Regional Differences in the Spatial Characteristics and Dynamic Convergence of Environmental Efficiency in China

Abstract

This study uses the undesirable output and super-efficiency slacks-based measure combined with window (WIN-US-SBM) data envelopment analysis (DEA) to evaluate the environmental efficiency (EE) in 30 Chinese provinces, from 2005 to 2016, explores regional differences in the EE, and uses the dynamic spatial Durbin model (DSDM) to analyze regional differences in effects of important factors on the convergence of EE. It reveals that EE in the eastern area is higher than EE in the central and western areas, and a positive spatial autocorrelation exists in the interregional EE. The difference in provincial EE gradually narrows over time and tends to converge to its own steady-state level. Economic growth reduces EE for the central and western areas and improves efficiency for the eastern area; economic growth from surrounding areas indirectly promotes local EE for the eastern area. Foreign direct investment (FDI) promotes EE in the eastern and central areas, and FDI in the adjacent areas has a positive effect on local EE for the eastern area. Export reduces EE for all areas, and export in surrounding areas indirectly promotes local EE for the central area. Industrialization reduces EE in the western area, and industrialization in the surrounding areas increases local EE for the eastern area. Energy efficiency promotes EE for the central area, urbanization increases EE for the central area, and urbanization of the surrounding areas reduces local EE for the eastern area.

Human Capital, Trade Competitiveness and Environmental Efficiency Convergence Across Asia Pacific Countries

“…They also established a club convergence among the efficient economies. Xu et al ( 2020 ), and studied the dynamic convergence of eco-efficiency in China. Through the application of the Super Efficiency SBM model as well as the dynamic spatial Durbin Model (DSDM), they found a positive autocorrelation in inter-regional Eco-efficiency and established steadiness in convergence over time as environmental efficiency narrowed (Long et al 2017 ).…”

Regional disparities and dynamic evolution of competitiveness of marine fish aquaculture industry − A study of China

“…In this paper, the absolute b-convergence model is used, which means that the competitiveness level of the MFAI in each region will converge without considering the influence of external factors. Referencing the existing studies (Xu et al, 2020;Yu et al, 2020), the absolute b-convergence model of the competitiveness level of the MFAI takes the following form:…”

Sustainable Evolution of China’s Regional Energy Efficiency Based on a Weighted SBM Model with Energy Substitutability

“…To solve the problems above, the data envelopment analysis (DEA) method developed by Charnes et al [10] has been widely applied in evaluating the energy efficiency of different regions or countries and monitoring efficiency evolution. As indicated by Liu et al [11] and Meng et al [12], a rapid increase in literature is produced by using the DEA models to evaluate the energy and technical efficiency of different DMUs in various situations, e.g., industrial sectors in Wu et al [13], the construction industry in Feng and Wang [14], the iron and steel industry in Yang et al [15], the transport industry in Feng and Wang [16], the environmental efficiency in Xu et al [17], and the Chinese regional energy efficiency in Wang et al [18]. However, the DEA model treats the internal production process as a "black box" [19] and assumes that it is invariant with respect to DMUs.…”