Abstract
Energy is a critical factor of economic growth, but the overuse of it results in global warming and climate change. Hence, energy efficiency improvement can help mitigate climate change and prevent economic losses or even ecological extinction. The data envelopment analysis (DEA) approach has been extensively applied for energy efficiency estimation, but past studies of this estimation employ a static mode that does not consider consecutive periods and the carry-over effect. This study estimates energy efficiency under a weight-restricted dynamic DEA (WrD-DEA) model, creates a weight-restricted dynamic energy efficiency (WrD-EE) indicator, and discusses issues concerning the energy decoupling rate and decarbonization. We utilize members in the Group of Seven (G7) and BRICS (Brazil, China, India, Russia, and South Africa) for our experimental observations. The main results herein are: (1) BRICS has larger room for improvement to achieve the standard ratio of the energy decoupling rate than the G7; (2) the G7 and BRICS do not converge to decarbonization; and (3) BRICS exhibits more rapid improvement on energy efficiency than the G7.
Highlights
It is well known that energy consumption and economic growth have a close correlation, with even India’s government announcing that it must increase energy consumption to help lift its population out of poverty [1]
Under the data envelopment analysis (DEA) approach, this study develops the dynamic model proposed by Kao [18] as the dynamic energy efficiency model (DEEM) in order to measure energy efficiency in the G7 and BRICS
Energy use brings economic development to a country, but CO2 emissions are the byproduct of energy use and contribute to global warming and climate change, which affect economic development and environmental ecology
Summary
It is well known that energy consumption and economic growth have a close correlation, with even India’s government announcing that it must increase energy consumption to help lift its population out of poverty [1]. Oikonomou et al [24] assert that the complete flexibility on the DEA model’s weights may result in unreasonable low or high values to the model’s multipliers, which result in a biased efficiency score They utilize the investigation weight restrictions to estimate the efficiency of Greece’s rural health care system. Mandal [32] takes India’s cement industry as an example to estimate energy efficiency under a framework of desirable and undesirable outputs and shows that the biased energy efficiency result may be caused by neglecting undesirable outputs in a production process. This paper targets energy efficiency in emerging countries since their economic growth rates are stronger and their gas emissions cause the global warming, which relates to climate change as a concern of developed countries.
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