Poverty Dynamics of Households in Rural China

Abstract

The objective of our study is to identify patterns and causes of households' transitions into and out of poverty using the long household panel data on rural China in 1989-2009. We propose a discrete-time multi-spell duration model that not only corrects for unobserved heterogeneity, but also addresses the endogeneity due to dynamic selection associated with household's livelihood strategies. The household choosing farming or out-migration as a main livelihood strategy was more likely to escape from persistent poverty than those taking local non-agricultural employment. The present study emphasizes the central role of agriculture in helping the chronically poor escape from poverty.

Spatial covariance of ecosystem services and poverty in China

“…More specifically, our analyses show that high levels of provisioning ES -particularly those related to agricultural production -generally coincide with low levels of rural poverty in China. Our results support economic analysis of household-level time series data from China which shows the importance of farming as strategy for staying out of poverty for the rural population (Imai and You 2014). However, our results also show that having low levels of provisioning ES is in itself not a good predictor of a county being poor.…”

“…China has been extraordinarily successful in reducing rural poverty between 1980 and the early 2000s, largely through increases in agricultural production and nonfarm incomes (De Janvry et al 2005;Imai and You 2014). However, lifting the remaining rural poor out of poverty has proved more difficult as they frequently live within remote areas (Imai and You 2014).…”

“…Again, this is not a surprising finding, as income rural poverty is a multifaceted issue that is driven by many factors that we were unable to quantify in this study. These include not only access to markets and remittances from migrants to urban areas (Donaldson 2011), demographics and education (Imai and You 2014), income from sources other than natural resources (De Janvry et al 2005) but also biophysical factors such as rainfall and elevation (Olivia et al 2011). …”

“…First, we use the binary indicator of 'poor county' due to its simplicity and policy relevance. Income poverty is widely used to study poverty in China (Imai and You 2014), and the list of 'key poverty-stricken counties' we use here is a key indicator used by the Chinese government to target government assistance (State Council Leading Group Office of Poverty Alleviation and Development 2012). Second, income poverty is the aspect of poverty most directly linked to the ES for which data are available at the scale of China (provisioning ES), as multiple studies have shown that wealth in rural areas is directly linked to natural resources derived from the environment (Cavendish 2000;Porro et al 2015).…”

“…The remarkable reductions in rural poverty between 1980 and 2001 have been attributed to not only increases in agricultural production but also large increases in non-farm incomes (De Janvry et al 2005;Imai and You 2014). However, the remaining rural poor population may be less well placed to move out of poverty via these mechanisms, as they disproportionately live in forested mountainous areas (Rodriguez et al 2009;FAO 2012).…”