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• Newly constructed poverty lines– Old lines seen as out of date: “too low” + no allowance for geographic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