Gauging the environmental efficiency with ecological compensation in presence of missing data using data envelopment analysis

The ecological compensation mechanism is regarded as the direction for the future management of the ecological environment of the river basin, which has become a global concern. Ex-post assessments on the performance of ecological compensation programs contribute to further improvement and optimization in the process of exploration. This study proposes a novel performance assessment approach to address the issue of environmental efficiency evaluation with uncertainty by systematically integrating data envelopment analysis (DEA), bootstrap, regression, and exponential smoothing. The last two methods are used to fill in missing data, DEA super-SBM is applied to measure the performance, and bootstrap is adopted to stimulate more data. This approach is applied to performance measurement of Xin'an river basin in China. Validated by benchmark comparisons and statistical tests, the outcomes indicate that this integrated conceptual method can serve as an effective way to gauge environmental efficiency with ecological compensation when missing data are presented. The results obtained from the case highlight the limited positive effect of ecological compensation. Marginal utility brought about by the ecological compensation investment fund is declining, and the fund utilization in some projects also appears to be low. Consequently, suggestions for future optimization on fund and performance management, evaluation method and compensation mode are provided.