Evaluation of the relationship between energy consumption, economic growth, and CO2 emissions in China’ transport sector: the FMOLS and VECM approaches

Abstract

Transport sustainability is an important foundation for achieving sustainable development in an economy. Particularly, environmental policies cannot overlook the growing importance in the transport sector as the economy expands. In this context, it is necessary to investigate the relationship between transport energy consumption (TEN), transport economic growth (TGDP), and transport CO2 emissions (TCE) to formulate the reasonable and specific transport policies. This paper investigated the long-run elasticity and causality between TEN, TGDP, and TCE for the case of China using the panel data covering 30 provincial regions during the period 2004–2016. Firstly, the stationary of each variable series was examined using the panel unit root test. Secondly, the cointegrating relationship in bivariate models was investigated by employing the panel Pedroni cointegration test. Thirdly, based on the fully modified ordinary least squares (FMOLS), the long-run elasticity coefficients in bivariate models were estimated. Finally, the panel Granger causality test based on the vector error correction model was utilized to determine whether the causality existed between the variables. The empirical results indicated that: (1) each variable was found to be integrated of order one, and the cointegrating relationship existed in all bivariate modes. (2) The panel FMOLS tests revealed that the long-run elasticity of TCE to TEN was almost equal to the long-run elasticity of TEN to TCE; the long-run elasticity of TCE to TGDP was significantly higher than the long-run elasticity of TGDP to TCE; and the long-run elasticity of TEN to TGDP was significantly higher than the long-run elasticity of TGDP to TEN. (3) Importantly, the bidirectional causal relationships existed between the TEN, TGDP, and TCE both in the short-run and in the long-run.