Mapping Poverty in Rural China: How Much Does the Environment Matter?

This is an interesting empirical approach I need to look at more closely. It is not entirely clear to me how closely environmental issues (rainfall, temperature etc.) are related to poverty levels.

This is an excellent paper with lots of colourful pictures.

Mapping Poverty in Rural China: How Much Does the Environment Matter?

Date: 2008-09-12
By: Susan Olivia (University of California, Davis)
John Gibson (University of Waikato)
Scott Rozelle (Stanford University)
Jikun Huang (Chinese Academy of Sciences)
Xiangzheng Deng (Chinese Academy of Sciences)

URL: http://d.repec.org/n?u=RePEc:wai:econwp:08/14&r=env
[PDF]

In this paper, we apply a recently developed small-area estimation technique to derive geographically detailed estimates of consumption-based poverty and inequality in rural Shaanxi, China. We also investigate whether using environmental variables derived mainly from satellite remote sensing improves upon traditional approaches that only use household survey and census data. According to our results, ignoring environmental variables in statistical analyses that predict small-area poverty rates leads to targeting errors. In other words, using environmental variables both helps more accurately identify poor areas (so they should be able to receive more transfers of poor area funds) and identify non-poor areas (which would allow policy makers to reduce poverty funds in these better off areas and redirect them to poor areas). Using area-based targeting may be an efficient way to reach the poor since many counties and townships in rural Shaanxi have low levels of inequality, even though, on average, there is more within-group than between-group inequality. Using information on locations that are, in fact, receiving poverty assistance, our analysis also produces evidence that official poverty policy in Shaanxi targets particular areas which in reality are no poorer than other areas that do not get targeted.
Keywords: China; environment; poverty; small area estimation
JEL: O15 O53 P36 Q56