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Income Growth, Inequality and Poverty

Reduction in Rural China

Luo Chuliang

Department of Economics, Beijing Normal University

[Abstract]: Economic growth and increasing inequality are both stylized features of

rural China during the period of economic transition, with both playing technically

opposing roles in poverty reduction. Using surveys conducted under the Chinese

Household Income Project Series in 1988, 1995, 2002, and 2007, this paper estimates

the elasticity of poverty reduction in rural China with respect to economic growth and

inequality. Using Shapley decomposition, we also discuss the effects of various

income components in the determination of poverty reduction and the elasticity of

poverty reduction to inequality for these income components.

[Key Words]: Economic Growth; Inequality; Poverty

JEL Classification: I32, I38, R28

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1. Introduction

In many developing countries, a reduction in poverty is almost always set as an

important goal for economic policy to achieve. China is no exception. At the end of

the 1970s, the incidence of poverty in rural China was as high as 31%, as officially

reported in NBS (2011). Poverty reduction has thus become an important incentive for

the implementation of reform and the strategy of China opening up and an important

aspect of evaluating such policies. Since the reform and opening-up policies were

executed, China has made great advances in poverty reduction. Rural poverty in

China has been reduced and the incidence of poverty has continuously declined over a

period of more than 30 years, falling to just 1.6% in 2007.1 However, some

researchers have argued that the official poverty line in China was too low and that

the incidence of poverty would therefore increase with a higher poverty standard.

However, Chen and Ravallion (2004) found that, even when a higher poverty line was

applied, poverty in rural China has still fallen dramatically.

It is widely accepted that the dramatic poverty reduction in rural China mainly

resulted from the rapid economic growth associated with the economic transition

initiated at the end of the 1970s. Not only has the development of the agriculture

sector and rural society as a whole increased the household income of rural residents,but economic growth in urban areas has continued to attract rural laborers migrating

from the countryside, thereby contributing to the household income of rural residents

through earnings from migration and nonfarm activities. All of these factors have

increased household income for rural residents and potentially reduced the incidence

of poverty2. For example, during the period from 1978 to 2008, per capita household

income in rural China increased from 133.6 Yuan to 4761 Yuan at an average annual

real growth rate of 7.15%. However, the process of economic transition also entailed a

rapid expansion in income inequality, a process usually considered unfavorable to

1 The differing interpretations of this trend arise from two main perspectives. First, the poverty standard was too

low and therefore it became relatively more influential with the growth of per capita income. Second, it ignored thedepth and intensity of poverty. Miao and Zhong (2006) conceded that although the incidence of poverty had beenin substantial decline during the past 20 years, the depth and intensity of poverty had worsened. In evidence, the

average income of those below the poverty line was even further away from the applied standard such that theywere worse off in relative terms.2There are different views about the impact of migrants on poverty reduction. For example, Du et al. (2005) and

Zhu (2006) argue that despite low-income workers having a strong incentive to leave, they disabled to overcome

the human capital and outgoing system obstacle. Consequently, they benefited less from migrants working. Thismeans that migrants can increase the income of rural residents, but may not be able to alleviate poverty effectively.

Alternatively, Yue and Luo (2008) conclude that the migration of rural residents and the length of time have a verysignificant impact on poverty alleviation. Lastly, Shi and Li (2007) estimated that a 1% increase in labor migration

led to a respective decline in the poverty rate of 0.24% and 0.4% before and after 1990.

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poverty alleviation. In evidence, between 1978 and 2007 the Gini coefficient

increased from 0.2124 to 0.3742, or some 0.54 percentage points per annum,

seemingly despite the high growth rate of mean household income. Accordingly,

while economic growth generally provides an opportunity for improving welfare, the

corresponding expansion in income inequality suggests that it may not benefit the

population equally. In particular, an expansion in income inequality always implies a

relative decline in income for at least the more impoverished parts of the population,

occasionally even in absolute terms. Therefore, economic growth with a

corresponding expansion in income inequality affects poverty both positively and

negatively.

This paper aims to explore the following questions. First, is it possible to

evaluate separately the effects of income growth and inequality on the reduction in

poverty? Second, in the situation where the population as a whole benefits from equal

economic growth, can we obtain a better reduction in poverty? Finally, is it possible to

decompose the income growth and inequality effects on the reduction in poverty into

their income components? The remainder of the paper is structured as follows.

Section 2 reviews the related literature, including the growthdistributionpoverty

triangle described by Bourguignon (2003), on the growth and inequality effects in

poverty reduction in China. Section 3 describes the recent changes in growth,

inequality and poverty in China. Section 4 decomposes the income growth and

inequality effects on the reduction in poverty and Section 5 further decomposes these

effects into their income components. Section 6 concludes the paper.

2. Literature review

(1) Growth effect and distribution effect on poverty reduction

Economic growth and the income distribution determine the reduction in poverty

reduction, as depicted in Figure 1, following Bourguignon (2003). However, while

growth and inequality directly affect the reduction in poverty, they do so in opposite

directions. Accordingly, we can consider poverty reduction as a function of income

growth, income distribution and their change. It is then obvious that an economic

growth process with a more equal income distribution will contribute better to the

reduction in poverty than growth with an expansion in income inequality. However,

during the economic growth process, the development strategy necessarily determines

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the change in the income distribution.

Figure1: The growthdistributionpoverty triangular relationshipSource: Bourguignon (2003).

Figure 2: The impact of economic growth and the income distribution on povertySource: Bourguignon (2003).

Figure 2 depicts the direct impact of economic growth and the income

distribution on poverty. In Figure 2, the income distribution in the shaded area to the

left of the poverty line indicates the incidence of poverty. A rightward movement in

the income distribution then captures economic growth, a process that will reduce the

proportion of the population under the poverty line. If accompanied by a narrowing of

the income gap, i.e. the new income distribution curve moves up relative to the curve

after translation and the concentration of income distribution becomes higher and the

degree of dispersion becomes lower, the incidence of poverty will decline further.

This indicates that a change in the income distribution will also affect the measures of

poverty. Therefore, Figures 1 and 2 intuitively indicate that economic growth and the

income gap determine the level and change in poverty. This correspondingly implies

that the pattern of economic growth, along with the economic growth rate, determine

Absolute poverty and reduction

Economic development strategy

Income distribution change Income growth

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the process of poverty alleviation.

The interaction between economic growth and the income distribution also

determines poverty reduction. These indirect effects also always influence poverty

reduction policy. While there are two opposing opinions on the relation between

economic growth and income distribution, the well-known Kuznets hypothesis

suggests that the inequality in economic growth likely increases during the initial

stage of industrialization and then gradually decreases, an outcome commonly

debated among economists and tested by researchers. This leads to the ongoing

discussion about whether income inequality is good or harmful for economic growth.

According to the Kuznets hypothesis, most developing countries are more likely to be

in the expansion stage of the income distribution during the process of economic

growth. In other words, most developing countries will inevitably pursue economic

growth at the expense of expanding the income distribution. Based on this idea, some

economists particularly emphasize the role of economic growth on the alleviation of

poverty. Consequently, they consider that distribution (or more precisely,

redistribution) policies concerning household income have only minor effects on

poverty alleviation. In this model, it is then crucial to enhance economic growth to

achieve a reduction in poverty.

Given the evidence on the Kuznets hypothesis is ambiguous, especially as some

developing economies, such as Japan, South Korea, Taiwan and Thailand,

experienced rapid economic growth alongside a more equal income distribution

during some periods, some studies have argued that the income distribution during the

period of economic growth mainly depends on a particular growth pattern (Li and Luo,

2008). Although economic growth remains important for poverty alleviation, the

growth effect is likely to be offset by the expansion of the income distribution. This

means that economies with similar growth rates may achieve poverty alleviation

differently because of differences in the distribution of income. In most cases,

economic growth will reduce poverty absolutely (Karry, 2004). However, the relative

benefit of the poor may not increase. The expectation is that if economic growth can

take place in a relatively balanced manner for each income group, poverty will reduce

significantly at the same economic growth rate. Some studies emphasize that changes

in the income distribution during the growth process are also crucial for poverty

alleviation. For the most part, poverty reduction by means of the pattern of economic

growth has attracted increasing attention in the literature, the typical approach being

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to decompose the actual process of economic growth into two counterfactual

processes, namely, economic growth with a constant income distribution and changes

in the income distribution in the absence of economic growth.

Table 1: Pro- and anti-poor outcomes arising from economic growth by countryPositive growth Negative growth

Pro-poor Anti-poor Total Pro-poor Anti-poor Total

Low-income countries 20.8 33.3 54.2 27.8 18.1 45.8

Low middle-income countries 26.7 31.4 58.1 19.0 22.9 41.9Upper middle-income countries 21.7 35.0 56.7 21.7 21.7 43.3Heavily indebted countries 18.6 27.1 45.8 32.2 22.0 54.2East Asia and the Pacific 17.1 57.1 74.3 17.1 8.6 25.7

East Europe and Central Asia 12.3 21.1 33.3 21.1 45.6 66.7Latin America and the Caribbean 30.4 29.1 59.5 24.1 16.5 40.5Middle East and North Africa 35.7 14.3 50.0 28.6 21.4 50.0South Asia 29.4 52.9 82.4 11.8 5.9 17.6

Sub-Saharan Africa 20.0 14.3 54.3 31.4 14.3 45.7

All countries 23.2 32.1 55.3 22.4 22.4 44.7Source: Son and Kakwani (2008).

The key question is whether the poor benefit from economic growth or is

economic growth pro-poor. Many studies have sought an answer to this question and,

of course, obtain diverse results (Kakwani and Pernia, 2000; Ravallion and Chen,

2003; Son, 2004), not least because there is no consensus on the ideology and

methodology underpinning pro-poor growth. For example, Dollar and Kraay (2002)

found that economic growth will benefit all, including the poor, and therefore

government intervention policies cannot affect the income share of the poor. On this

basis, economic growth is the key to an antipoverty policy. Conversely, Kakwani and

Pernia (2000) concluded that although economic growth is important in poverty

alleviation, economic growth does not benefit the poor naturally and so income

redistribution plays a very important role in poverty reduction along with economic

growth. Son and Kakwani (2008) likewise emphasized that pro-poor growth only took

place when the poor benefit relatively more. To gain some insight into this debate,

Table 1 details the pro-poorness of economic growth for 237 periods in 80 countries

during 19842001. In the sample, 55.3% (44.7%) of cases exhibit positive (negative)

growth. Of the 55.3% of cases with positive economic growth, cases where the poor

benefit more (less) account for 23.2% (32.1%) of the total. In contrast, the proportions

of pro- and anti-poor outcomes are almost equal during periods of negative growth.

This distribution indicates that economic growth does not always necessarily benefit

the poor.

(2) Growth and inequality effects on poverty reduction in rural China in

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existing studies

Economic growth and the expansion of the income distribution have been two

fundamental features of the Chinese economy since the end of the 1970s. Numerous

studies have already discussed the effects on poverty. For instance, Wei and

Gustafsson (1999) conducted a decomposition based on Datt and Ravallion (1992) to

identify the impact of the growth and inequality effects on the reduction in poverty in

rural China. The conclusions obtained from this and related studies are typically

consistent, showing that economic growth substantially reduced poverty while the

growth effect offset at least to some extent the widening income distribution.

In other work, Lin (2003) calculated a pro-poor index for rural China. The results

showed that all of the pro-poor indexes were positive but less than unity in the periods

19851990, 19901995 and 19952001. This suggested that the Chinese rural poor

benefited from economic growth through the diffusion effect. Elsewhere, Yao et al.

(2004) found that widening the income gap hindered the process of poverty

alleviation because poverty was more elastic with respect to the income gap.

Assuming a certain income distribution1, Hu et al. (2005, 2007) calculated inequality

measures and poverty indicators based on grouped income data and discussed the

impact of economic growth and changes in inequality on poverty. They found that the

poor benefit less than the rich do from economic growth in rural China. Likewise,

Chen (2009) re-estimated the Gini coefficient and poverty indicators for Chinas rural

areas and found significant volatility and inconsistency in the process of poverty

reduction. Based on the decomposition of poverty changes, Chen (2009) found that

the incidence of poverty decreased by 39.13% because of economic growth during the

period 19802005, though a corresponding deterioration in the income distribution

offset this by 18.15%. Moreover, Wen (2006) found that the elasticity of poverty

reduction with respect to economic growth displayed some regional differences using

provincial data on economic growth and poverty from 1993 to 2004.

Using a micro-level household survey, Chen and Wang (2001) examined changes

in Chinese poverty during the 1990s and found that economic growth reduced the

poverty rate significantly. However, growing income inequality increased the poverty

rate and the poor therefore benefited less from economic growth. Using data from the

Chinese Health and Nutrition Survey (CHNS) and household surveys conducted by

1 The research ideas in Hu et al. (2005, 2007) are identical to Lin (2003). The conclusions are also very consistent,

with any differences reflected mainly in the inspection period.

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the rural research center in the Chinese Rural Ministry, Wan and Zhang (2006) found

that income growth and the decline in inequality led to an alleviation in poverty in the

first half of the 1990s. However, the slow growth of rural resident income and the

widening income gap led the reduction in poverty to slow, and in some years of the

late 1990s, even increase. Du and Sun (2009) found that there were some differences

in the economic growth and income distribution effects for poverty reduction in

different stages of economic development. In sum, although income distribution

effects partly offset the poverty reduction effects of economic growth, poverty

decreased overall during 19911993 and 19972000. However, poverty increased

during 19931997 because the (negative) income distribution effects were larger than

the (positive) economic growth effects. During the period 20002004, both economic

growth and the income distribution served to reduce poverty. However, Du and Sun

(2009) did not distinguish between the poverty effects in urban and rural areas in their

discussion.

3. Background: Trends in growth, inequality and poverty

(1)Income growth, income distribution and the characteristics of poverty change

Overall, China has experienced rapid economic growth and expansion in the

income distribution since reform and the process of opening up. Figure 3 depicts the

changes in household net income per capita in rural China, an index of GDP per

capita1, Gini coefficients for rural areas2 and measures of the incidence of poverty. As

shown, household income and GDP per capita in rural China rapidly and steadily

increased during the period since 1978. The Gini coefficients for rural China also

steadily increased. Eventually, the upward trend eased and remained stable in a state

of greater inequality after 2000. As also shown, the incidence of poverty in rural

China has consistently declined, with a downward trend particularly evident before

the mid-1990s. Since the late 1990s, the incidence of poverty continued on a

downward trend, but the rate of decline has reduced significantly.

It is worth noting the interrelationship between the real growth of household net

1 The main purpose for using both a per capita net income index and a GDP per capita index is to eliminate theimpact of price factors. For both indicators, the base year is 1978 = 100.2A more reasonable indicator measuring the national income gap would be the national Gini coefficient.

Unfortunately, there is no official data available for this indicator. Other sources of national Gini coefficients aremore sporadic and it is difficult to confirm the consistency across different years. However, it is not difficult to

infer that the absolute value of the national Gini coefficient will be larger than the rural Gini coefficient and theupward trend will become more apparent. This is because the income gap between urban and rural areas is

expanding and the income gap in urban areas is rising.

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income per capita in rural China and GDP per capita. Before 1994, the index of

household net income per capita in rural China was higher than that of GDP per capita,

meaning that the real growth rate of household net income in rural China was higher

than that of GDP per capita. Thereafter, the real income growth rate was lower than

the growth rate of GDP per capita and the gap was widening, thereby indicating an

inconsistency between household income growth in rural China and GDP growth.

Figure 4 details the growth effect on the reduction in poverty from household net

income and GDP per capita growth.

0

5

10

15

20

2530

35

40

0

200

400

600

800

1000

1200

1978 1982 1986 1990 1994 1998 2002 2006

%real index,1978=100

real income per capita in rural (1978=100)real GDP per capita (1978=100)Gini coefficients within rural (%)

poverty ratio (%) Figure 3: Economic growth, income gap and poverty changeSources: Per capita net income index and GDP per capita from China Statistics Yearbooks; Gini coefficient from

the China Rural Household Survey Yearbook (2007) and Li et al. (1999); poverty rate from the 2008 povertymonitoring report for China.

To measure the relationship between the change in the rural poverty rate and

economic growth, Figure 4 plots calculations of the growth effect on poverty changes1,

using the index of household net income per capita in rural China and GDP per capita

as indicators of economic growth, respectively. The formula is:

ln() ln(1)ln() ln(1) ,

Where Povertt is the incidence of poverty in year t, is either the index ofhousehold net income for rural China or GDP per capita index, also in year t, and

1 We did not calculate the income distribution effects of changes of poverty rate following in a similar way.Without controlling for growth effects, calculating the distribution effects of poverty changes in this waywill lead

to misunderstanding.

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ln() is the natural logarithm. Problematically, this calculation does not control forthe effects of changes in the income distribution. Therefore, the result gives the

overall economic growth effect to poverty change, rather than the growth effect based

on the counterfactual assumption (income distribution unchanged).

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

19791981198319851987198919911993199519971999200120032005200

income per capita in rural GDP per capita

Figure 4: Effect of economic growth on poverty changeSource: Authors calculations using data underlying Figure 3.

As shown in Figure 4, economic growth leads to poverty alleviation in nearly all

years. The two curves are usually below the horizontal axis, no matter whether we

employ household net income per capita in rural China or GDP per capita as the

measure of economic growth. In this figure, the further an observation is away from

the horizontal axis, the greater impact of economic growth on the change in poverty.

Consequently, Figure 4 indicates that the elasticity of poverty alleviation with respect

to economic growth is unstable with strong volatility1.

(2) Uneven income growth

The growth effect on poverty reduction mainly results from the uneven growth at

various income levels. Table 2 reports income and its growth rate by quintiles from

2000 to 2007. As shown in Table 2, although per capita household net incomes for all

quintiles grow at a positive rate, the growth rates for the low quintiles were generally

lower. For instance, the income growth rate for the top quintile was about 2

percentage points higher than that of the bottom quintile during the period from 2000

1 The conclusion based on the macro data differs from that obtained from the micro-level household data. Most of

the studies based on the micro data suggest that the poverty alleviation elasticity of economic growth is declining.This may relate to the timing of the household surveys. Later sections of this paper discuss this issue further using

household data.

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to 2007. The annual income growth rate on average for the bottom quintile was 7.69%

during this period, compared with 9.49% for the top quintile. Consequently, the ratio

of the top income quintile to the bottom quintile rose from 6.47 in 2000 to 7.27 in

2007, and in 2003 even exceeded 7.33, the highest ratio recorded during this period.

Table2: Annual household net income per capita by quintile

Bottom 20% Second 20% Third 20% Fourth 20% Top 20%

Top 20%

bottom20%

2000 802 1440 2004 2767 5190 6.47

2001 818 1491 2081 2891 5534 6.77

2002 857 1548 2164 3031 5903 6.89

2003 866 1607 2273 3207 6347 7.33

2004 1007 1842 2579 3608 6931 6.88

2005 1067 2018 2851 4003 7747 7.26

2006 1182 2222 3149 4447 8475 7.17

2007 1347 2582 3659 5130 9791 7.27

Average growthrate(%)

7.69 8.70 8.98 9.22 9.49

Sources: Per capita income level from China Statistics Abstract (2006); China Statistics Yearbook (2007, 2008);

authors calculations.

(3)Income growth of poor and non-poor

The uneven income growth found during this period in rural China may

potentially hinder welfare improvements for the poor. Although the majority of

existing studies suggest the incidence of poverty has steadily fallen since the end of

the 1970s, as shown in Table 3, both household net income and wage income per

capita of the poor increased extremely slowly between 2000 and 2007. In fact, the

household net income per capita of the poor increased from only 515 to 652.6 Yuan,

which is almost negligible in both absolute and relative terms, whereas the household

net income per capita of the national household nearly doubled, from 2,253 to 4,140

Yuan. The basic account is the same for wage income growth, with the relatively

slower growth rate implying a relative deterioration in poor households1. The ratio of

poor households with national average income showed a declining trend during the

period from 2000 to 2007, with the ratio of household net income per capita

decreasing 7 percentage points, from 22.86% in 2000 to 15.76% in 2007.

Although the ratio of wage income per capita experienced a slight rebound in

2006, it nonetheless decreased from 15.08% in 2000 to just 11.29% in 2007. The

different growth rates for poor households and all households indicate that the welfare

improvement of the poor was significantly lower than the average in rural areas

1 Some studies suggest that although the incidence of poverty was declining, the depth and strength of poverty

continued to deepen (Miao and Zhong, 2006).

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where subscript r denotes the reference group. The first term on the right-hand side of

equation (1) is the growth effect on poverty change and the second term is the

distribution effect. The final term on the right-hand side is the residual. This

decomposition form is sometimes subject to criticism on two grounds. The first is that

the growth effect and the distribution effect depend on the choice of the reference

group. The second is that the decomposition is not complete as it includes an

(unexplained) residual term. According to the Shapley decomposition rule, we can

decompose the change in poverty across the two periods as follows:

=

2

1

= 0.52, 11,1+ 2, 21, 2+ 0.51, 21, 1+ 2, 22, 1, (2)

where equation (2) includes both of the time points in the reference group and obtains

the average. Therefore, it can obtain the full decomposition form. Once again, the firstterm on the right-hand side of equation (2) provides the growth effect, while the

second term yields the distribution effect. As a result, equation (2) has overcome the

reference group problem found in equation (1).

Although the decomposition of (1) and (2) provides the contributions of

economic growth and income distribution to poverty change, they are not sufficient to

reflect the impact of the pattern of economic growth on the reduction in poverty. For

instance, changes in the income distribution may result from differences in the

location of the income distribution. For example, a1 percent increase in the Gini

coefficient could result from income growth for persons in high-income groups, an

income decrease for persons in low-income groups or from changes in income in

middle- income groups. However, different forms of change clearly have different

effects on poverty. The distributional changes thus indicate whether the changes for

different groups during the process of economic growth are pro- or anti-poor. In

response, studies have begun to discuss the pro-poorness of growth, of which there is

a voluminous literature. Perhaps the only consensus in this literature is in the

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conceptual framework. Elsewhere, there is considerable disagreement, especially on

the measure of pro-poorness, comprising the indexes in Kakwani and Pernia (2000)

and Ravallion and Chen (2003) and the poverty equivalent growth rate (PEGR) index.

Kakwani and Pernia decomposed the change in the poverty indicator in the two

periods into the growth effect and distribution effect. Let the change in poverty be

= 2 1. As in equation (2), we can decompose the overall change in thepoverty rate into:

= 0.5ln2, 1 ln1,1+ ln2,2 ln1,2+ 0.5ln1, 2 ln1,1+ ln2,2 ln2, 1 = + .

Kakwani and Pernia (2000) defined = / as the pro-poorness index. In thecase of a positive growth rate, >1 indicates that growth is pro-poor, < 0suggeststhat growth is harmful for the poor, and 0 < < 1 means that the poor benefit fromthe trickle-down effect of economic growth, but the benefit is lower than for the

non-poor population. In Kakwani and Pernias (2000) opinion, we cannot consider the

most recent growth episode in China as pro-poor. Using this pro-poor index, Kakwaniet al. (2003) proposed the PEGR index to adjust the economic growth rate with the

pro-poor index, such thatPEGR = e. Improving the PEGRtherefore requires not only rapid economic growth, but also improvement in the

pro-poor index. Put differently, economic growth only benefits the poor when the

PEGR index is greater than the economic growth rate.

Ravallion and Chen (2003) proposed a different index to measure the

pro-poorness of economic growth as follows:

1

(0, 1) ln(, ) ln( 1,)(0,1)

0

.

In this index, growth is pro-poorness if the income growth rate of the poor population

is higher than the income growth rate of the whole society.

We should note that the three different pro-poor indicators arise from two very

different ideas concerning the alleviation of poverty. In general, the Kakwani and

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Pernia (2000) index and the PEGR index emphasize the role of income change in the

process of economic growth, and a decrease in the income gap is then the premise for

being pro-poor in the process of economic growth. However, the Ravallion and Chen

(2000) index places rather more emphasis on the rate of increase in income of the

low-income population and is more biased toward the poverty reduction effect of the

change in the income distribution. There is then often inconsistency in the conclusions

arising from these dissimilar principles concerning the alleviation of poverty.

Another method that measures the impact of economic growth on poverty is the

growth elasticity of poverty change. The definition of an increase in the elasticity of

poverty in this paper is then that the extent poverty will change if income increases 1

percent for all groups based on the existing income distribution. If the income of i is

,and income increases1 percent, then = (1 +1 % ). If the Lorenz curve doesnot change, the growth elasticity of poverty is:

= (), (), (), . (3)

Similarly, if the income of i is

and the change is

=

+ 1 % (

(

)),

average income does not change. However, the Gini coefficient will increase 1

percent. The change in poverty is then the distribution elasticity of poverty:

= , ,, ,, , . (4)

To discuss the contribution of itemized income, Duclos and Araar (2006)

decomposed the poverty index according to the sources of income based on the

Shapley decomposition. All of the income components amounts are zero at the

beginning of the decomposition process. At this time, the poverty index is one and the

index will decrease if we increase the amount of income components. Finally,

following Shapley decomposition, we average the various possible impacts. In

addition, Araar and Duclos (2007) decompose the distribution elasticity caused by

inequality according to the source of income. Similar to the change in total income, if

the change in is = + 1 % ( ()), it will affect both inequality and

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poverty at the same time. Araar and Duclos (2007) defined the elasticity of inequality

by income component as the ratio of the change in the poverty rate and the inequality

indicators.

(2)Description on household data

The data used in this paper are from the rural survey waves of the China

Household Income Project (CHIP) conducted in 1988, 1995, 2002 and 2007. The

samples are from the regular annual household survey by the National Bureau of

Statistics. Table 4 details the sampling sizes. As shown, the 1988 survey covered the

most provinces, while the sample of households and individuals is greatest in 2007, as

are the number of counties involved in the survey. Riskin and Kahn (1999) provide a

detailed description of the survey conducted in 1988 and 1995, while Li et al. (2008)

detail the sample structure and sampling methods of the 1995 and 2002 surveys. The

procedure for the 2007 survey is generally similar to the previous surveys, except that

it did not specifically include household income questions. All of the data for

household income are from the annual household survey of the National Bureau of

Statistics. To maintain consistency in the income measures, we also used household

net income from the National Bureau of Statistics for the surveys conducted in 1988,

1995 and 2002.

Table 4: Sample size1988 1995 2002 2007

# of individuals 51,352 34,739 37,969 51,847# of households 10,258 7,998 9,200 1,300

# of provinces 28 19 22 16

Table 5 describes income and income inequality for each survey year. As shown,

household net income per capita increased significantly from 1988 to 2007. Adjusting

for inflation, household net income per capita increased in real 1988 terms by 33% in

1995, doubled in 2002, and more than tripled in 2007. The income gap also changes

with the growth of per capita income. The most prominent change is that some

indicators that measure the inequality reached their highest point in 1995. For

example, the Gini coefficient was 0.3811 in 1995 and 0.376 in 2007. The change of

1 According to the China Rural Household Survey Yearbook, the Gini coefficient for rural households in 1995 wasup to 0.3415. It did not exceed this peak again until 2000. The Gini coefficient was 0.3536 in 2000 and kept rising

thereafter. The Gini coefficient calculated by Ravallion and Chen (2003) was 0.3398 in 1995. According to theresults of the National Bureau of Statistics, the Gini coefficients were 0.3000, 0.3415, 0.3646 and 0.3742,

respectively, in the sample years in this analysis. Although we employ data from the National Bureau of Statistics,

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income growth and distribution potentially exert an important impact on rural poverty.

Table 5: Income and income inequality1988 1995 2002 2007

Net household income per capita 534 711 1,089 1,670

relative (1988=100) 100 133 204 313

Inequality measures 0.737 0.847 0.835 0.851Gini 0.332 0.381 0.367 0.376

MLD (mean log of deviation) 0.404 0.292 0.237 0.286

Theil 0.204 0.259 0.243 0.253Highest/lowest 11.32 14.06 11.16 12.65

0

1

2

3

4

5

67

8

9

10

1 2 3 4 5 6 7 8 9 10

1988-1995 1995-2002 2002-2007

Figure 5: Average annual real income growth by income groupNotes: The horizontal axis is the income decile. The vertical axis is the actual annual income growth rate. Theformula used for calculating the annual real growth rate is yt/y0t 1.

Figure 5 plots the annual real income growth of all income deciles, which we can

take as a kind of growth incidence curve, to illustrate how those in the various income

deciles benefit from economic growth. During the period from 1988 to 1995, the

growth rate of almost all income deciles increased with the exception of the bottom

decile. In other words, high-income groups experienced a higher income growth rate.

This trend was similar to the period from 2002 to 2007. In contrast, the income

growth rate in the middle-income deciles was not as strong as during the period from

1988 to 1995. For the most part, income growth was more even during the period

from 2002 to 2007. The common characteristic of the growth curves for these two

periods is that the income growth rate was higher for the high-income deciles. The

shape of the growth incidence curve completely differed during the period from 1995

to 2002 where the income growth rate of the low-income deciles was higher than for

the Gini coefficients in 1988 and 1995 are still different from the official results. However, the results for 2002 and

2007 are very close.

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the high-income deciles. Figure 5 then clearly illustrates that the distributional

characteristics of the relative income growth rate vary by income decile and period.

We use two poverty lines to identify the poor. The first is the official poverty line,

which was 236 Yuan in 1988; the second is the international poverty standard in one

dollar per day, which amounted to 518 Yuan in 1988, assuming purchasing power

parity between RMB and USD in 2005. The FGT index (Foster, Greer and Thorbecke,

1984) is used to measure poverty,

() = 1

=1

where N is the total population, q is the poverty population, z and are therespective poverty and income of individual i, and is the gap between

personal income and the poverty line. The sum is only limited to the population whose

income is lower than the poverty line. The parameter is the poverty aversioncoefficient. The larger is , the higher is the level of poverty aversion. This will alsogive more weight to an extremely poor population and be more sensitive to the

income distribution of the poor. Finally, FGT(0) is poverty incidence, FGT(1) is the

poverty gap and FGT(2) is the weighted poverty gap.

Table 6: Poverty measures by year

1 USD/day (518 Yuan in 1988) National poverty line (236 Yuan in 1988)

FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2)

1988 59.62 21.94 11.57 12.89 5.07 3.51

1995 45.27 16.43 8.57 10.71 3.81 2.04

2002 20.87 6.11 2.70 2.72 0.82 0.44

2007 9.11 2.83 1.45 1.48 0.71 0.54

Table 6 reports the poverty measures. As shown, according to the official poverty

line, the poverty incidence decreased 2 percentage points, from 12.89% in 1988 to

10.71% in 1995. In the second seven-year period from 1995 to 2002, the poverty rate

decreased about 8 percentage points. According to the poverty line of 1USD/day, the

poverty rate was nearly 60% in 1988, decreasing to 45% in 1995. It thus decreased by

15% in seven years and further decreased by nearly 25% between 1995 and 2002. The

poverty rate stood at nearly 9.11% in 2007. Together, these results indicate that

poverty has significantly reduced and that this downward trend in the poverty rate ismore obvious when using a higher poverty standard. With the increase of in the

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FGT index, equaling the increasing weight of the low-income population, the

downward trend of poverty will diminish. The changes in the poverty line and the

poverty aversion coefficient in the FGT index indicate that a person who is poorer

obtains less benefit during the process of economic growth.

Using a different poverty standard, Table 7displays the income and income

growth rate of poor households and non-poor households at different periods. It is not

difficult to discern that the gap in income per capita of poor and non-poor households

expands regardless of the measure of poverty used. The ratio of income per capita of

poor to non-poor households declined nearly 20% from 39.02% in 1998 to 19.81% in

2007 according to the poverty line of one US dollar per day. According to the national

poverty line, it declined 17% from 24.2% in 1988 to 7.27% in 2007. Moreover,

although the incidence of poverty was declining, the mean income of the poor

population was not significantly improved.

Table 7: Income and income growth of poor and non-poor households

1 USD/day National poverty line

TotalNon-poor Poor

Poor/Non-

poor (%)Non-poor Poor

Poor/Non-

poor (%)

Average real income

(Yuan)

1988 838.97 327.38 39.02 591.79 143.19 24.20 533.98

1995 1025.62 329.98 32.17 777.70 151.92 19.53 710.69

2002 1279.03 366.47 28.65 1114.41 164.75 14.78 1088.57

2007 1801.69 356.95 19.81 1693.31 123.03 7.27 1670.11

Annual growth rate (%)

19881995 2.91 0.11 3.98 0.85 4.17

19952002 3.20 1.51 5.27 1.16 6.28

20022007 7.09 -0.52 8.73 -5.67 8.94

Source: Authors calculations based on the household survey data for 1988, 1995, 2002 and 2007.

Note: Nominal income converted to 1988 level using CPI index.

5. Decomposition of poverty changes: Growth and inequality effect

(1) Growth effect and inequality effect on poverty changes

Based on the previous discussion, there are two fundamental features of the

recent poverty changes in rural China: (1) rural poverty has decreased significantly

during the process of economic growth; (2) income growth is uneven across income

groups. That is, the income growth of poor households is relatively slower and the

relative income of the poor population continues to decline.

Table 8 reports the growth and inequality effects on poverty reduction using the

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Datt-Ravallion (D-R) and Shapley decomposition, respectively. The D-R

decomposition always uses the mean income and income distribution in the previous

year as the reference group for identifying the growth and inequality effects on the

poverty reduction. Economic growth always has a positive effect on poverty reduction,

so that the growth effect always has a negative sign for poverty changes. However, the

changes in the income distribution usually have the opposite effect. According to the

poverty standard of 1 USD/day, if the income distribution was unchanged, the income

growth of rural residents leads to a decrease in the poverty rate by 21.57% or 19.37%

between 1988 and 1995. Instead, if there is no income growth, the distribution effect

caused by a widening of the income gap will make the incidence of poverty increase

by 2.82% or 5.02% between 1988 and 1995. The adverse effect of the distribution

effect on poverty alleviation becomes more evident if we choose a lower poverty

standard.

Table 8: decomposition of poverty changes (%)

1 USD/day National poverty line (236 Yuan in1988)

FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2)

DR Shapley DR Shapley DR Shapley DR Shapley DR Shapley DR Shapley

19881995

Growth effect -21.57 -19.37 -9.02 -9.23 -4.63 -5.11 -6.21 -6.98 -1.51 -2.09 -0.59 -0.97

Inequality effect 2.82 5.02 3.94 3.73 2.60 2.11 5.56 4.80 1.42 0.84 -0.12 -0.50Residual 4.41 -0.42 -0.97 1.53 -1.16 -0.77

19952002

Growth effect -23.68 -23.48 -8.98 -9.11 -4.68 -4.68 -5.67 -5.98 -2.06 -1.83 -1.04 -0.84

Inequality effect -0.72 -0.92 -1.08 -1.22 -1.18 -1.18 -1.69 -2.00 -1.40 -1.17 -0.95 0.76

Residual -0.40 -0.27 0.00 -0.63 0.47 0.39

20022007

Growth effect -13.53 -13.36 -4.10 -4.21 -1.78 -1.91 -1.82 -2.11 -0.44 -0.53 -0.20 -0.23

Inequality effect 1.42 1.60 1.04 0.93 0.78 0.65 1.15 0.86 0.50 0.42 0.37 0.33

Residual 0.35 -0.22 -0.25 -0.58 -0.18 -0.07

According to the official poverty standard, the growth effect will make the

poverty rate decrease by 6.21% or 6.98% between 1988 and 1995, whereas the

distribution effect will make the poverty rate increase by 5.56% or 4.8% between

1988 and 1995. The deterioration in the income distribution thereby offsets most of

the poverty alleviation effect of economic growth in some cases. The decomposition

results based on the other poverty measures are similar. It is noteworthy that the

change in the income distribution has a positive effect on the decline in the weighted

poverty gap in accordance with the national poverty line. Note, however, that the case

was somewhat special during the period from 1995 to 2002. As reported in Table 5,

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both the decline in income growth and the Gini coefficient occurred during the same

period according to the two surveys. However, the poverty reduction through the

distribution effect was relatively low.

The determinants of poverty reduction during the period from 2002 to 2007 were

similar to those from 1988 to 1995. The change in the income distribution was also

not conducive to poverty alleviation. In absolute terms, the adverse effect of the

income distribution on poverty alleviation has declined to a great degree. In relative

terms, the adverse effect of the income distribution on poverty alleviation even

exceeded the magnitude of the positive effect from economic growth in the decline in

the poverty gap and the weighted poverty gap according to the national poverty

standard. Comparing these three stages, we can also see that the poverty alleviation

from economic growth, i.e. the growth effect on the reduction in poverty, became

increasingly smaller in accordance with the official poverty line. In the Shapley

decomposition, for instance, the incidence of poverty declined by 6.98 percentage

points through the growth effect between 1988 and 1995, but only by 2.11 percentage

points between 2002 and 2007. So on the one hand, the growth effect on poverty

reduction declined for the poorest part of the population; on the other hand, the

poverty reduction further worsened through the deterioration of the income

distribution.

The growth effects and inequality effects on poverty reduction reported in Table

8 were from the changes in the poverty measures, economic growth and changes in

income distribution. In contrast, the growth elasticity and distribution elasticity on

poverty reduction shown in Table 9 are from simulations based on the income

distribution in the current years. Therefore, the growth elasticity and distribution

elasticity illustrate the potential changes in the poverty measures under the condition

of the current income distribution.

Table 9: Growth elasticity and distribution elasticity of poverty changes

1 USD/day National poverty line

FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2)

G D G D G D G D G D G D

1988 -2.39 3.02 -1.54 4.21 -0.89 5.65 -1.29 0.04 -1.72 1.08 -1.79 2.12

1995 -1.90 3.82 -1.81 6.65 -1.75 9.54 -1.39 0.52 -1.75 2.02 -1.84 3.43

2002 -2.86 10.33 -2.31 12.97 -1.74 15.51 -2.06 2.27 -2.42 4.77 -2.52 6.98

2007 -2.16 13.12 -1.09 13.69 -0.62 17.95 -2.18 4.86 -2.22 8.15 -1.91 10.70

Notes: G and D denote growth and distribution elasticity, respectively.

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The most obvious change in Table 9 is the sharp increase in the distributional

elasticity of poverty change from 2002 to 2007, especially a lower poverty line or a

higher poverty aversion coefficient being set. For a given poverty line, the distribution

elasticity rises with the increase in the poverty aversion coefficient in any year. The

poverty incidence under the poverty standard of one USD/day will increase 0.04% if

the Gini coefficient increases by 1 percentage point. The poverty gap will increase

1.08% and the weighted poverty gap will increase 2.12%. When the Gini coefficient

increases by1 percentage point, the poverty rate, the poverty gap and the weighted

poverty gap increase by 3.02%, 4.21% and 5.655%, respectively, under the national

poverty line. The distribution elasticity of poverty change gradually increased during

these four years. Under the poverty standard of one US dollar per day, the poverty rate,

the poverty gap and the weighted poverty gap increase by 4.86%, 8.15% and 10.7%,

respectively, in 2007. According to the national poverty line, the three indicators

increase by 13.12%, 13.69% and 17.95%, respectively. The distribution elasticity of

poverty is then much larger than the growth elasticity.

The sign of the growth elasticity is always negative, indicating that economic

growth always leads to a decrease in poverty. Nevertheless, it does not exhibit any

dynamic trend as for the distribution elasticity. According to the national poverty line,

the absolute value of growth elasticity on poverty alleviation declines with the

increase in the poverty aversion coefficient in any year. The economic growth effect

on poverty reduction gradually declines with a higher degree of poverty aversion. The

growth elasticity on poverty alleviation was lowest in 1995, whereby a 1 percent

increase in the income of rural residents led to a decrease of 1.9 percentage points in

the poverty rate. The growth elasticity on poverty alleviation was highest in 2002,

whereby a 1 percent increase in the income of rural residents led to a 2.86% decrease

in the poverty rate. According to the poverty standard of one US dollar per day,

growth elasticity measured by the poverty rate gradually increased during these four

years. When the distribution characteristics remained unchanged, the 1 percent

increase in income led to a 2.18% decrease in the poverty rate; it was only 1.29% in

1988. The change of distribution elasticity and growth elasticity indicates that

inequality of income distribution increasingly becomes an obstacle to poverty

alleviation. For the deeper levels of poverty in the population, the adverse impact of

the distribution effect is more prominent.

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(2)The pro-poor growth index

We measure how much the poor will benefit from economic growth using the

various pro-poor indexes calculated using several different methods. We should note

that the pro-poorness of economic growth based on the three indexes is not always

consistent for some periods, especially during the period from 1995 to 2002.

According to the Ravallion and Chen (2003) index, economic growth was rather

pro-poor from 1988 to 1995. According to the national poverty line and the poverty

line of one US dollar per day (accounting for 12.89% and 59.62% of the population,

respectively), the income growth rate of the poor population in 1988 was respectively

146.2% and 42.5% higher than the income growth rate of the population during this

period. Therefore, economic growth during this period was pro-poor according to the

Ravallion and Chen (2003) index. However, the Kakwani and Pernia (2000) index and

the PEGR index indicate that economic growth in this period was not pro-poor,

insofar as the poor only shared in the benefits of economic growth through the

trickle-down effect. The Kakwani and Pernia (2000) index always ranges from zero to

one, while the PERG index is lower than the income growth rate of the population.

Table 10: Pro-poor growth index

1 USD/day Official poverty line

FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2)

19881995

Ravallion & Chen (2003) index 0.425 1.462

Kakwani & Pernia (2000) index 0.665 0.450 0.392 0.351 0.523 0.791

PEGR index/7 0.031 0.021 0.019 0.017 0.025 0.037

19952002

Ravallion & Chen (2003) index 0.428 0.680

Kakwani & Pernia (2000) index 1.030 0.893 0.849 1.409 1.122 0.992

PEGR index/7 0.078 0.068 0.064 0.107 0.085 0.075

20022007

Ravallion & Chen (2003) index 0.060 -1.048Kakwani & Pernia (2000) index 0.869 0.683 0.543 0.684 0.199 -0.296

PEGR index/5 0.093 0.073 0.058 0.073 0.021 -0.032

This inconsistency is more obvious during the period from 1995 to 2002.

According to the Ravallion and Chen (2003) index, the income growth rate of the

bottom10.71% of the population with the lowest income (the poverty rate in 1995

calculated according to the national poverty line) increased by 68% between 1995 and

2002. The income growth rate of the bottom 12.89% of the population with the lowest

income (the poverty rate in 1988 calculated according to the national poverty line)

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increased by 146.2% between 1988 and 1995, almost double that during the period

19952002. Therefore, the pro-poor economic growth between 1995 and 2002 is

lower than during the period 19881995. However, the situation is exactly the

opposite according to the Kakwani and Pernia (2000) index. This is because the

pro-poor index is greater than one according to the poverty rate given by the national

poverty line and the poverty standard of one US dollar per day. The Kakwani and

Pernia (2000) index lies closer to one in the other case, much higher than the

corresponding index in the other periods. The Kakwani and Pernia (2000) index

indicates that the extent of the pro-poorness of economic growth was highest between

1995 and 2002 and economic growth was strictly pro-poor during the period

19952002. The PEGR was relatively high taking into account economic growth and

poverty alleviation between 1995 and 2002.

The pro-poorness of economic growth between 2002 and 2007 is perhaps the

most surprising. As shown in Table 4, the average income of the poor displayed

negative growth in this period and it was particularly evident when decreasing the

poverty line standard. The pro-poorness of economic growth was the lowest during

this period according to the Ravallion and Chen (2003) index. However, the Kakwani

and Pernia (2000) index showed that the pro-poor in this period were located

somewhere between that in 19881995 and 19952002. The PEGR index was the

highest in 20022007 according to the poverty line of one US dollar per day. If we

decrease the poverty line or increase the poverty aversion coefficient, the PEGRindex may be the lowest in this period. The concern for poverty is mainly

concentrated in the poverty rate under usual circumstances. The decline of the poverty

rate means the alleviation of poverty, but the deepening of poverty for the poor may

also accompany the change. The pro-poor index between 2002 and 2007 indicates that

it became increasingly difficult for the extremely poor to benefit from economic

growth.

6. Decomposition of poverty changes by income components

(1) Contribution on poverty measures by income components

Researchers usually examine the impact factors of poverty and poverty changes

using regression methods, such as in Wei and Gustafsson (2000) and Li et al. (2008).

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significant downward trend. Taking the poverty rate for example, the relative

contribution of agriculture net income to the poverty rate was 80.24% in 1988

according to the national poverty line, while it decreased by nearly 12% to 68.35%

and further declined to 52.8% in 2002 and 43.71% in 2007. This trend remains

evident even if we set the poverty line to one US dollar per day or consider the other

poverty indicators. The changes in wage income lie opposite to this trend. The effect

of migrant income and other wage income increases gradually in the poverty decision.

According to the national poverty line, the relative contribution of migrant income to

the poverty rate was 3.71% in 1995, while it increased by 9% to 12.79% in 2002 and

further increased to 18.35% in 2007. The contribution of other wage income also

increased from 4.57% in 1988 to 22.13% in 2007. Wage income mostly comes from

nonfarm economic activities. However, the relative contribution of nonfarm business

income had decreased to varying degrees in the periods 19952002 and 20022007

with the exception of the1 percent increase between 1988 and 1995.

The effects of property income and transfer income in the poverty decision are

very low. The contribution of transfer income on poverty alleviation was the highest

in 2007 except for 1988. With the increase in the poverty aversion coefficient, the

relative contribution of transfer income also rises because it gives greater weight to

the low-income population. This will increase when we use a lower poverty line. This

means that the effect of transfer income on poverty alleviation gradually increases.

The effect of transfer income on poverty relates to preferential agricultural policies,

although we have no further means of dividing transfer income into private and public

transfers1.

The increase in the poverty aversion coefficient means that it gives a higher

weight to the low-income population. In other words, the poverty gap is more

sensitive than the poverty rate to the low-income population. In addition, the weighted

poverty gap is more sensitive than the poverty gap to income change in the

low-income population. According to the contribution of itemized income under the

different poverty aversion coefficients and poverty standards, we can further infer the

impacts on the different poor populations. The relative contribution of migrant income

increased in different years. However, the change in the poverty aversion coefficient

and the poverty standard did not significantly change the relative contribution of

1The 2007 survey did not distinguish between private and public transfers.

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migrant income to poverty in the corresponding year. Therefore, migrant income has a

significant poverty alleviation effect and may have a more equal distribution among

the poor population. The contribution of agriculture net income to poverty rose with

the increase in the poverty aversion coefficient and the decline in the poverty line in

1995; this was not apparent in other years. In general, the basic feature may be the

opposite; for example, the relative contribution of agriculture net income to poverty

decreased with the increase in the poverty aversion coefficient in 2007.

(2) The distribution elasticity by income component

From the growth and distribution factors, we can see that the distribution

elasticity is gradually increasing. This means that the adverse effect of inequality in

the income distribution for poverty alleviation is strengthening. Table 9 further details

the distribution elasticity by income components. As shown, the distribution elasticity

of each income component is positive in most cases. This means that the rising

inequality of itemized income will lead to an increase in poverty. For example, a 1

percent increase in the inequality of migrant income will lead to an increase of 5.53%

in the poverty rate, 9.51% in the poverty gap and 6.6% in the weighted poverty rate

according to the national poverty line. In turn, it will lead to a decrease of 0.21% in

the poverty rate, an increase of 2.29% in the poverty gap and an increase of 2.23% in

the weighted poverty gap according to the poverty line of one US dollar per day.

Overall, this suggests an upward trend in the impact of the inequality of itemized

income on poverty. The distribution elasticity is also usually increasing. This means

that the adverse effect of the inequality of itemized income on poverty alleviation is

gradually increasing. For example, according to the national poverty line, the

distribution elasticity of poverty to agriculture net income was 3.31%. However, this

increased in subsequent years and reached 16.42% in 2007. The distribution elasticity

of poverty to migrant income rose 10% between 1988 and 2007. The impact of these

two incomes on the distribution elasticity of poverty is also relatively large. If

considering the poverty gap and the weighted poverty gap, the growth rate of

distribution elasticity will be higher, especially for the agriculture net income. The

distribution elasticity that poverty indicators reflect on agriculture net income and

migrant income is usually relatively high. The distribution elasticity of the poverty

gap and the weighted poverty gap to agriculture net income even reached 30%

(national poverty line) and 10% (the poverty line of one US dollar per day) in 2007.

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The lower the poverty standard is, the higher will be the distribution elasticity of

income component in most cases. This means that the strength of the inequality in

itemized income is not beneficial to the poverty alleviation of the low-income

population. In 2007, the distribution elasticity of the poverty rate to migrant income

was as high as 16.55% according to the national poverty line and it decreases by 10%

to 6.37% according to the poverty standard of one US dollar per day. The impact is

similar for the poverty gap. However, the poverty distribution elasticity of itemized

income does not exhibit a regular relationship with the change in the poverty aversion

coefficient.

Table 12: The distribution elasticity of itemized income to poverty change

National poverty line 1 USD/day National poverty line 1 USD/dayFGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2) FGT(0) FGT(1) FGT(2)

1988 1995

Income from migration 5.53 9.51 6.60 -0.21 2.29 2.23Wage income 2.21 2.61 1.52 0.48 1.07 0.81 3.08 4.78 3.28 0.73 1.38 1.21

Agriculture income 3.31 4.91 3.37 -0.15 1.08 1.16 4.30 8.11 5.94 0.38 1.98 1.91

Nonfarm operation

income2.91 3.69 2.44 0.17 1.11 1.00 3.35 5.83 4.15 0.62 1.56 1.42

Property income 1.78 0.94 0.51 0.84 1.21 0.54 3.33 5.39 3.78 0.52 1.53 1.36

Transfer income 1.83 3.58 2.43 0.33 1.08 0.89 1.13 -0.99 -1.06 2.09 0.21 -0.01

2002 2007

Income from migration -0.070 0.509 1.086 -0.106 0.105 0.333 0.050 1.288 2.541 -0.119 0.396 0.903Wage income 0.043 1.220 2.273 -0.105 0.344 0.874 0.212 2.004 3.805 -0.063 0.636 1.342

Agriculture income 1.139 2.699 2.277 -0.109 0.630 1.645 1.224 3.060 2.969 -0.013 0.962 1.953

Nonfarm operationincome

-0.048 0.577 1.751 -0.073 0.168 0.804 -0.011 0.846 1.738 -0.054 0.288 0.661

Property income -0.043 0.152 0.366 -0.014 0.033 0.106 -0.012 0.213 0.470 0.000 0.062 0.156

Transfer income 0.025 0.058 0.006 0.018 -0.042 0.273 0.601 -0.028 0.073 0.188

7. Conclusion

Rural poverty has been in significant decline during the reform and opening upof China. According to the official poverty standard, the incidence of poverty in rural

areas is insignificant. On the one hand, economic growth and the increase in farmer

income have reduced poverty significantly; on the other hand, the expansion of the

income gap during the process of economic growth has an adverse effect on poverty

alleviation. The poverty alleviation effect of economic growth fluctuates in different

periods. Using micro survey data, we estimate the economic and distribution effects

of poverty change in different years using Datt-Ravallion and Shapley decomposition.

We also calculate the impact of a 1 percent change in income and the Gini coefficient

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on the poverty rate based on the characteristics of the income distribution in different

years. In addition, we further define the results as relating to the growth and

distribution elasticity of poverty.

The results indicate that the growth elasticity of poverty decreased gradually

while the distribution elasticity of poverty increased gradually. On this basis, the

economic growth in China between 2002 and 2007 did not benefit the poor according

to the pro-poor index in different periods and it may even have damaged the benefits

of economic growth to the poor according to the national poverty line and the

weighted poverty gap. This also means that the economic growth in this period was

not conducive to the welfare improvement of extreme poverty.

We also discussed the impact of income components on the incidence of poverty

in the different years. The contribution of agriculture net income to poverty indicators

is generally the most significant; however, its share exhibits a significant downward

trend. The effect of migrant income and other wage income in the poverty decision is

that of a gradual increase. The share of property income and transfer income has been

very low in the poverty determinants. The increase in the distribution elasticity

indicates that the adverse effect of inequality in the income distribution for poverty

alleviation is rising. The impact of the inequality of itemized income distribution for

poverty shows an upward trend and the adverse effect is gradually increasing. The

lower the poverty standard is, the higher the distribution elasticity of itemized income

will be. This means that the enhancement of itemized income inequality is not

beneficial to the poverty alleviation of low-income groups. As for pro-poor policies,

income growth remains the key factor for addressing poverty alleviation. At the same

time, we should be more concerned about the change in the income distribution. The

expansion of the income inequality has largely offset the poverty reduction effect of

economic growth. To reduce the income gap, on the one hand we need to strengthen

the redistribution effect of public transfers so that they can be more beneficial to the

rural low-income population. On the other hand, we should focus on improving the

employment opportunities for people on low incomes so that they can effectively

benefit from Chinas economic growth. Narrowing the income distribution plays a

more important role in the process of poverty alleviation in the focus counties.

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