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1. These included the poor counties in the ‘three Xi’ prefectures that had been given state

fi nancial aid since the early 1980s, namely, Dingxi and Hexi prefectures in Gansu province

and Xihaigu prefecture in Ningxia Autonomous Region.

2. See the Appendix for a discussion of national poverty trends.

3. Agricultural Development Bank was set up in 1994 to manage policy loans for the

agricultural sector, and took charge of subsidized loans for four years. In 1998 the

responsibility for subsidized loans was assigned back to the Agricultural Bank of

China.

4. Chapter 1 discusses these two types of targeting error.

5. TCG and TIG are analogous to the widely used poverty headcount and poverty gap

measures, but are two-sided rather than one-sided.

6. Since the targeting income gap for all counties is 77 yuan and all the income gaps are

from one fi fth of the mis-targeted counties, the average magnitude of mis-targeting in

mis-targeted counties is 385 yuan.

7. The targeting income error formula is the same as for targeting income gap except the

poverty line Z is now the income of the threshold county and the summation is divided

by D, instead of N. Targeting rank error replaces income difference with income rank

difference.

8. The Ministry of Agriculture data is known to show more poverty in China’s southwest

and less in the northwest in comparison with the National Bureau of Statistics data

(World Bank, 1992). Both data are available for poor counties in 1994 and 1995. The

two series have a rank correlation of 0.89 and 0.92 in the two years.

9. Part of the measured bias against southwest provinces may be due to biases in the Ministry

of Agriculture versus National Bureau of Statistics data. However, offi cials in Beijing

confi rmed that the number of poor counties in the poorest provinces was limited to

preserve balance among provinces.

10. Among 592 poor counties, 532 counties have complete data for all four years.

11. The authors fi nd that living in an area with poor natural conditions reduces consumption

growth; namely poor areas tend to grow slower because of geographic externalities.

Without allowing for geographic externalities, the estimated rate of return from poverty

programs is zero.

12. The specifi cation implicitly assumes that poor county designation is not endogenous to

time-varying unobservables that differ within prefectures and are not correlated with initial

characteristics. The authors estimate three equations in fi rst differences simultaneously,

using an iterative 3SLS procedure, imposing appropriate cross-equation restrictions and

using different instruments for the three equations. The instruments are lagged variables

for income, grain production and poverty status. The coeffi cients on the poverty status

variables should be interpreted as the effect of the poverty program on counties in the

same prefecture in the same period with the same starting income and grain production

levels and controlling for time-invariant unobservables. Without allowing for fi xed effects,

the effect of the poverty program is negative in both periods, although not statistically

signifi cant in the second period.

13. This involves estimating non-food expenditures based on a regression of food share on

a constant and the log of total expenditures/food poverty line.

14. As we have noted, the non-food expenditure share of 40 per cent used prior to 1998

dropped sharply to 17 per cent in 1998 due to the change from a fi xed share to regression

estimation. Data made available to the author by the NBS show that in 1999, the nonfood

expenditure shares of the poor, defi ned as those with incomes below 850 yuan per

capita, in Guizhou, Gansu and Henan province were 27 per cent, 33 per cent and 49 per

cent, respectively.

15. The poverty headcounts of the World Bank (2001) are about ten percentage points higher

using expenditure rather than income data (see Table A.4.4).

16. Chen and Ravallion (1996) calculate price indices for the poor that grow signifi cantly faster

than the overall consumer price index in two of four provinces. Khan and Riskin (2001)

fi nd that the growth of the consumer price index for the poor is four percentage points

higher than that for the overall consumer price index for the period 1988 to 1995.

17. Riskin and Li (2001) use a national poverty line while defl ating incomes by provincial

price indices, which will produce an unpredictable bias in the change in the poverty

headcount.

18. Personal communication with China Centre of Preventive Medicine, Ministry of

Health.