Distribution of Poverty Funds between and within Poor Counties

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Having considered errors in designation of poor counties we now turn to

evidence on the allocation of the various poverty funds described above,

both between and within counties. Using the National Bureau of Statistics

county level data collected from the Rural Poverty Monitoring Survey in

a regression model, we test the extent to which county poverty funding

amounts from different sources for the period 1998–2001 can be explained

by county characteristics for the sample of poor counties where data exist.10

The variables used and the regression results are presented in Table 4.10.

The results suggest that, apart from investment from ‘other sources’,

poverty fund allocations across poor counties are significantly and

positively related to the level of poverty incidence, as measured by the

headcount ratio (the proportion of the poor in the total population). A

one percentage point increase in poverty incidence will increase the total

poverty fund allocation per capita by 0.76 yuan. For central government

funds the increase will be 0.85 yuan and for subsidized loans 0.46 yuan.

The size of the rural population has a signifi cantly negative impact on the

per capita allocation of all poverty funds, indicating that large counties are

at a disadvantage. Interestingly, although revolutionary base counties are

favored in poor county designation, they are discriminated against in fund

allocation between counties, as other things being equal, revolutionary base

counties receive 26 yuan per capita less than non-revolutionary counties.

Minority counties are still at an advantage, as they receive 14 yuan per capita

more than non-minority counties, again allowing for other factors. Inland

border counties are also favored in poverty fund allocation. Compared with

Table 4.10 Determinants of poverty fund allocation (1998–2001)

Independent Total poverty Central Other Subsidized Budgetary Food-forvariables

funds government funds loans funds work

funds

Poverty 0.76*** 0.85*** –0.16 0.46*** 0.18*** 0.21***

incidence (3.57) (5.34) (–0.41) (4.01) (4.17) (3.67)

Rural pop. –2.44*** –1.89*** –0.74*** –1.06*** –0.30*** –0.52***

(–18.29) (–18.84) (–3.03) (–14.63) (–11.24) (–14.56)

Revolutionary –25.83*** –26.07*** –5.70 –15.85*** –2.55 –7.68***

base (–3.02) (–4.05) (–0.37) (–3.40) (–1.48) (–3.32)

Minority 13.65* 9.75* 13.33 10.06** 0.85 –1.16

(1.84) (1.74) (0.98) (2.48) (0.57) (–0.57)

Border 66.96*** 45.27*** –16.68 16.87*** 13.21*** 15.19***

(6.24) (5.61) (–0.85) (2.89) (6.11) (5.23)

Highland 0.11 2.67 –4.81 1.44 0.58 0.65

(0.01) (0.38) (–0.28) (0.28) (0.31) (0.25)

Mountainous 6.64 9.66 4.46 2.51 2.55 4.60*

area (0.76) (1.47) (0.28) (0.53) (1.45) (1.95)

Year 3.18 7.82*** –7.47** 3.79*** 3.03*** 1.00*

(1.57) (5.12) (–2.01) (3.42) (7.40) (1.83)

Shanxi –27.53** –20.42** –6.50 –28.93*** 2.99 5.53

(–2.09) (–2.05) (–0.27) (–4.01) (1.12) (1.54)

Inner Mongolia –6.53 –12.01 –5.35 –24.95*** 4.38 8.56**

(–0.43) (–1.04) (–0.19) (–2.99) (1.42) (2.07)

Liaoning –56.69*** –54.87*** –13.07 –41.95*** –6.22 –6.70

(–2.86) (–3.66) (–0.36) (–3.86) (–1.55) (–1.24)

Jilin 49.52* 79.27*** 26.73 44.00*** 4.82 30.45***

(1.96) (4.15) (0.58) (3.18) (0.94) (4.43)

Heilongjiang 103.35*** 70.60*** 54.32 14.92 17.58*** 38.10***

(5.56) (5.06) (1.60) (1.48) (4.70) (7.59)

Anhui 143.74*** 115.36*** 37.44 59.85*** 17.98*** 37.54***

(7.29) (7.76) (1.04) (5.56) (4.52) (7.03)

Fujian 5.49 –39.03** 67.17* –31.91*** –7.50* 0.38

(0.26) (–2.41) (1.71) (–2.72) (–1.73) (0.07)

Jiangxi 37.09** 37.36*** 2.38 15.17 2.88 19.31***

(2.18) (2.90) (0.08) (1.63) 0.84 (4.17)

Shandong –10.45 –2.81 0.10 –4.12 0.37 0.93

(–0.53) (–0.19) (0.00) (–0.39) (0.10) (0.18)

Henan 53.63*** 52.53*** 12.99 27.08*** 9.43*** 16.02***

(3.93) (5.10) (0.52) (3.63) (3.41) (4.32)

Table 4.10 (continued)

Independent Total poverty Central Other Subsidized Budgetary Food-forvariables

funds government funds loans funds work

funds

Hubei 34.42** 34.28*** –6.27 20.51** 3.34 10.43**

(2.15) (2.84) (–0.21) (2.34) (1.03) (2.40)

Hunan 122.77*** 90.44*** 19.59 53.72*** 14.51*** 22.21***

(5.39) (5.26) (0.47) (4.32) (3.15) (3.60)

Guangxi 14.43 33.75*** –22.45 18.29** 5.52* 9.94**

(0.97) (3.00) (–0.82) (2.24) (1.83) (2.46)

Hainan –27.86 54.38*** –35.73 –1.71 10.26** 45.83***

(–1.10) (2.85) (–0.77) (–0.12) (2.01) (6.67)

Chongqing 65.01*** 56.85*** –3.13 24.58** 12.24*** 20.04***

(3.29) (3.82) (–0.09) (2.28) (3.07) (3.74)

Sichuan 163.53*** 152.04*** –15.40 91.14*** 21.49*** 39.41***

(9.85) (12.27) (–0.51) (10.16) (6.47) (8.85)

Guizhou 3.35 8.34 –15.79 8.10 –0.40 0.65

(0.25) (0.83) (–0.65) (1.11) (–0.15) (0.18)

Yunnan –11.93 –22.04 ** 38.48* –9.06 –5.77** –7.21**

(–0.98) (–2.40) (1.72) (–1.36) (–2.34) (–2.18)

Shaanxi 3.64 9.12 –4.69 11.70* –0.79 –1.78

(0.29) (0.96) (–0.20) (1.69) (–0.31) (–0.52)

Gansu 7.39 20.18** –10.29 1.06 16.40*** 2.72

(0.59) (2.15) (–0.45) (0.16) (6.53) (0.81)

Qinghai 211.25*** 215.78*** 6.26 162.21*** 7.71** 45.86***

(12.09) (16.34) (0.20) (16.96) (2.18) (9.66)

Ningxi 117.41*** 99.54*** 25.53 44.82*** 36.12*** 18.60***

(5.41) (6.07) (0.64) (3.77) (8.22) (3.15)

Xinjiang 25.151 79.18*** 3.22 8.46 23.15*** 47.58***

(1.55) (6.45) (0.11) (0.95) (7.04) (10.79)

No. of obs. 2121 2128 2128 2128 2128 2128

Adjusted R2 0.38 0.47 0.01 0.38 0.29 0.37

Notes:

*** signifi cant at 0.01 level.

** signifi cant at 0.05 level.

* signifi cant at 0.10 level.

Source: Calculated by the author.

counties on the plains, counties in highland and mountainous areas have

no special advantage in allocation.

Many provincial dummies have large and signifi cant coeffi cients, indicating

some provinces are at an advantage, while others are discriminated against.

Compared with counties in Hebei province, which is the reference point for

the analysis, those in Shanxi, Inner Mongolia, Liaoning, Fujian and Yunnan

are at a disadvantage, while those in Jilin, Heilongjiang, Anhui, Jiangxi,

Henan, Hubei, Hunan, Guangxi, Hainan, Chongqing, Sichuan, Gansu,

Qinghai, Ningxia and Xingjiang have an advantage. Qinghai has the most

favored treatment as its poor counties receive 211 yuan per capita more than

expected from the central government, after controlling for characteristics

like poverty incidence, population size and minority status.

The anomalies found here confirm the view that regional targeting

may be a rather ‘blunt instrument’ for reaching the poor (Ravallion and

Lipton, 1995). Even when funds are targeted at the poorest regions, there is

considerable leakage to the non-poor in poor regions and lack of coverage

of the poor in non-poor regions. Further, even between poor counties there

are important anomalies in the per capita allocation of funding. In PRC

political factors have strongly infl uenced poverty targeting from the outset.

Entrenchment of political interests to maintain poor county status has

made removal of poor county designation diffi cult, leading to a tendency

to expand coverage and increase leakage, thus widening targeting errors

over time. The evidence presented here suggests that political constraints

are likely to undermine regionally targeted programs, when targeting is at

the county level or higher.