Spatial Analysis Of Spatio-temporal Characteristics And Influencing Factors Of China’s Reginal Carbon Productivity

As the core indicator to measure the development of low-carbon economy, carbon productivity reflects the economic output per unit of carbon dioxide emission. In the face of global climate change, promoting energy saving and emission reduction and developing low carbon economy have become a world consensus. As the biggest CO2 emitter and the largest developing country in the world, China’s energy conservation and emission reduction should be carried out on the premise of economic growth. Meanwhile, it is well known that due to its vast territory there is remarkable regional disparity among the economic development and CO2 emissions in China. The issue of spatial heterogeneity and dependence cannot be neglected in policy making. In this context, it is important to analyse some issues of China’s carbon productivity such as variation trend, spatial distribution and influencing factors from the space perspective.By definition, this paper measured the carbon productivity of 30 provinces in China from 1978 to 2013 to reveal the spatiotemporal characteristics like variation trend and spatial distribution. In addition, using the Theil index and convergence models, this paper examined the difference and convergence of China’s reginal carbon productivity, respectively. Furthermore, based on the theoretical analysis of the factors affecting carbon productivity and the spatial spillover effects, using the spatial panel data models and the partial differential effect decomposition method, this paper examined the main factors driving the carbon productivity in China from the spatial spillover perspective. Finally, on the basis of the research results, this paper put forward some feasible measures to improve the carbon productivity. The main conclusions of the study are as follows:(1) In 1997-2013, the carbon productivity of the whole nation and the eastern, central and western regions all show a rising trend, growing at an annual rate of 4.05, 4.29, 4.77 and 2.79 per cent respectively. In terms of spatial distribution pattern, the regional difference of carbon productivity is obvious. The carbon productivity gradually increase from northwest to southeast, with an obvious clustering characteristic. The results of Moran’s I test indicate that there is significant spatial autocorrelation of China’s provincial carbon productivity. And the spatial autocorrelation is very stable, which can be characterized by path dependence or the spatial lock-in effect to some extent.(2) The total difference and convergence of China’s regional carbon productivity mainly stems from the within-region difference of carbon productivity, while the between-region difference begins to expand unceasingly. In the view of the withinregion difference, the difference in the eastern region presents a decreasing tendency, and the difference in the central region decreases insignificantly, while the difference in the western region shows a trend of enlargement. And the contribution of the difference in the western region to the total difference increases obviously.(3) From the view of whole country, the carbon productivity does not show a σ convergence and an absolute β convergence, but a conditional β convergence. And technology progress is an important factor influencing the carbon productivity convergence. From the view of three economic regions, the eastern region exists significant convergence trend, however, the central and western regions do not exist a σ convergence, an absolute β convergence and a conditional β convergence.(4) According to the analysis of our spatial panel model, economic growth, industrial structure, government intervention, technological progress and population size have significantly positive effects on carbon productivity whereas energy consumption structure exert a negative effect on carbon productivity, and the influence of foreign direct investment to carbon productivity is not significant. From the view of spatial spillover effects, the spatial spillovers of China’s regional carbon productivity take place mainly through factors such as economic growth, energy consumption structure, technological progress and government intervention. Among them, economic growth and technological progress have positive spillover effects on carbon productivity whereas energy consumption structure and government intervention have negative spillover effects on carbon productivity.