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Measurement of the “Underlying energy efficiency” in Chinese provinces

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Abstract

China is one of the largest consumers of energy globally. The country also emits some of the highest levels of CO2 globally. In 2009, 18% of the world’s total energy was consumed in China and the growth rate of energy consumption in China is 6.4% per year. In recent years, the Chinese government decided to introduce several energy policy instruments to promote energy efficiency. For instance, reduction targets for the level of energy intensity have been defined for provinces in China. However, energy intensity is not an accurate proxy for energy efficiency because changes in energy intensity are a function of changes in several socioeconomic factors. For this reason, in this paper we present an empirical analysis on the measurement of the persistent and transient “underlying energy efficiency” of Chinese provinces. For this purpose, a log-log aggregate energy demand frontier model is estimated by employing data on 29 provinces observed over the period 1996 to 2008. Several econometric model specifications for panel data are used: the random effects model and the true random effects model along with other versions of these models. Our analysis shows that energy intensity cannot measure accurately the level of efficiency in the use of energy in Chinese provinces. Further, our empirical analysis shows that the average value of the persistent “underlying energy efficiency” is around 0.78 whereas the average value of the transient “underlying energy efficiency” is approximately 0.93.

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  • Massimo Filippini & Lin Zhang, 2013. "Measurement of the “Underlying energy efficiency” in Chinese provinces," CER-ETH Economics working paper series 13/183, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    • Handle: RePEc:eth:wpswif:13-183
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    1. Broadstock, David C. & Li, Jiajia & Zhang, Dayong, 2016. "Efficiency snakes and energy ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households," Energy Policy, Elsevier, vol. 91(C), pages 383-396.

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    More about this item

    Keywords

    Chinese energy demand; Stochastic frontier analysis: Underlying energy efficiency; Energy intensity.;
    All these keywords.

    JEL classification:

    • D - Microeconomics
    • D2 - Microeconomics - - Production and Organizations
    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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