An analysis of energy use efficiency in China by applying stochastic frontier panel data models
2020 (English)In: Energies, E-ISSN 1996-1073, Vol. 13, no 8, article id 1892
Article in journal (Refereed) Published
Sustainable development
Sustainable Development
Abstract [en]
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.
Place, publisher, year, edition, pages
MDPI, 2020. Vol. 13, no 8, article id 1892
Keywords [en]
Chinese provinces, Determinants of inefficiency, Energy efficiency, Four components stochastic frontier model, Time-variant efficiency, True fixed-effects model, Energy policy, Environmental regulations, Stochastic systems, Cleaner energies, Control variable, Energy-use efficiency, Panel data models, Parametric modeling, Specific energy, Stochastic frontier, Stochastic frontier models, Stochastic models
National Category
Economics
Identifiers
URN: urn:nbn:se:hj:diva-49122DOI: 10.3390/en13081892ISI: 000538041800035Scopus ID: 2-s2.0-85083628078Local ID: GOA;intsam;1438296OAI: oai:DiVA.org:hj-49122DiVA, id: diva2:1438296
2020-06-102020-06-102023-08-28Bibliographically approved