Estimation of inter-fuel substitution possibilities in China's transport industry using ridge regression

The transport industry is a key driver of the rapid growth of oil demand in China. It accounted for 38.2% of total Chinese oil consumption in 2010, and is consequently a major contributor to greenhouse gas emissions and other pollutants. In order to estimate the potential to lower Chinese dependence on oil and reduce carbon dioxide emission, this study has investigated the potential for inter-fuel substitution between coal, oil, natural gas and electricity in China's transport industry over the period 1980–2010, by employing a log linear translog production and cost function. A ridge regression procedure was adopted to estimate the parameters of the function. Estimation results show that all energy inputs are substitutes, and indicate higher substitution possibilities between oil and natural gas relative to other energy input pairs. Furthermore, the substitution elasticity between oil and electricity in the transport sector is increasing significantly over time. Understanding of the substitution relationship among different fuels is crucial for making relevant policies for optimizing the development mode of Chinese transport industry. - Highlights: • Literature on inter-fuel substitution is limited especially in transport industry. • Translog production function model and ridge regression are used. • Elasticity between different energy input pairs are analyzed. • Understanding of the substitutional relationship is crucial