Transcript The Growth of Poor Children in China 1991-2000

The Growth of Poor Children in
China 1991-2000:
Why Food Subsidies May Matter
Lars Osberg
Jiaping Shao
Kuan Xu
Economics Department
Dalhousie University
UNU-WIDER Conference
Advancing Health Equity
29-30 September 2006
Helsinki, Finland
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The paper in one slide
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China – 1991 – 2000
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Does income poverty now matter more for
child development in China?
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Rapid growth in inequality & average income
Increased Average Height-for-Age children 2-13
Elimination of food subsidies after 1995
Little increase in height of disadvantaged kids
Robust OLS & quantile regressions on panel data
Poverty status & growth in height-for-age
 Not significant in 1991-1993
 Significant negative impact 1997-2000
General moral: Food subsidization may play
an important social protection role for child
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well-being and development
China Health and Nutrition Survey
(CHNS)

Micro-data collected in 1989, 1991, 1993,
1997 and 2000


Surveys conducted by the Carolina Population Center
at the University of North Carolina
Follows a panel of about 16,000 individuals in
4,400 households in 9 provinces
 Incredible level of detail
1991 – 2000 data used
 Children aged 2 to 13
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<2 – variable height + measurement error
>13 – variability due to puberty onset
documentation available at
http://www.cpc.unc.edu/china
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Survey Provinces
4
Context: Very Rapid Growth in GDP
Per Capita & Inequality in China

GDP per capita in
China
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1980 =$763
2004 = $5,419
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Gini index of
inequality in money
incomes
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China
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1991-2000 annual
real growth rate of per
capita GDP = 9.2 %
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1991 = $ 1,721
2000 = $ 3,928
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World Bank GDP
per capita, PPP
(constant 2000
international $)
2006 = 10.9% GDP
growth

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Canada
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0.338 to 0.368
Netherlands

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0.281 to 0.302
USA
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0.345 in 1991
0.407 in 2000.
0.266 to 0.248
Switzerland
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0.309 to 0.280
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Overall Income Distribution Shifts Up
– Lower Tail Stays
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Issue: Well-Being & Growth ??
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Rising Inequality in Cash Income in China
+ Money Matters More
Social Policy Changes
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Marketization
Elimination of food subsidies
Loss of employment guarantees
Loss of health care coverage
Are the poor absolutely worse off?
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Meng, Gregory and Wang (2005)
Does poverty affect health of poor kids?
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HAZi =
(height child i – median height same sex & age)
(standard deviation of height - same age & sex)

“good indicator underlying health status”

slow height growth correlates with:
perform less well in school
 score poorly on tests of cognitive function
 poorer psychomotor skills & fine motor skills
 lower activity levels
 interact less frequently in their environments
 fail to acquire skills at normal rates
Mansuri (2006:3)
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HAZi < -2 = “stunted”
HAZi < -3 = “severely malnourished”
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Indicator of most basic of Sen’s “Capabilities”
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to attain normal physical & cognitive development
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Chinese Children are taller on average
- Height as % of CDC Norm Age 2 -18
Male
1
0. 99
1991
2000
0. 98
0. 97
0. 96
0. 95
0. 94
0. 93
0. 92
24
48
72
96
120
144
168 192
216
Age i n Mont h
Female
1991
2000
1
0. 99
0. 98
0. 97
0. 96
0. 95
0. 94
0. 93
0. 92
24
48
72
96
120
144
Age i n Mont h
168
192
216
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Change of average height-for-age (HAZ)
by decile 1991 to 2000 (age 2-13)
Decile
Average
HAZ
1991
Average
HAZ
2000
Absolute
Change
Percentage
Change
1
-3.39
-3.22
0.16
4.8 %
2
-2.51
-2.09
0.42
16.8 %
3
-2.12
-1.58
0.53
25.1 %
4
-1.80
-1.25
0.55
30.7 %
5
-1.50
-0.95
0.55
36.8 %
6
-1.19
-0.62
0.56
47.5 %
7
-0.87
-0.34
0.53
60.6 %
8
-0.52
0.01
0.53
101.3 %
9
-0.13
0.45
0.58
439.8 %
10
0.80
1.30
0.50
62.1 %
N
2766
1735
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Stagnation in % children who are
“Severely Malnourished” [HAZi < -3] ?
HAZi < -3
HAZi < -2
1991
7.23%
28.49%
1993
6.27%
24.86%
1997
3.94%
19.71%
2000
4.27%
16.43%
[1991: n=1659; 1993: n=1390;1997:n=1123; 2000:n=813]
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Income Growth + Social Policy Reform
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Rapid growth in GDP in China
accompanied by structural reforms
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Employment security
Housing
Food subsidies
Relatively more important for low income
households
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“Even though income growth reduces poverty,
the radical reform measures implemented in
the 1990s have sufficiently offset this gain that
urban poverty is higher in 2000 than in 1986.”

Meng, Gregory and Wang (2005)
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Social Protection in 1991 and 2000
1991
Individual
%1
2000
Mean2
health subsidy rec'd last year
8.18%
Bath/haircut subsidy rec'd last year
23.41% 78.93
#
Book/newspaper subsidy rec'd last
12.60% 85.74
year
#
House subsidy rec'd last year
2.02%
116.14
#
Other nonfood subsidy last year
15.48% 264.25
#
Meat/veg/oil subsidy rec'd last year
30.80% 144.94
#
Does person have health insurance?
27.77%
19.94%
Annual insurance premium
105.72
%
#
2.87
77.55
Household
Average value of ration coupon last
year
422.77
Mean
#
Value of Food Coupons, 1991
[$2 PPPpoverty line = 1072 Yuan; ½ Median = 597 Yuan]
Item
%1
Average
annual
amount 2
Average
market value
per coupon
(Yuan)
Total
coupon
value
(Yuan)
Rice
86.34%
690.32
0.43
296.84
Wheat Flour
71.28%
512.5
0.32
164
Other cereal grains
27.15%
334.9
0.24
80.38
Cooking oil
81.05%
32.36
2.53
81.87
Eggs
2.67%
25.98
1.63
42.35
Pork (or other meat)
9.59%
67.04
2.93
196.43
Chicken
0.29%
20
n/a
n/a
Sugar
3.60%
29.34
1.83
53.69
Other
4.30%
1185.74
0.78
924.88
Does income poverty now matter more
for child development in China?
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Loss of food subsidy has removed buffer
to impact of income shocks
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China – special factors
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HAZi reflects accumulation of all past
health & nutrition
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“One child” policy means family resources are
concentrated
Very rapid growth in most people’s incomes
Including any long-ago food subsidies
∆ HAZi – is current growth influenced by
current income shocks ?
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Panel OLS 1991-2000; 2-4 become 11-13
Poverty line=$2 / day ; very small sample
Variables
1991-2000
Dependent variable
HAZ_2000
HAZ_initial year
0.472*** (0.132)
Father weight (kg)_initial year
0.012
(0.008)
Father height (cm) _initial year
0.018
(0.020)
Father age at child’s birth
0.013
(0.027)
Father # of yrs formal education_initial year
-0.053*** (0.018)
Mother weight (kg) _initial year
0.023**
(0.011)
Mother height (cm) _initial year
0.029*
(0.015)
Mother age at child’s birth
-0.026
(0.089)
Mother age at child’s birth squared
0.000
(0.001)
Mother # of yrs formal education initial year
0.063*** (0.017)
Change of number of household members
-0.101
(0.087)
Log of total equivalent income in the period
-0.130
(0.169)
Dummy=1 if income <$2 / day_91
0.156
(0.129)
Dummy=1 if income <$2 / day _93
0.410*** (0.128)
Dummy=1 if income <$2 / day_97
-0.603*** (0.148)
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Estimates from panel – Robust OLS
– Early and late 1990s compared

Poverty line = $2 / day / per capita
Controls for tap water, region
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Larger sample
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2 to 11 in 1991 were 4 to 13 in 1993
2 to 10 in 1997 were 5 to 13 in 2000
Poverty status
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insignificant in 1991 & 1993
Statistically significant & negative in 1997 &
2000
 Same results if ½ median poverty line
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Either national median or rural/urban separately
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Variables
1991-1993
1997-2000
Dependent variable
HAZ_1993
HAZ_2000
HAZ initial year
0.711*** (0.042)
0.537*** (0.041)
Father weight (kg)
0.001
0.016*** (0.005)
Father height(cm)
0.010** (0.005)
0.003
(0.007)
Father age at child’s birth
0.009
(0.009)
0.005
(0.013)
Father education
0.015
(0.010)
-0.005
(0.013)
Mother weight(kg)
0.007*
(0.004)
0.008*
(0.004)
Mother height (cm)
0.003
(0.006)
0.019*** (0.007)
Mother age at childbirth
0.013
(0.037)
0.112**
Mother age squared
0.000
(0.001)
-0.002*** (0.001)
Mother education
-0.005
(0.009)
0.020*
(0.010)
Change number in hhold
0.023
(0.046)
-0.033**
(0.016)
Log total equiv income
0.027
(0.046)
-0.087
(0.061)
income <$2 / day_91
-0.029
(0.066)
income <$2 / day _93
0.069
(0.083)
(0.003)
income <$2 / day_97
-0.193**
income <$2 / day _2000
-0.153*
(0.048)
(0.098)
(0.082)
OLS – presumes common impact of
RHS variables on conditional mean
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OLS – choose β to minimize sum squared
residuals
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Social important issue – stunting & deprivation
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Implies: outliers acquire greatest weight
Presumes: symmetric loss function for errors
Child growth & development – arguably a different
process for the stunted & for the thriving
Quantile regression
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Estimates the differing determinants of outcomes
at each point in the outcome distribution
Linear, asymmetric loss function
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Panel 1991-93
– Robust OLS & Quantile Regression
Estimated Impact of Poverty on HAZi
Poverty
1991
0.4
Poverty
1993
0.4
0.2
0.2
0
0
-0.2
-0.2
-0.4
-0.4
-0.6
-0.6
-0.8
-0.8
-1
-1
0
20
40
60
Quantile
80
100
Quantile point estimates
95% pointwise confidence band
OLS estimate
95% confidence interval for OLS estimate
0
20
40
60
Quantile
80
100
Quantile point estimates
95% pointwise confidence band
OLS estimate
95% confidence interval for OLS estimate
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Panel 1997-2000
– Robust OLS & Quantile Regression
Estimated Impact of Poverty on HAZi
Poverty
1997
0.4
Poverty
2000
0.4
0.2
0.2
0
0
-0.2
-0.2
-0.4
-0.4
-0.6
-0.6
-0.8
-0.8
-1
-1
0
20
40
60
Quantile
80
100
Quantile point estimates
95% pointwise confidence band
OLS estimate
95% confidence interval for OLS estimate
0
20
40
60
Quantile
80
100
Quantile point estimates
95% pointwise confidence band
OLS estimate
95% confidence interval for OLS estimate
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Quantile Regression Estimates
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1991 & 1993
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1997
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quantile point estimates vary relatively little
& close to OLS estimates - i.e. β = 0
nothing gained by using quantile regression
fairly close to OLS β = -0.2
(≠0 @ 95%)
2000
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Increasingly large negative impact of
poverty for larger HAZ
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Poverty especially reduces the chances of
substantial growth
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Caveats

China = 1.3 Billion people

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HUGE diversity of circumstances
CHNS data – very fine BUT

Great Audacity would be required to generalize
from 4,400 households in 9 provinces
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Sample selection implies much smaller sample size for
regressions reported here
 N = 1278, 587, 129
Simplest poverty measure used + 3
alternative poverty lines
Suggestive results NOT conclusive evidence
– to be corroborated with larger data sets ??
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Possible Implications

Bottom decile of children aged 2-13 in
China ≈ 13 million

Failure to keep up with increase in stature
of other children matters
1: For future output, health & well-being
2: Because children are citizens NOW

General Moral?

Subsidies to basic food availability may play
a crucial safety net role for child well-being
Historically important in OECD nations
 Worth considering in Social Policy Reform in
LDCs
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