No.65-Exploring Multidimensional Poverty in China: 2010 to 2014

Shen, Yangyang; Alkire, Sabina
Published: 2017/7/12 1:35:56    Updated time: 2017/7/12 13:53:12

Abstract: Most poverty research has explored monetary poverty. This paper presents and analyses the global Multidimensional Poverty Index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to sub-groups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.
Keywords: China; multidimensional poverty; poverty; disaggregation; mismatch

Authors:

Sabina Alkire (Director of Oxford Poverty and Human Development Initiative (OPHI), University of Oxford)

Yangyang Shen (Correspondent author; Post-Doc at China Institute for Income Distribution, Beijing Normal University)

 

1. Motivation and literature review

1.1 Motivation

When the People’s Republic of China was founded in 1949, China was one of the poorest countries in the world. According to the U.N. Economic and Social Commission for Asia and the Pacific (ESCAP), China’s national income per capita was 27 dollars in 1949, less than 2/3 of the average per capita income in Asia of 44 dollars and less than half of India’s per capita income of 57 dollars. Before China’s reform and opening (1979), 250 million people (30.7% of the population)1 were living in severe income poverty. But this tide turned after the 1980s. During 1978-2010, 250 million people moved out of monetary poverty by national definitions; 439 million people moved out of extreme income poverty from 1990 to 2011 using the $1.25/day standard (Millennium Development Goals Report 2015). In 2015, the official published rural poverty national headcount ratio was 5.7%2 .

Many studies have explored how China achieved this remarkable transformation. Economic growth is no doubt one factor3 . At the same time, China’s development-oriented anti-poverty policy played an important role as well. Impact evaluation4 and analyses of causal relationships5 have been conducted, but these have explored the dramatic changes in monetary poverty. This paper has a different focus. We consider poverty to be multidimensional, and so we explore the evolution of multidimensional poverty in non-monetary dimensions. While we cannot go back to 1978 to find out how many million people China have been lifted from multidimensional poverty, we can and do rigorously explore the evolution of multidimensional poverty from 2010-2014.

The theoretical framework for our paper follows Amartya Sen’s capability approach (Sen, 1999). According to Sen, poverty and development are best conceptualised in the space of capabilities – which show what each person is able to do and be. Poverty shows how people’s capabilities are constricted. It is multidimensional because people’s lives are “battered and diminished in many ways”. But why should Sen’s approach change how we measure poverty?

Empirically, there is an emerging agreement that economic growth does not necessarily lead to the improvement of welfare ((Bourguignon et al., 2010), (Ahluwalia, 2011)) and that monetary poverty measurement is not a sufficient proxy for poverty in all its dimensions (Ravallion, 2011b). A key motivation for this theoretical framework is that the Chinese traditional concept of poverty is multidimensional. “Poverty” in Chinese can be written as “贫困”, which combines two characters that can be divided into “Pin” and “Kun” with different meanings. “Pin” means “deficient”, while “Kun” means “being trapped” hence unable to access development related resources. 6 This concept has shaped China’s anti-poverty policies since the 1980s. For example, the recent document “Outline of China’s Rural Poverty Alleviation of 2011-2020” takes a multidimensional view and articulates the general target of anti-poverty policies as removing two worries – those related to food and clothing – and providing “three guarantees” – for basic health care, housing, and access to compulsory education. China is thus a pioneer in conceptualising nad implementing multidimensional poverty alleviation policies. But China has not yet officially applied multidimensional methods of poverty measurement. This paper creates and analyses China’s global MPI to explore what value-added an MPI for China might have.

1.2 Literature review

This paper is not the first study of multidimensional poverty in China. Multiple poverty concepts emerged in the 1990s with dashboards of indicators. For instance, 吴国宝 (1997) used indicators of education, assets, caloric intake, clean drinking water, housing, health condition, time use and health to explore the characteristics of poor people. 李小云 et al. (2005) designed a participatory multiple poverty index with eight dimensions, including production, living standard and education. During the beginning of the 21st century, multidimensional poverty concepts from the outside world were introduced7 . The pioneering empirical study using the AF method is 王小林 & Alkire (2009). They found that nearly 20% of the households in both rural and urban China were experiencing deprivations in at least three out of eight non-income dimensions. Since then, many studies have applied the AF method for empirical analyses. For instance, 邹薇 & 方迎风 (2011), 蒋翠侠 et al. (2011) and 张全红 (2015) analyse dynamic changes in poverty; 方迎风 (2012) compares the TFR and AF method; 蒋翠侠 et al. (2011) and 张全红 (2015) explore general weighting structures. Wang (2016) explores the relationship between income and multidimensional poverty. But none of the existing papers use nationally representative datasets, making it impossible for the existing academic literature to state how multidimensional poverty has evolved in China.

In contrast with the existing papers, our results use nationally representative data. Additionally, the MPI we compute is internationally comparable, and can be compared across three time periods. Moreover, this paper explores poverty by regions, social characteristics, and indicators and investigates the relationship between monetary and multidimensional poverty. It provides the first definitive national picture of poverty and its change over time according to the global MPI.

While we are very pleased to offer this new study, and grateful for the CFPS dataset that makes it possible, we would like to acknowledge two shortcomings at the outset. The first is that the global MPI, while being very useful as a tool by which to compare China to other countries across the developing world, is actually inappropriate for contemporary China because it reflects the degree of ‘acute’ poverty which has largely been resolved in China. So for purposes of national policy, China would probably wish to build an improved national MPI. Second, despite the great benefits of the CFPS dataset, its sample size is relatively small compared to China’s population. This results in estimations with high standard errors, and does not permit all relevant disaggregated comparisons, for example by each province or county. Estimations should be run on larger datasets also, to obtain high resolution poverty maps.

The paper unfolds as follows: we present the methodology, data and indicators in the second and third sections respectively. Section four presents China’s national poverty results from 2010 to 2014. Detailed disaggregated analyses are shared in section five. The relationship between monetary and multidimensional poverty is explored in section six; robustness tests for weights are shared in section seven, then the paper concludes.

 

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1 Source: director Xiaojian Fan’s report for the State Council Leading Group Office of Poverty Alleviation and Development [in Chinese].

2 Appendix-A provides the poverty results in China. For related studies see: (Ravallion & Jalan, 1999), (Chen & Ravallion, 2004), (Chen & Ravallion, 2008) and (UNDP, 2013).

3 (Yao, 2000), (林伯强, 2003)[in Chinese], (沈扬扬, 2012a, 2012b) [in Chinese]) studied the relationship between economic growth and income inequality to poverty, and in general concluded that economic growth reduces poverty, but inequality increases poverty.

4 See (Rozelle, 1998), (Park, Wang, & Wu, 2002), (Chen, Ravallion, Galasso, Piazza, & Tidrick, 2005), (Meng, 2013), (Li & Sicular, 2014).

5 See (万广华 & 张藕香, 2008) [in Chinese], (罗楚亮, 2010) [in Chinese].

6 See (X. Wang, Feng, Xia, & Alkire, 2016).

7 For instance, the Watts multidimensional poverty index (陈立中, 2008a, 2008b); the fuzzy sets method (丁建军, 2014).