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In this paper, we use the Meta regression analysis method to carry out a quantitative research on 39 domestic articles which are about the influences of technological progress on China’s energy efficiency. It is aimed at exploring the influences of differences in model design, data selection and evaluation method on empirical results. The results show that, in terms of energy efficiency measures, selecting the absolute value gets better empirical results than using the relative amount, while higher utility value will be achieved in case of relative amount of technological progress variable than in case of level value. The industrial structure with the proportion of the secondary industry as measurement increases the bounce-back effect of technological progress on energy efficiency, thus reducing the function effect of technological progress on energy efficiency. But energy price and human capital can make the results more valuable. Furthermore, whether selecting panel data or provincial data, sample data selection will not affect the empirical research results. Additionally, selecting tobit model and considering lagging factors in model design can increase the significance of results.

Keywords

Technological Progress, Energy Efficiency, Meta Regression Analysis.
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