关键词: 清洁能源, 要素配置结构, 碳生产率, 人力资本, 中国

Abstract:

Improving China's carbon productivity is regarded as a significant move to achieve the win-win goal of carbon emissions reduction and economic sustainable growth for China's low-carbon transition. This paper introduces the energy and human capital features （including education and learning by doing）into the C-D production function to obtain the baseline and improved carbon productivity determining equations. We also empirically examined the role played by clean energy use and factor allocation structure on carbon productivity using provincial panel data of Mainland China covering the period from 2003 to 2012. Our empirical results showed that the effect of clean energy use has emerged to improve China's provincial carbon productivity;furthermore,the effect is significantly different in regions of different clean energy development stages. Sub-regional regression results showed the effect of clean energy is smaller in the Eastern region than the Midwest region. Factor allocation structure is an important condition affecting China's provincial carbon productivity. Note that there is a significant positive correlation between capital-energy ratio （K/E）and labor-energy ratio （L/E）and carbon productivity,respectively,but a declining labor-energy ratio has adversely affected China's carbon productivity growth in recent years. Improvement of education human capital contributes to carbon productivity growth,however,the contribution is extremely weak. “Learning by doing （LBD）” did not support the expected positive impact on China's carbon productivity as the carbon productivity determining equation previously showed. In addition,we discussed the problem of endogeneity in our models. To ensure China's carbon productivity growth,we should expand the supply scale of clean energy （i.e.,nuclear,wind and solar）continuously and adjust the factor allocation structure prudentially.

Key words: clean energy, factor allocation structure, carbon productivity, human capital, China