Selection of targeted poverty alleviation policies from the perspective of land resources-environmental carrying capacity

Selecting the appropriate targeted poverty alleviation policies and exploring the implementation path of refined poverty alleviation policies are important to provide support for achieving a comprehensive poverty alleviation for China in 2020. Two models, namely, land resources-environmental carrying capacity (LRECC) index and the coupling coordination degree (CCD), were established to quantitatively explore the important effects of differences in the LRECC in the production, living and ecological spaces on poverty, and determine the important role of superior carrying space in poverty alleviation. Additionally, this study explored the relationship between the poverty incidence and the LRECC by using of the coefficient of geographical association (CGA) to perform the priority and the optimal selection of targeted poverty alleviation policies from the production, living, and ecological spaces. Results showed that the comprehensive CGAs of Long Zhouping township, Huo Shaoping township and other townships were high; therefore, the priority of targeted poverty alleviation was high. By contrast, the comprehensive CGAs of Ya Zikou township, Du Zhenwan township, and other townships were low; thus, the priority of targeted poverty alleviation was low. Long Zhouping and Dayan townships should select the production aspect of targeted poverty alleviation policies, whereas Du Zhenwan and Ya Zikou townships and Gao Jiayan and Moshi townships should select the living and ecological aspects, respectively. Selecting the appropriate targeted poverty alleviation policies by quantitatively identifying the advantages of regional land resource endowment and the poverty incidence will help take the poor out of poverty, and do not become poor again, thereby achieving regional sustainable development.

Automated summary

Selecting appropriate targeted poverty alleviation policies and exploring their implementation path are crucial for achieving comprehensive poverty alleviation in China by 2020. This study establishes the LRECC index and CCD model to quantitatively assess the effects of LRECC differences in production, living, and ecological spaces on poverty alleviation. It also examines the relationship between poverty incidence and LRECC, and prioritizes and optimally selects targeted poverty alleviation policies based on geographical association coefficients. The findings indicate the importance of selecting suitable policies based on regional advantages and poverty incidence for sustainable regional development.