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1
China’s (Uneven) Progress Against Poverty
Martin Ravallion and Shaohua Chen Development Research Group, World Bank
2
Questions
• How much progress has China made against absolute poverty?
• When and where was the greatest progress made? • What happened to inequality? A poverty-inequality
trade off? • What were the proximate causes of uneven progress
over time and across provinces? What role was played by public policies?
• What lessons does China’s past success against poverty hold for China in the future and for the rest of the developing world?
3
DataFive findingsFive lessons
4
Data
5
Distributional data for China
• Newly constructed poverty lines– Old lines seen as out of date: “too low” + no allowance for geographic
COL differences – New lines: 850 Yuan per year for rural areas and 1200 Yuan for urban
areas, both in 2002 prices; also province-specific lines
• Newly assembled distributional data – much of which has not previously been analyzed– Rural Household Surveys (from 1980) and Urban Household Surveys
(1981) of National Bureau of Statistics– Early surveys small for 30% of provinces, but no sign of bias– Time series of tabulated distributions (micro data not available)
• Incomplete data at provincial level– though we can still provide estimates of the trends.
6
New poverty lines
• Region-specific food bundles for urban and rural areas, valued at median unit values by province.
• Food bundles based on the actual consumption of those between the 15th and 25th percentile nationally.
• These bundles are then scaled to reach 2100 calories per person per day, with 75% of the calories from foodgrains.
• Allowances for non-food consumption are based on the nonfood spending of households in a neighborhood of the point at which total spending equaled the food poverty line in each province (and separately for urban and rural areas).
7
Deflators over time• Urban and rural CPI
• Urban inflation rate higher than rural, esp., in the 1990s (higher costs of previously subsidized goods)
40
80
120
160
200
240
1980 1985 1990 1995 2000
CPI (100 in 1990)
Urban
Rural
8
Rising urban-rural COL differential
16
20
24
28
32
36
40
44
1980 1985 1990 1995 2000
Urban-rural cost-of-living differential (%)
9
Corrections for 1990 change in valuation method in RHS
• 1990 change in valuation methods for imputing income from consumption of own-farm output
• Distributions by both methods for 1990 are used to correct the data for the late 1980s
)(/)( 3
)9.44(
2
)5.54()8.111()5.5421(12562.023457.020915.019272.1
pppoldYnewY
R 2 = 0 . 9 9 9 5 9
10
Corrections for 1990 change in valuation method in RHS
• 1990 change in valuation methods for imputing income from consumption of own-farm output
• Distributions by both methods for 1990 are used to correct the data for the late 1980s
Alternative estimates for 1990
Mean income (Yuan per person)
Gini index (%)
Headcount index (%)
Old method New method:
629.70 31.53 37.63
1. Actual 686.30 29.87 29.93 2. Estimated using our correction model
688.05
30.05
29.86
11
Poverty measures
• Headcount index (H): % living in households with income per person below the poverty line.
• Poverty gap index (PG): mean distance below the poverty line as a proportion of the poverty line
• Squared poverty gap index (SPG): poverty gaps are weighted by the gaps themselves, so as to reflect inequality amongst the poor (Foster et al., 1984).
• Parameterized Lorenz Curves – alternative functional forms (Beta+general elliptical) – checks for theoretical consistency and accuracy
12
Inequality measures
• Relative Gini index based on sum of income differences normalized by the mean for that distribution
• Absolute Gini index based on sum of income differences normalized by a fixed mean
13
Persistent data problems
• Sample frame based on registration system => underestimation of urban poverty
• Survey compliance problems, esp., urban areas
• Single price indices, independent of level of income
14
Five findings
15
1. Huge overall progress against poverty, but uneven progress
2. Rising inequality, though more so in some periods and places
3. The pattern of growth matters to both poverty and inequality in China
4. No sign of an aggregate growth-equity trade off
5. Poverty would have fallen much faster without rising inequality
16
Finding 1: Huge overall progress against poverty, but uneven progress
• In the 20 year period after 1981, the proportion living below our new poverty lines fell from 53% to 8%. ( 62%+ in 1980.)
• Half of the decline in poverty came in 1981-84. • However, there were many setbacks for the poor.
– Poverty rose in the late 1980s and stalled in early 1990s, – recovered pace in the mid-1990s, – but stalled again in the late 1990s.
17
0
10
20
30
40
50
60
1980 1985 1990 1995 2000
Headcount index (%)
Upper line
Lowerline
Headcount index, 1981-2001
18
Headcount index for “$1/day”, 1981-2001
10
20
30
40
50
60
70
1980 1985 1990 1995 2000
China
Developing world less China
East Asialess China
19
0
10
20
30
40
50
60
70
80
1980 1985 1990 1995 2000
Headcount index for rural areas
Upperline
Lowerline
Old valuationmethod
Effect on headcount index of our correction for the change in valuation methods
20
0
1
2
3
4
5
6
7
-30 -20 -10 0
Trend rates of change in rural headcount index (upper line; by province; %/year; 1983-2001)
Xit
Xi
Xiit tX log
21
0
1
2
3
4
5
6
7
-30 -20 -10 0
Trend rates of change in rural headcount index (upper line; by province; %/year; 1983-2001)
Xit
Xi
Xiit tX log
Guangdong
Fujian, Jiangsu
Beijing
22
Finding 2: Rising inequality But not continuously and more so in some
periods and some provinces
• Relative inequality is higher in rural than urban areas– in marked contrast to most developing countries.
• Though steeper increase in urban inequality. • Relative inequality between urban and rural areas has
not shown a rising trend once one allows for the higher rate of increase in the urban cost-of-living.
• Absolute inequality has increased appreciably – between and within both urban and rural areas, – and absolute inequality is higher in urban areas.
23
1.2
1.6
2.0
2.4
2.8
1980 1985 1990 1995 2000
Without adjustment forurban-rural COL differential
With adjustment for COL
Ratio of urban to rural mean income
Relative inequality between urban and rural areas
24
0.0
0.4
0.8
1.2
1.6
2.0
2.4
1980 1985 1990 1995 2000
Difference between urban and rural mean(divided by 1990 national mean)
With COL adjustment
Without COL adjustment
Absolute inequality between urban and rural areas
25
10
15
20
25
30
35
40
1980 1985 1990 1995 2000
Urban
Rural
National
Gini index (%)
Relative inequality in rural and urban areas and nationally
26
0
20
40
60
80
100
120
140
1980 1985 1990 1995 2000
National
Rural
Urban
Absolute Gini index (relative to 1990 mean)
Absolute inequality in rural and urban areas and nationally
27
100
200
300
400
500
600
700
24
28
32
36
40
1980 1985 1990 1995 2000
Me
an
inco
me
in r
ura
l are
as
(Yu
an
/pe
rso
n/y
ea
r; 1
98
0 p
rice
s)G
ini index of income inequality (%
)
Old valuation method(broken lines)
Gini index(right axis)
Mean(left axis)
Effect on Gini index and mean of our correction for the change in valuation methods
28
• Economic growth was clearly a key proximate cause of poverty reduction
• Growth elasticity of poverty reduction
= – 3.2 (t= – 8.7) (using survey means)
– 2.6 (t= – 2.2) (using GDP per capita)
Finding 3: The pattern of growth matters
ttt YP lnln 10
29
The sectoral pattern of growth matters
• The gains to the poor from aggregate economic growth depended on its sectoral composition.
• Decomposition of change in poverty:
– Within-sector effect is the change in poverty measures over time weighted by final year population shares
– Population shift effect measures the partial contribution of urbanization over time, weighted by the initial urban-rural difference in poverty measures. (Kuznets process of migration.)
)])([()]()([ 810181818101018101018101uuruuuurrr nnPPPPnPPnPP
W i t h i n - s e c t o r e f f e c t P o p u l a t i o n s h i f t e f f e c t
30
Poverty measures
(% point change 1981-2001) H PG SPG
Within rural
-32.53 (72.5)
-10.39 (74.0)
-4.51 (75.0)
Within urban
-2.08 (4.6)
-0.32 (2.3)
-0.09 (1.5)
Population shift
-10.27 (22.9)
-3.32 (23.7)
-1.42 (23.6)
Total change -44.87 -14.04 -6.01 Note: % of total in parentheses.
Decomposition of the change in povertyMigration to urban areas helped, but the bulk of the reduction in poverty came from within rural areas
Note: Quite rapid urbanization despite restrictions on migration• Urban share of 19% in 1980; rose to 39% in 2002
31
Regression decomposition for mean income growth
• Mean income: • Growth rate:
• Test equation:
• Null hypothesis:
ut
ut
rt
rtt nn
rt
ut
rt
ut
rt
ut
ut
rt
rtt nnnssss ln)]/([lnlnln
tit
it
it ns /
trtu
t
rtu
trt
n
ut
ut
urt
rt
rt
nn
nss
ssP
ln).(
lnlnln 0
H0: i for i=r,u,n
32
Headcount
index Poverty gap index
Squared poverty gap index
Constant 0.033 0.040 0.039 (0.808) (0.690) (0.510)
-2.563 -3.341 -3.722 Growth rate of mean rural income (share-weighted) ( r)
(-8.432) (-7.768) (-6.637)
0.092 0.519 0.744 Growth rate of mean urban income (share-weighted) ( u)
(0.201) (0.797) (0.877)
0.735 2.189 3.941 Population shift effect ( n) (0.159) (0.335) (0.462) R2 0.823 0.796 0.739 D-W 2.671 2.653 2.661
trtu
t
rtu
trt
n
ut
ut
urt
rt
rt
nn
nss
ssP
ln).(
lnlnln 0
33
Headcount
index Poverty gap index
Squared poverty gap index
Constant 0.033 0.040 0.039 (0.808) (0.690) (0.510)
-2.563 -3.341 -3.722 Growth rate of mean rural income (share-weighted) ( r)
(-8.432) (-7.768) (-6.637)
0.092 0.519 0.744 Growth rate of mean urban income (share-weighted) ( u)
(0.201) (0.797) (0.877)
0.735 2.189 3.941 Population shift effect ( n) (0.159) (0.335) (0.462) R2 0.823 0.796 0.739 D-W 2.671 2.653 2.661
trtu
t
rtu
trt
n
ut
ut
urt
rt
rt
nn
nss
ssP
ln).(
lnlnln 0
34
Decomposing GDP growth
• Standard classification of its origins, namely – “primary” (mainly agriculture), – “secondary” (manufacturing and construction) and – “tertiary” (services and trade).
• The primary sector’s share fell from 30% in 1980 to 15% in 2001, though not montonically.
• Almost all of this decline was made up for by an increase in the tertiary-sector share.
35
10
20
30
40
50
60
1980 1985 1990 1995 2000
Secondary
Tertiary
Primary
Share of GDP
Shares of GDP by sector
36
Regression decomposition for sectoral decomposition
• Test equation:
• Null hypothesis:
H0: i for i = 1,..n
t
n
iititit YsP
10 lnln
37
H e a d c o u n t i n d e x ( l o g d i f f e r e n c e ) C o n s t a n t 0 . 1 1 6 0 . 1 6 3 0 . 1 5 5 ( 1 . 0 5 9 ) ( 1 . 6 5 6 ) ( 1 . 7 6 1 )
- 2 . 5 9 5 G r o w t h r a t e o f G D P p e r c a p i t a ( - 2 . 1 6 2 )
- 8 . 0 6 7 - 7 . 8 5 2 P r i m a r y ( 1 ) ( - 3 . 9 6 9 ) ( - 4 . 0 9 2 ) - 1 . 7 5 1 S e c o n d a r y ( 2 ) ( - 1 . 2 1 4 ) - 3 . 0 8 2 T e r t i a r y ( 3 ) ( - 1 . 2 3 9 ) - 2 . 2 4 5 S e c o n d a r y +
T e r t i a r y ( - 2 . 1 9 9 ) R 2 0 . 2 0 7 0 . 4 3 1 0 . 4 2 3 D - W 1 . 5 5 3 1 . 7 2 5 1 . 7 6 8
- 6 . 3 1 7 - 5 . 6 0 7 21
( - 3 . 2 3 1 ) ( - 3 . 1 4 ) 1 . 3 3 1
32 ( 0 . 4 0 5 )
t
n
iititit YsP
10 lnln
38
H e a d c o u n t i n d e x ( l o g d i f f e r e n c e ) C o n s t a n t 0 . 1 1 6 0 . 1 6 3 0 . 1 5 5 ( 1 . 0 5 9 ) ( 1 . 6 5 6 ) ( 1 . 7 6 1 )
- 2 . 5 9 5 G r o w t h r a t e o f G D P p e r c a p i t a ( - 2 . 1 6 2 )
- 8 . 0 6 7 - 7 . 8 5 2 P r i m a r y ( 1 ) ( - 3 . 9 6 9 ) ( - 4 . 0 9 2 ) - 1 . 7 5 1 S e c o n d a r y ( 2 ) ( - 1 . 2 1 4 ) - 3 . 0 8 2 T e r t i a r y ( 3 ) ( - 1 . 2 3 9 ) - 2 . 2 4 5 S e c o n d a r y +
T e r t i a r y ( - 2 . 1 9 9 ) R 2 0 . 2 0 7 0 . 4 3 1 0 . 4 2 3 D - W 1 . 5 5 3 1 . 7 2 5 1 . 7 6 8
- 6 . 3 1 7 - 5 . 6 0 7 21
( - 3 . 2 3 1 ) ( - 3 . 1 4 ) 1 . 3 3 1
32 ( 0 . 4 0 5 )
t
n
iititit YsP
10 lnln
39
Primary sector was the main engine of poverty reduction
• Growth in the primary sector (primarily agriculture) did more to reduce poverty than either the secondary or tertiary sectors.
• Starting in 1981, if the same aggregate growth rate
had been balanced across sectors then it would have taken 10 years to bring the national poverty rate down to 8%, rather than 20 years.
• But could a more equitable growth process have allowed the same rate of growth?
40
Province level
• Complete series of mean income from 1980
• But less complete distributional data; 11-12 years
• Marked differences in initial conditions; Gini index around mid-1980s varied from 18% to 33%.
• OLS estimates of province specific trends:Xit
Xi
Xiit tX log
41
-30
-25
-20
-15
-10
-5
0
5
0 1 2 3 4 5 6 7
Tre
nd in
rura
l headco
unt index (%
per ye
ar)
Trend in mean income (% per year)
Beijing
Tianjin
Shanghai
Provinces with higher growth rates in rural mean income saw faster poverty reduction
42
-30
-25
-20
-15
-10
-5
0
5
0 1 2 3 4 5 6 7
Tre
nd in
rura
l headco
unt index (%
per ye
ar)
Trend in mean income (% per year)
Beijing
Tianjin
Shanghai
Provinces with higher growth rates in rural mean income saw faster poverty reduction
Reliability?H<2%
43
-30
-25
-20
-15
-10
-5
0
5
0 1 2 3 4 5 6 7
Tre
nd in
rura
l headco
unt index (%
per ye
ar)
Trend in mean income (% per year)
Beijing
Tianjin
Shanghai
Provinces with higher growth rates in rural mean income saw faster poverty reduction
Elasticity = -2.4 (t = -4.3)(dropping Beijing, Shanghai, Tianjin)
44
Wide variation in growth elasticities of poverty reduction
• 95% CI for the impact of a 3% growth rate on H is (0%, 9%)
• Dropping Beijing, Shanghai and Tianjin the 95% CI for 3% growth rate is (4%, 10%)
• Growth elasticity calculated as ratio of trend in H to trend in mean varies from –6.6 ro 1.0 (mean=-2.3)
• Geographic composition of growth mattered to aggregate rate of poverty reduction….
45
0
1
2
3
4
5
6
7
-.8 -.7 -.6 -.5 -.4 -.3 -.2 -.1 .0 .1
Share weighted total elasticity of the headcount index to growth
Tre
nd rate
of gro
wth
in m
ean rura
l inco
me (%
/year)
Henan
Growth did not occur where it would have most impact on poverty
46
Inequality and the pattern of growth
• The composition of growth also mattered to the evolution of aggregate inequality.
• Agricultural growth was inequality decreasing.
47
1 2 3 C o n s t a n t - 0 . 0 7 2 0 . 0 3 8 0 . 0 3 8 ( 0 . 4 2 9 ) ( 1 . 2 7 8 ) ( 3 . 5 9 8 )
0 . 0 1 2 G r o w t h r a t e o f G D P p e r c a p i t a ( 0 . 5 4 4 )
- 1 . 7 9 8 - 1 . 7 5 5 P r i m a r y ( 1 ) ( 2 . 2 4 4 ) ( 2 . 8 1 9 ) 0 . 1 7 0 S e c o n d a r y ( 2 ) ( 0 . 4 3 2 ) - 0 . 2 1 8 T e r t i a r y ( 3 ) ( - 0 . 2 7 2 )
R 2 0 . 0 1 8 0 . 3 2 6 0 . 3 1 6 D - W 2 . 1 1 2 2 . 1 1 2 2 . 2 0 2
- 1 . 9 6 8 21 ( 2 . 2 6 3 ) 0 . 3 8 8 32 ( 0 . 3 8 1 )
N o t e : T h e d e p e n d e n t v a r i a b l e i s t h e f i r s t d i f f e r e n c e o v e r t i m e i n t h e l o g o f t h e G i n i
Inequality and GDP growth by origin
48
1 2 3 C o n s t a n t - 0 . 0 7 2 0 . 0 3 8 0 . 0 3 8 ( 0 . 4 2 9 ) ( 1 . 2 7 8 ) ( 3 . 5 9 8 )
0 . 0 1 2 G r o w t h r a t e o f G D P p e r c a p i t a ( 0 . 5 4 4 )
- 1 . 7 9 8 - 1 . 7 5 5 P r i m a r y ( 1 ) ( 2 . 2 4 4 ) ( 2 . 8 1 9 ) 0 . 1 7 0 S e c o n d a r y ( 2 ) ( 0 . 4 3 2 ) - 0 . 2 1 8 T e r t i a r y ( 3 ) ( - 0 . 2 7 2 )
R 2 0 . 0 1 8 0 . 3 2 6 0 . 3 1 6 D - W 2 . 1 1 2 2 . 1 1 2 2 . 2 0 2
- 1 . 9 6 8 21 ( 2 . 2 6 3 ) 0 . 3 8 8 32 ( 0 . 3 8 1 )
N o t e : T h e d e p e n d e n t v a r i a b l e i s t h e f i r s t d i f f e r e n c e o v e r t i m e i n t h e l o g o f t h e G i n i
Inequality and GDP growth by origin
49
Rural Urban Constant 0.013 0.006 (0.880) (0.386)
-0.476 -1.430 Growth rate in mean rural income (-3.206) (-5.808)
0.510 1.014 Growth rate in mean rural income lagged (4.322) (4.635)
0.075 0.687 Growth rate in mean urban income (0.830) (3.305) R2 0.491 0.690 D-W 1.741
Inequality and growth in mean urban and rural incomes
Rural economic growth reduced inequality within both urban and rural areas, as well as between them
50
Rural Urban Constant 0.013 0.006 (0.880) (0.386)
-0.476 -1.430 Growth rate in mean rural income (-3.206) (-5.808)
0.510 1.014 Growth rate in mean rural income lagged (4.322) (4.635)
0.075 0.687 Growth rate in mean urban income (0.830) (3.305) R2 0.491 0.690 D-W 1.741
Inequality and growth in mean urban and rural incomes
Rural economic growth reduced inequality within both urban and rural areas, as well as between them
51
Finding 4: No sign of an aggregate growth-equity trade off
• The strong positive correlation over time between China’s GDP per capita and inequality is driven by common time trends.
• Near zero correlation between changes in (log) Gini and growth rate.
• The periods of more rapid growth did not bring more rapid increases in inequality. Indeed,…
52
Annualized log difference (%/year)
Inequality
Gini index
Mean household
income
GDP per
capita
1. 1981-85 Falling -1.12 8.87 8.80 2. 1986-94 Rising 2.81 3.10 7.99 3. 1995-98 Falling -0.81 5.35 7.75 4. 1999-2001 Rising 2.71 4.47 6.61
The periods of falling inequality had highest growth in mean household income
53
Annualized log difference (%/year)
Inequality
Gini index
Mean household
income
GDP per
capita
1. 1981-85 Falling -1.12 8.87 8.80 2. 1986-94 Rising 2.81 3.10 7.99 3. 1995-98 Falling -0.81 5.35 7.75 4. 1999-2001 Rising 2.71 4.47 6.61
The periods of falling inequality had highest growth in mean household income
54
-0.4
0.0
0.4
0.8
1.2
1.6
2.0
2.4
2.8
3.2
0 1 2 3 4 5 6 7
Trend growth rate in mean rural income (% per year)
Tre
nd in
rur
al G
ini ind
ex (%
per
yea
r)
Provinces with higher growth did not have steeper rises in inequality
r = -0.18
Xit
Xi
Xiit tX log
55
Double handicap in more unequal provinces
More unequal provinces faced two handicaps in rural poverty reduction:
1. High inequality provinces had a lower growth elasticity of poverty reduction:
2. High inequality provinces had lower growth: signs of “inefficient inequality” both within rural areas, and between urban and rural areas =>
tG
iR
iR
iY
iH
i Gy ˆ365.1)1)(0136.0935.5(/)392.2(
8380)560.2()487.4(
R 2 = 0 . 3 8 6 ; n = 2 9
56
Regressions for provincial trends in poverty and mean incomes
tii
iR
iiH
i
GDONGCOAST
URGY
ˆ012.25291.9
797.6463.0141.0877.67
)160.15()292.5(
)201.3(83
)313.3(80
)090.8()239.6(
R 2 = 0 . 8 2 7
tii
iR
iiY
i
GDONGCOAST
URGY
ˆ290.1507.0
632.1149.0007.0143.14
)875.1()913.0(
)682.2(83
)526.2(80
)294.1()759.3(
R 2 = 0 . 4 2 3
Initial conditions (mean and distribution) + location
57
Initially poorer and less unequal provinces had higher rates of poverty reduction
• Large effects; going from the lowest initial inequality to the highest inequality cuts 7% points off the annual rate of poverty reduction.
• Initial distribution matters independently of growth; both inequality measures remain significant (though with smaller coefficients) when one adds the trend growth rate to the regression for trend poverty reduction
58
Finding 5: Poverty would have fallen much faster without rising inequality
• Lack of aggregate growth-equity trade-off implies that:– Growth has more impact on poverty– Rising inequality puts a brake on poverty reduction
• If not for the rise in inequality within rural areas, the national poverty rate in 2001 would have been 1.5% rather than 8%.
• In most provinces, rapidly rising rural inequality meant far lower poverty reduction than one would have expected given the growth. – An exception was Guangdong, which achieved rapid rural
poverty reduction by combining growth with stationary inequality. Why?
• Nor did higher inequality permit higher growth
59
Steeper increases in inequality did not mean faster poverty reduction
-30
-25
-20
-15
-10
-5
0
5
-0.4 0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2
Trend in inequality (% per year)
Tre
nd in
headco
unt in
dex
(% p
er ye
ar)
Guangdong
Beijing
60
0
4
8
12
16
20
24
28
0 4 8 12 16
Act
ual h
eadco
unt index in
2001 (%
)
Simulated headcount index in 2001using 1981 Lorenz curve (%)
Actual poverty incidence in 2001 and simulated level without the rise in inequality
61
Five lessons
62
Lesson 1: Low-lying fruit of agrarian reform
• Great Leap Forward and the Cultural Revolution left a legacy of pervasive and severe rural poverty by the late 1970s.
• Yet much of the rural population that had been forced into collective farming (with weak incentives for work) could still remember how to farm individually.
• Undoing these failed policies called for de-collectivizing agriculture and shifting the responsibility for farming to households.
• This brought huge gains to the country’s (and the world’s) poorest. Possibly half of the total decline in poverty in China 1981-2001 was due to this reform.
• But it was a one-time reform.
63
Lesson 2: Agricultural growth is good for poor people
• Important lesson for other developing countries.• Though here too are unusual historical circumstances:
– the relatively equitable land allocation that could be achieved at the time of breaking up the collectives.
• With fairly equal access to land (at least for the present) and relatively few distortions to incentives, achieving higher agricultural growth in China will require – sound investments in research and development, – and in rural infrastructure.
• Evidence that targeted poor-area development programs can help in this setting.
64
Lesson 3: Some forms of public spending and taxation matter more than others
• Taxation: Don’t tax poor farmers to subsidize urban consumers! Higher procurement prices reduced poverty.
• These are distributional effects in large part:
• This too is an unusual country circumstance– a procurement system that taxed farmers by setting quotas and
fixing procurement prices below market levels. • This was a powerful anti-poverty lever in the short-term.
• Public spending: Local – but not central – public spending reduced poverty, but not inequality.
tttt CPIPPH ln249.1ln257.1082.0ln 12
)492.2(1
)688.3()058.3(
tttt YCPIPPH ln335.2ln882.0ln040.1060.0ln)843.9(
12
)651.4(1
)049.8()791.3(
65
Lesson 4: Less clear on economy-wide policies (macro stability and free trade)
• Support for the view that macroeconomic stability (esp., avoiding inflationary shocks) has been good for poverty reduction:
• But the score card for trade reform is blank!
– Neither the trade reforms nor the trade expansions coincided with the times of falling poverty.
– Zero correlation between changes in trade volume (TV) and changes in poverty. Nor with lagged TV up to two years.
– Also holds with controls (inflation, proc. price, mean Y).– Endogeneity of trade? Yes, but bias probably goes against the
view that trade reform was poverty reducing in short-term.
tttt CPIPPH ln249.1ln257.1082.0ln 12
)492.2(1
)688.3()058.3(
66
Lesson 5: Inequality is now an issue for China
• High inequality in many provinces will inhibit future prospects for both growth and poverty reduction.
• Aggregate growth is increasingly coming from sources that bring limited gains to the poorest.
• Inequality is continuing to rise and poverty is becoming much more responsive to rising inequality.
• Perceptions of what “poverty” means are also changing, which can hardly be surprising in an economy that can quadruple its mean income in 20 years.
Elasticity of H to Gini
1981 0.0 2001 3.7