An Evaluation of the Impact of Ecological Compensation on the Cross-Section Efficiency Using SFA and DEA: A Case Study of Xin’an River Basin

Junran Dong and Desheng Wu
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Junran Dong: School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China

Sustainability, 2020, vol. 12, issue 19, 1-18

Abstract: This paper aims to address the issue of evaluating watershed environmental efficiency with ecological compensation. One of the main objectives is the dynamic assessment of cross-section efficiency. The first transboundary watershed ecological compensation pilot of Xin’an river basin serves as the case study, and stochastic frontier analysis (SFA) is adopted as the main evaluation method. Furthermore, the efficiency is estimated by the data envelopment analysis (DEA) approach. The results validate that SFA can be used as an effective method on such issues by comparing it with the benchmark and the result of DEA, which proves the feasibility of our research methodology. The other purpose is to investigate the factors affecting environmental efficiency. This paper explores the relationship between environmental efficiency with 21 pollutant emission factors as well as the correlation between environmental efficiency and five macro factors of economic development, industrial structure, population density, degree of environmental protection, and natural environment. Finally, suggestions are provided for future improvement. This paper therefore presents a comprehensive reference analysis that contributes to facilitating balanced regional development and environmental conservation in the future.

Keywords: watershed ecological compensation; environmental efficiency; Xin’an river basin; stochastic frontier analysis; data envelopment analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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