Exploring carbon emissions, economic growth, energy and R&D investment in China by ARDL approach

This paper examines the causal relationship among economic growth, energy structure, R&D investment and carbon emission in China by using autoregressive distributed lag bounds testing approach of cointegration during the period of 1990-2011. In order to examine this linkage, the authors use the two-step procedures. Firstly, the authors conducted the unit root tests to measure whether the single integrated of time series is not more than 1. Secondly, the authors explore the long-run relationships between the variables by using ARDL bounds testing approach complemented by Johansen-Juselius maximum likelihood procedure in a multivariate framework. The findings are as follows:when carbon emissions and economic growth, respectively, are the dependent variable, the other independent variables show the long-term stability cointegration relationship of the dependent variable. Whether in the short-run or long-run relationship, the impact of economic growth and R&D investment on carbon emission is not statistically significant. In the long term and short term relationships, carbon emissions have a positive impact on the economic growth. However, energy structure has a negative impact on the economic growth. The decrease in energy structure will cause carbon emissions reduction and boost economic growth in both the long-run and short-run period. Therefore, China's government should give more attention to the optimization of energy structure and make a reasonable and feasible energy saving policy.