Literature DB >> 21518856

Rural household income and inequality under the Sloping Land Conversion Program in western China.

Jie Li1, Marcus W Feldman, Shuzhuo Li, Gretchen C Daily.   

Abstract

As payment for ecosystem services (PES) programs proliferate globally, assessing their impact upon households' income and livelihood patterns is critical. The Sloping Land Conversion Program (SLCP) is an exceptional PES program, in terms of its ambitious biophysical and socioeconomic objectives, large geographic scale, numbers of people directly affected, and duration of operation. The SLCP has now operated in the poor mountainous areas in China for 10 y and offers a unique opportunity for policy evaluation. Using survey data on rural households' livelihoods in the southern mountain area in Zhouzhi County, Shaanxi Province, we carry out a statistical analysis of the effects of PES and other factors on rural household income. We analyze the extent of income inequality and compare the socio-demographic features and household income of households participating in the SLCP with those that did not. Our statistical analysis shows that participation in SLCP has significant positive impacts upon household income, especially for low- and medium-income households; however, participation also has some negative impacts on the low- and medium-income households. Overall, income inequality is less among households participating in the SLCP than among those that do not after 7 y of the PES program. Different income sources have different effects on Gini statistics; in particular, wage income has opposite effects on income inequality for the participating and nonparticipating households. We find, however, that the SLCP has not increased the transfer of labor toward nonfarming activities in the survey site, as the government expected.

Entities:  

Year:  2011        PMID: 21518856      PMCID: PMC3093530          DOI: 10.1073/pnas.1101018108

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


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