household size
Real
expenditure
per capita
All Thailand
4,068
Change in log of real expenditure per capita
compared to 2007
2008
2009
2010
baht/quarter
-0.073
0.034
-0.044
0.00
0.00
0.087
0.046
Memo: nominal exp/cap
4,248
-0.027
0.00
0.00
0.00
Region 1: Bangkok
7,973
0.304
0.135
0.259
0.00
0.00
0.00
Region 2: Center
4,686
-0.060
0.01
Region 3: North
3,226
-0.131
0.00
Region 4: Northeast
2,926
-0.107
6,037
-0.030
0.00
-0.125
0.00
Memo: % very poor
0.019
-0.097
-0.017
0.06
21.1
0.40
0.036
0.00
0.025
0.00
0.010
0.00
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176,141
10,520
51,442
43,389
0.00
-0.067
0.049
Urban
1,321
0.00
176,141
0.00
0.026
0.012
Very poor (deciles 1-2)
0.009
-0.031
0.00
4,164
3,184
0.00
0.00
Region 5: South
Rural
0.050
0.00
0.49
June 2017
0.00
Number of
households
45,521
25,269
0.19
-0.006
108,690
0.00
-0.088
67,451
0.00
-0.020
20,546
0.00
17.6
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Readings
Haughton & Khandker, chapter 10
Chen and Ravallion (2008)
•
◦ Chen, Shaohua, and Martin Ravallion. 2008. The Developing World Is Poorer Than We Thought, But No
Less Successful in the Fight against Poverty. Policy Research Working Paper No. 4703, World Bank,
Washington, DC.
PovcalNet: http://iresearch.worldbank.org/PovcalNet/index.htm
Haughton (2012): Bubble Rap
◦ Jonathan Haughton. 2012. Bubble Rap: Visualizing Poverty Dynamics, Case Studies in Business,
Industrial, and Government Statistics. Data file at
http://web.cas.suffolk.edu/faculty/jhaughton/BubblesGDPp125r2017.xlsm
Dollar and Kraay (2002)
◦ David Dollar & Aart Kraay. Growth is Good for the Poor, Journal of Economic Growth, 7(3): 195-225.
Haughton & Khandker (2012) on Thailand
◦ Jonathan Haughton and Shahidur Khandker. 2013. “The Surprising Effects of the Great Recession: Losers and
Winners in Thailand in 2009-2009”, under consideration by World Development.
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