The pattern of growth and poverty reduction in China

Abstract

China’s rapid economic growth has been the proximate cause of the huge reduction in the incidence of poverty since 1980. Yet, the growth process has been highly uneven across sectors and regions. We test whether the pattern of China’s growth mattered to poverty reduction using a new provincial panel data set constructed for this purpose. Our econometric tests support the view that the primary sector (mainly agriculture) has been the main driving force in poverty reduction. We note a number of similarities, and differences, with India.

Introduction

Based on cross-country comparisons, a number of papers in the literature have found that measures of absolute poverty tend to fall with economic growth.¹ However, it is also evident that there is a sizeable variance in the impacts of a given rate of growth on poverty. Some of this is measurement error, but it has also been argued that there are systematic factors influencing the elasticity of poverty measures to higher mean income.

Probably the main reason advanced in the literature and in policy discussions as to why a given rate of growth can deliver diverse outcomes for poor people is that the “pattern of growth” matters independently of the overall rate of growth. We can state this hypothesis in slightly more formal terms as follows:

Pattern of growth hypothesis (PGH): The sectoral and/or geographic composition of economic activity affects the aggregate rate of poverty reduction independently of the aggregate rate of growth.

If true, then the often-heard claim that the policies that are good for growth are necessarily also good for poverty reduction becomes questionable, given that the actions needed for growth in one sector or place need not accord with those needed elsewhere. This is particularly salient to the role of agricultural growth, which is likely to require rather different policies to other sectors (Headey, 2008).

In principle one can think of two reasons why PGH might hold. The first is that the relevant between-group component of inequality is sufficiently large that the pattern of growth across those groups systematically alters the distribution of income and (hence) the extent of poverty at any given mean income. Intuitively, if economic growth is very intense in sectors that do not benefit poor people then inequality will rise, choking off the gains to the poor from growth.

The second reason is that the composition of economic activity is one factor influencing the initial level of inequality. This holds even if the subsequent growth process is distribution-neutral (all incomes grow at the same rate). Intuitively, when the poor have a low initial share of total income they will tend to have a lower share of the gains in aggregate income during the growth process. Empirically, the initial distribution of income is known to be important for the subsequent effect of economic growth on poverty (Ravallion, 1997, Bourguignon, 2003).

In the context of India, Ravallion and Datt, 1996, Ravallion and Datt, 2002 and Datt and Ravallion (2002) report results indicating that the sectoral and geographic composition of growth has mattered to aggregate poverty reduction. Rural economic growth has had more impact on poverty in India than urban economic growth, and growth in the tertiary (mainly services) sector has had more impact than the primary (mainly agriculture) sector, while the secondary (mainly manufacturing) sector appears to have brought little direct gain to India’s poor. Empirical support for the PGH has also come from cross-country evidence suggesting that more labor-intensive growth processes have greater impact on poverty, as found by Loayza and Raddatz (forthcoming).

However, all this sits uneasily with the observation that the country that has undoubtedly made the most impressive progress against absolute poverty over recent decades has also had one of the most sectorally and geographically unbalanced growth processes. We refer to China. While the impressive growth performance of China since the early 1980s is well known, there has been much concern in recent times that this growth process has been “unbalanced,” and in particular that growth rates in agriculture have appreciably lagged those in other sectors, notably industry and services (Kuijs and Wang, 2006, Chaudhuri and Ravallion, 2006). The primary sector’s share fell from 30% in 1980 to 15% in 2001, though not montonically. Yet China’s record against absolute poverty has been impressive. Using their national poverty line, Ravallion and Chen (2007) found that the poverty rate (headcount index) fell from 53% in 1981 to 8% in 2001. Using decomposition methods, the same authors found that about three-quarters of this reduction in poverty nationally was due to poverty reduction solely within rural areas.

These observations motivate the main questions addressed by this paper: What role did the apparent “imbalances” of China’s growth process play in China’s progress against poverty? Would a more balanced growth process have had a larger impact on poverty? Or could it be that the unbalanced growth actually fostered poverty reduction, by allowing a higher overall growth rate?

There is already evidence in the literature to suggest that China’s rate of poverty reduction would have been even higher if not for the pattern of growth. Using aggregate (national level) time series data for China, Ravallion and Chen (2007) find evidence that the sectoral composition of growth (how much comes from agriculture versus manufacturing versus services) matters to both poverty and inequality independently of the rate of growth. If the same rate of growth had been possible without the sectoral imbalances observed then the Ravallion and Chen results suggest that it would have taken half the time to achieve the reduction in poverty observed over 1981–2001.

This type of calculation assumes that the same overall rate of growth would have been possible without the sectoral imbalances. In principle, that is a strong assumption. However, it is not as strong as one might guess in the China context. The sectoral imbalance in China’s growth process is in part the result of deliberate policies on the part of the government. A number of specific policy instruments were used for this purpose, including²:

• subsidized prices for key inputs (including energy, utilities and land), weak or weakly enforced regulations (including environmental protection);

• favoured treatment for industry in access to finance, especially for large (private and state-owned) enterprises;

• restrictions on labor movement through the Hukou system and discriminatory regulations against migrant workers in cities; and

• local administrative allocation of land, with the effect that out migrants from rural areas face a high likelihood that they will lose their agricultural land rights.³

Given that the sectoral pattern of growth was far from being a wholly market-driven process, it would clearly be hazardous to assume that the specific pattern of growth was efficient and (hence) promoted the maximum overall rate of growth. Ravallion and Chen (2007) address this issue empirically, and argue that the national-level data do not provide compelling evidence for believing that lower growth rates in the primary sector were the “price” of higher growth in the secondary and tertiary sectors.

The main contribution of the present paper is to assess the contribution to poverty reduction of the sectoral and geographic pattern of China’s growth, by extending the Ravallion–Chen analysis to the provincial level. By adding the extra variability in the geographic (inter-provincial) dimension we are able to enhance the power of the various tests of the PGH that we undertake—enhancing the scope for identification and precision of the estimates over past studies. By allowing us to introduce a latent provincial effect in the error term, our provincial panel-data analysis also addresses concerns about omitted variables. Additionally, the common origin and methodology of the primary data make this empirical exercise more immune to the comparability problems facing cross-country studies.⁴

In addition to testing whether the pattern of growth has mattered to poverty reduction, we aim to assess how quantitatively important the pattern of growth has been to China’s (very high) overall rate of poverty reduction. We may not reject the PGH, but find that the effect is small. Or we might find that far larger reductions in poverty could have been possible if the same growth rate was more even across sectors and areas. We investigate this issue more deeply using the sub-national data, and also see if there is any evidence of a significant trade-off between the overall growth rate and its sectoral composition.

We shall also make a number of observations comparing China with India in terms of the relevance of the pattern of growth to poverty reduction. The fact that a similar study was already conducted at the provincial level for the case of India by Ravallion and Datt (2002) allows us to compare the results of China and India.

The following section describes the trends in poverty reduction across China’s provinces that we find in the data. Section 3 examines the role played by the sectoral composition of growth, and Section 4 extends this analysis to allow for differing parameters across provinces. Section 5 uses counterfactual analysis to quantify the importance of the pattern of growth to poverty reduction. Section 6 concludes.