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2017•Energy ProcediaOpen access

Analysis of Agriculture Total-Factor Energy Efficiency in China Based on DEA and Malmquist indices

Nan Li, Yuqing Jiang, Zhixin Yu, Liwei Shang

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Abstract

With the panel data of 30 administrative regions in China, this paper first used mechanical power, thermal energy, chemistry, biodynamic energy as input index, gross output value of agriculture, forestry, animal husbandry and fishery value as output index, built the DEA model to analyze the agricultural total factor energy efficiency(TFEE) of each province from 1997 to 2014. By using the Malmquist index, the total factor productivity(TFP) is decomposed into the technology progress change(TPCH) and the technology efficiency change(TECH) from 1997 to 2014. The results show that the average agricultural total factor energy efficiency level in the eastern region is the highest, followed by the central region, the western region is the lowest. China’s agricultural TFP has the slow growth trend in the fluctuations, which was powered by TECH.

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What this paper is about

With the panel data of 30 administrative regions in China, this paper first used mechanical power, thermal energy, chemistry, biodynamic energy as input index, gross output value of agriculture, forestry, animal husbandry and fishery value as output index, built the DEA model to analyze the agricultural total factor energy efficiency(TFEE) of each province from 1997 to 2014. By using the Malmquist index, the total factor productivity(TFP) is decomposed into the technology progress change(TPCH) and the technology efficiency change(TECH) from 1997 to 2014. The results show that the average agricultural total factor energy efficiency level in the eastern region is the highest, followed by the central region, the western region is the lowest. China’s agricultural TFP has the slow growth trend in the fluctuations, which was powered by TECH.

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Available abstract

With the panel data of 30 administrative regions in China, this paper first used mechanical power, thermal energy, chemistry, biodynamic energy as input index, gross output value of agriculture, forestry, animal husbandry and fishery value as output index, built the DEA model to analyze the agricultural total factor energy efficiency(TFEE) of each province from 1997 to 2014. By using the Malmquist index, the total factor productivity(TFP) is decomposed into the technology progress change(TPCH) and the technology efficiency change(TECH) from 1997 to 2014. The results show that the average agricultural total factor energy efficiency level in the eastern region is the highest, followed by the central region, the western region is the lowest. China’s agricultural TFP has the slow growth trend in the fluctuations, which was powered by TECH.

Key concepts: Total factor productivity, Malmquist index, Agriculture, Agricultural economics, Animal husbandry, Index (typography), Productivity, Panel data

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