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Poverty measurement
Michael Lokshin,
DECRG-PO
The World Bank
Properties and Robustness
Questions for the analyst: How do we measure “welfare”?
Individual measures of well-being When do we say someone is "poor"?
Poverty lines. How do we aggregate data on welfare into a
measure of “poverty”? How robust are the answers?
Three components of poverty analysis
Welfare
Indicators
Poverty
Lines
Poverty
Analysis
Adding up poverty: Headcount
q = no. people deemed poor
n = population size Advantage: easily understood Disadvantages: insensitive to distribution below the
poverty line e.g., if poor person becomes poorer, nothing happens to H.
Example: A: (1, 2, 3, 4) B: (2, 2, 2, 4) C: (1,1,1,4)
Let z = 3. HA = 0.75 = HB=HC;
qH
N
Adding up poverty: Headcount
Adding up poverty: Poverty Gap
1
1 1
1
,..., ,...,
qi
i
q q n
z yPG
n z
y y z y y
Advantages of PG: reflects depth of poverty
Disadvantages: insensitive to severity of poverty
Example: A: (1, 2, 3, 4) B: (2, 2, 2, 4)Let z = 3. HA = 0.75 = HB; PGA = 0.25 = PGB.
Adding up poverty: Poverty Gap
Adding up poverty: Poverty Gap
The minimum cost of eliminating poverty: (Z-z)*q -- Perfect targeting.
The maximum cost of eliminating poverty: Z*q -- No targeting.
Ratio of minimum cost of eliminating poverty to the maximum cost with no targeting:
Poverty gap -- potential saving to the poverty alleviation budget from targeting.
q
i
iz PGZ
yZ
nqZ
qZ
1
)(1
*
*)(
Adding up poverty:Squared Poverty Gap Week Transfer Principal: A transfer of income from any
person below the poverty line to anyone less poor, while keeping the set of poor unchanged, must raise poverty
Advantage of SPG: sensitive to differences in
both depth and severity of poverty.
Hits the point of poverty line smoothly. Disadvantage: difficult to interpret Example: A = (1, 2, 3, 4) B = (2, 2, 2, 4)
z = 3 SPGA = 0.14; SPGB = 0.08
HA=HB, PGA=PGB but SPGA>SPGB
q
i
i
z
yz
nSPG
1
21
Adding up poverty: FGT-measures
1
0
1
2
1( 0)
0 : (Headcount)
1: (Poverty Gap/Depth)
2 : (Squared Poverty Gap/Severity)
qi
i
z yP
n z
P H
P PG
P SPG
Additivity: the aggregate poverty is equal to population- weighted sum of poverty level in the various sub-groups of society.
Range:
poorestthetoWeight
Pzy
HPy
i
i
0
0
Rawls welfare function: maximize the welfare of society's worse-off member.
Adding up poverty: FGT-measures
1
0 1 22
1
10; ; 2
i
i
i
i i i
P z y
y z z
P P P z y
y y z y z
Derivatives
Adding up povertyAdding up poverty: Recommendations
Does it matter in poverty comparisons what measure to use?
Depends on whether the relative inequalities have changed across the situations being compared.
If no changes in inequality, no change in ranking.
Recommendations: Always be wary of using only H or PG; check SPG. A policy conclusion that is only valid for H may be
quite unacceptable.
Adding up poverty: Example 1
Example: Effect of the change in price of domestically produced goods on welfare.
Price of rice in Indonesia: Many poor households are net rice producers, the
poorest households are landless laborers and net consumers of rise.
Policy A Decrease in price of rice: small loss to person at poverty line, but poorest gains;
Policy B Increase in price: poorest loses, but small gain to person at poverty line.
So HA > HB yet SPGA < SPGB Which policy would you choose?
Adding up povertyAdding up poverty: Example 2
Poverty line = (6) Initial distribution: (1,2,3,4,5,6,7,8,9,10); HC: = 0.50 Poverty gap: (5/6,4/6,3/6,2/6,1/6,0) = 0.25 SPG: (25/36,…,0) = 0.16 Poverty Alleviation Budget $6 Case 1: (6,3,3,4,5,6,7,8,9,10); HC = 0.40 PG: (0,3/6,3/6,2/6,1/6,0..0) = 0.15 SPG: (0,9/36,9/36,4/36,1/36,0..0) = 0.07 Case 2: (1,2,6,6,6,6,7,8,9,10); HC = 0.20 PG: (5/6,4/6,0,…,0) = 0.15 SPG: (25/36,16/36,0,…,0) = 0.11
Social Welfare functionSocial Welfare function
Utilitarian Social Welfare Function. Social states are ranked according to linear sum of individual utilities:
We can assign weight to each individual’s utility:
Inclusive and Exclusive Social Welfare Functions
1
( )n
ii
W u x
1
( )n
i ii
W a u x
Robustness of poverty comparisonsRobustness of poverty comparisons
Why should we worry? Errors in living standard data Uncertainty and arbitrariness of the poverty line Uncertainty about how precise is the poverty measure Unknown differences in need for the households with
similar consumption level. Different poverty lines that are completely reasonable and
defensible.
How robust are our poverty comparisons? Would the poverty comparison results change if we
make alternative assumptions?
RobustnessRobustness: Poverty incidence curve
1. The poverty incidence curve Each point represents a headcont for each possible
poverty line Each point gives the % of the population deemed
poor if the point on the horizontal axis is the poverty line.
RobustnessRobustness: Poverty depth curve The poverty depth curve = area under poverty incidence curve Each point on this curve gives aggregate poverty gap – the poverty
gap index times the poverty line z.
RobustnessRobustness: Poverty severity curve
The poverty severity curve = area under poverty depth curve Each point gives the squared poverty gap.
RobustnessRobustness: Formulas
Poverty incidence curve:
Poverty deficit curve:
Poverty severity curve:
z
dxxfyF0
)()(
zz
dxxFdxxfxzzD00
)()()()(
zz
dxxDdxxFxzzS00
)()()()(
Robustness:Robustness: First Order Dominance Test
If the poverty incidence curve for the A distribution is above that for B for all poverty lines up to zmax then there is more poverty in A than B for all poverty measures and all poverty lines up to zmax
Robustness:Robustness: First Order Dominance Test
What if the poverty incidence curves intersect? -- Ambiguous poverty ranking.
You can either:i) restrict range of poverty lines ii) restrict class of poverty measures
Robustness:Robustness: Second Order Dominance Test
If the poverty deficit curve for A is above that for B up to zmax then there is more poverty in A for all poverty measures which are strictly decreasing and weakly convex in consumptions of the poor (e.g. PG and SPG; not H).
e.g., Higher rice prices in Indonesia: very poor lose, those near the poverty line gain.
What if poverty deficit curves intersect?
Robustness:Robustness: Third Order Dominance Test
If the poverty severity curve for A is above that for distribution B then there is more poverty in A, if one restricts attention to distribution sensitive (strictly convex) measures such as SPG.
Formal test for the First Order Dominance –
Kolmogorov-Smirnov test
Robustness:Robustness: Examples
Initial state (1,2,3) (2,2,3) (1,2,4) – unambiguously lower poverty (2,2,2) poverty incidence curves cross. compare z=1.9 and z=2.1 poverty deficit curves do not cross Thus poverty has fallen for all distribution sensitive measures.
Example 2:Initial State A: (1,2,3) Final State B: (1.5,1.5,2)
C. F(z) D(z) S(z) A B A B A B 1 1/3 0 1/3 0 1/3 0 1.5 1/3 2/3 2/3 2/3 1 2/3 2 2/3 1 4/3 5/3 7/3 7/3 3 1 1 7/3 8/3 14/3 15/3
Robustness:Robustness: Recommendations
First construct the poverty incidence curves up to highest admissible poverty line for each distribution.
If they do not intersect, then your comparison is
unambiguous.
If they cross each other then do poverty deficit curves and restrict range of measures accordingly.
If they intersect, then do poverty severity curves. If they intersect then claims about which has more
poverty are contentious
Robustness:Robustness: Egypt, poverty changes between 1996 and 2000
The percentage of the poor for All Egypt.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Poverty Line Z as %of mean
P0
1995/96
1999/2000
The Poverty Gap Index for all Egypt.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Poverty Line Z as % of mean
P1
1995/96
1999/2000
Severity of Poverty Index for All Egypt.
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
Poverty Line Z as % of mean
P2
1995/96
1999/2000
Poverty profiles: Additivity
How poverty varies across sub-groups of society. Useful to access how the sectoral or regional patterns of economic change are likely to affect aggregate poverty.
Additive poverty measures: (e.g., FGT class). Suppose population is divided into m mutually exclusive sub-groups. The poverty profile is the list of poverty measures Pj for j=1,…,m.
Aggregate poverty for additive poverty measures:
Aggregate poverty is a population weighted mean of the sub-group
poverty measures.
jn
ijijjj
m
jjj nyzpPandnnPP
11
/),(/
Poverty profiles: Example
Urban population (2,2,3,4) Rural population (1,1,1.5,2,4)
Zu=3,Zr=2,n=9,nu=4,nr=5,
Direct way: n=9; q=7; H=q/n=0.78
4
01 1
5
01
2
1
( , ) / (3, ) / 0.75
(2, ) / 0.80
/ (0.75*4 0.80*5) / 9 0.78
un
u j iu j iu ui i
r ir ri
j jj
P p z y n p y n
P p y n
P P n n
Poverty profiles: Two types
Two main ways to present poverty profiles: Type A: Incidence of poverty for sub-groups defined by
some characteristics (e.g., place of residence) Type B: Incidence of characteristics defined by the poverty
status.Region Number of persons Poverty profile Poor Non-poor Type A:
% of regional population who are poor
Type B: % of total population who are poor
South 100 100 50 33 North 200 600 25 66
Poverty profiles:
Select the target region for poverty alleviation. Geographic targeting. If one chooses South
more money will go to poor. So Type A is preferable. Minimizes the poverty gap.
General rule: When making the lamp-sum transfers with the aim to minimize the aggregate value of FGT type of poverty Pa the next unit of money should go to the sub-group with the highest value of Pa-1.
Poverty profiles: Egypt regions
5
3010
20
8
10
21
1554
20
2 5
% of poor % of population
Border
Upper EgyptRural
Upper EgyptUrban
Lower EgyptRural
Lower EgyptUrban
Metropolitan
Poverty profiles: Egypt (Type A)
Poverty measurements by gender of individual
29.1054 7.5857 2.8383
63411 63411 63411
27.1285 7.0133 2.6250
61876 61876 61876
28.1290 7.3030 2.7330
125287 125287 125287
52.4891 13.2851 4.6560
51304 51304 51304
49.9152 12.4107 4.2883
49526 49526 49526
51.2248 12.8556 4.4754
100830 100830 100830
39.5633 10.1346 3.6512
114715 114715 114715
37.2588 9.4128 3.3645
111402 111402 111402
38.4279 9.7790 3.5100
226117 226117 226117
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N
Mean
N
Sex of PersonMale
Female
Total
Male
Female
Total
Male
Female
Total
AREAURBAN
RURAL
Total
PO P1 P2
Poverty profiles: Multivariate
Univariate: Simple cross-tabulation of poverty measures against specific variables
Multivariate: Poverty measure is modeled as a function of multiple variables: or “poverty regression”
Model household expenditure or income first and then predict poverty measures based on this regression. Do not run probit on poverty measure when expenditure data is available.
Steps: Estimate regression: Log(Ci)=+Xi+I Predict consumption: E(Ci)=Exp(Xi+2/2) Calculate poverty rates based on predicted consumption, or Calculate probability of being poor, then the national
headcount index will be equal to weighted average of the predicted probability, etc. Simulations.
Metro Upper urban Upper rural Lower Urban Lower rural Border urban Border rural Household characteristics Log household size -0.440** -0.522** -0.625** -0.463** -0.420** -0.510* -0.371 Log household size2 -0.019 0.035* 0.087** -0.003 0.028* 0.006 -0.038 Share of children 0-6 -0.201** -0.270** -0.303** -0.226** -0.269** -0.298 -0.428* Share of children 7-15 -0.085** -0.158** -0.273** -0.119** -0.237** -0.209 -0.380** Share of elderly -0.148** -0.110* -0.113** -0.105* -0.087* -0.239 -0.380 Share of adult females -0.086** -0.039 -0.058* -0.065 -0.021 -0.318* -0.324* Share of adult males Reference Share of literate 0.325** 0.253** 0.261** 0.297** 0.288** 0.299* 0.193 Share of university 0.453** 0.192** 0.304** 0.635** 0.394** -0.099 -0.022 Share of unemployed 0.002 0.037 -0.014 0.107** 0.081** 0.447** 0.202 Characteristics of the head Age 0.017** 0.006* 0.005** 0.019** -0.002 0.019 0.005 Age2/100 -1.040** -0.231 -0.322 -1.438** 0.457* -1.623 -0.201 Male -0.072** -0.043** 0.005 -0.022 -0.039** -0.034 -0.051 Female Reference Education Illiterate -0.928** -0.738** -0.645** -1.030** -0.395** -0.960** -0.382 Read & Write -0.881** -0.693** -0.634** -0.960** -0.353** -0.791** -0.273 Basic -0.788** -0.581** -0.571** -0.944** -0.336* -0.745** -0.286 Secondary -0.668** -0.521** -0.523** -0.773** -0.269* -0.640** -0.077 Diploma -0.571** -0.421** -0.472** -0.701** -0.212 -0.564** -0.045 University -0.387** -0.359** -0.475** -0.617** -0.162 -0.458* -0.003 Postgraduate degree Reference Working status Government -0.031 -0.017 0.024 -0.123** 0.034 -0.249* 0.023 Public 0.017 0.010 0.034 -0.051 0.093** -0.130 -0.019 Private 0.158** 0.107** 0.043** 0.029 0.092** -0.114 0.040 Foreign/JVC 0.242** 0.159* 0.072 0.201** 0.055 -0.148 -0.096 Unemployed 0.069 0.160* 0.035 0.049 0.121 -0.031 -0.199 Out of labor force Reference Industry of employment Agriculture Reference
Regression of log consumption per capita on characteristics of household and household head for seven regions of Egypt.
Metro Upper Urban
Upper Rural
Lower Urban
Lower Rural
Border Urban
Border Rural
Child born in the family 56.22 63.93 45.02 34.79 23.97 65.91 34.82 Family member looses job 26.93 113.06 13.26 13.22 45.9 -13.6 -42.07 Female headed households -21.95 -17.47 2.92 -5.49 -10.08 -16.67 -15.59 Head education Change from illiterate to read and write -14.93 -17.28 -6.25 -16.06 -11.58 -57.86 -30.25 Change from illiterate to basic -39.7 -51.05 -31.64 -19.57 -15.68 -66.66 -26.09 Change from illiterate to secondary -62.68 -63.97 -47.6 -50.59 -32.03 -82.64 -68.38 Change from illiterate to diploma -75.57 -79.4 -61.19 -60.89 -44.36 -89.15 -72.72 Change from illiterate to University degree -89.92 -85.74 -60 -70.74 -53.26 -94.83 -75.95 Change from illiterate to postgraduate degree -98.95 -99.01 -99.14 -98.51 -76.38 -99.92 -77.53 Sector of employment Unemployed 0.42 3.12 0.52 4.55 3.86 24.65 8.39 employed in the government job 10.85 7.42 -9.77 34.12 -7.59 221.22 -5.77 employed in the public sector job -4.55 -3.57 -13.12 13.75 -20.79 89.91 6.57 employed in the private sector job -41.27 -36.8 -17.25 -6.81 -21.13 79.88 -9.42 employed in the foreign firm -57.17 -50 -29.26 -43.17 -12.22 121.15 30.69
Impact of changes in household characteristics on poverty
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