WITHDRAWN: Identifying the endogenous optimization pathways for improving environmental performance

Abstract

Improving environmental performance has been widely regarded as a key action to promote environmental sustainability. However, in most environmental performance models, the optimization pathways are pre-determined, neglecting the heterogeneity of the optimization pathways inherent in different producers, which can lead to a potential risk of distorting the results of environmental performance and generating misleading policy implications. This study reveals how endogenous optimization pathways for improving environmental performance can be identified. We first develop a distance function with endogenous direction to identify the endogenous optimization pathways for improving environmental performance and then propose an environmental performance index based on the identified endogenous optimization pathways. We apply our approach to a sample of 101 Chinese cities by considering two major pollutants (i.e., SO 2 and NOx emissions). It is found that our approach can capture the heterogeneity of the optimization pathways across different cities and pollutants well. A majority of cities prefer to improve their environmental performance by reducing NO x emissions rather than reducing SO 2 emissions. • Introduce endogenous optimization pathways into environmental performance measurement. • Develop DDF models with endogenous directions to identify the heterogeneous optimization pathways. • Construct a new environmental performance index based on endogenous optimization pathways. • Conduct an application study on 101 Chinese environmental protection cities.