The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: Evidence from dynamic panel quantile regression

Abstract

The transport sector is becoming a key sector for China to accomplish its targets for reducing carbon emission intensity (CEI). Identifying the dominant factors driving CEI of the transport sector is important for CEI mitigation. This paper applied dynamic panel quantile regression to explore the effect of driving factors on CEI in the Chinese transport sector at the provincial level during 2000–2016. The empirical findings indicate that economic growth has a positive influence on CEI at low quantiles, whereas this effect is the opposite at high quantiles. Further, the findings show an inverted U-shaped pattern between economic growth and CEI at low quantiles, which validates the Environmental Kuznets Curve hypothesis in low-CEI provinces. Energy intensity positively influences CEI, with the greatest impact occurring at higher quantiles. Among the lowest CEI provinces, private vehicles and cargo turnover appear to contribute to CEI, and a positive impact of urbanization exists, except at the 5th and 30th quantiles. In conclusion, policy implications for effectively promoting the CEI abatement in the transport sector are discussed.