An Analysis of Energy Use Efficiency in China by Applying Stochastic Frontier Panel Data Models

Xiaoyan Zheng and Almas Heshmati ()
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Xiaoyan Zheng: Department of Economics, Sogang University, 35 Baekbeom-ro (Sinsu-dong #1), Mapo-gu, Seoul 04107 Korea

Energies, 2020, vol. 13, issue 8, 1-17

Abstract: This paper investigates energy use efficiency at the province level in China using the stochastic frontier panel data model approach. The stochastic frontier model is a parametric model which allows for the modeling of the relationship between energy use and its determinants using different control variables. The main control variables in this paper are energy policy and environmental and regulatory variables. This paper uses province level data from all provinces in China for the period 2010–2017. Three different models are estimated accounting for the panel nature of the data; province-specific heterogeneity and province-specific energy inefficiency effects are separated. The models differ because of their underlying assumptions, but they also complement each other. The paper also explains the degree of inefficiency in energy use by its possible determinants, including those related to the public energy policy and environmental regulations. This research supplements existing research from the perspective of energy policy and regional heterogeneity. The paper identifies potential areas for improving energy efficiency in the western and northeastern regions of China. Its findings provide new empirical evidence for estimating and evaluating China’s energy efficiency and a transition to cleaner energy sources and production.

Keywords: energy efficiency; time-variant efficiency; true fixed-effects model; four components stochastic frontier model; determinants of inefficiency; Chinese provinces (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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