This study focuses on the sustainability efficiency of China’s transportation system by investigating the relationship between CO₂ emission levels and the respective cargo and passenger turnover volumes for each transport mode from January 1999 to December 2017. A new Robust Bayesian Stochastic Frontier Analysis (RBSFA) is developed, taking carbon inequality into account. In this model, the aggregated variance/covariance matrix for the three classical distributional assumptions of the inefficiency term—Gamma, Exponential, and Half-Normal—is minimized, producing lower Deviance Information Criteria compared to each classical assumption individually.

The results are controlled for the impact of key macroeconomic variables related to fiscal policy, monetary policy, inflationary pressure, and economic activity. Findings indicate that China’s transportation system demonstrates high sustainability efficiency, with relatively small random fluctuations explained by macroeconomic policies. Waterway, railway, and road transport modes improved the sustainability efficiency of cargo traffic, while only the railway mode improved the sustainability efficiency of passenger traffic. However, the air transport mode reduced the sustainability efficiency for both cargo and passenger traffic.

This research supports the formulation of government policies based not only on the internal dynamics of carbon inequality across different transport modes but also on the macroeconomic impacts on China’s transportation sector.

Researcher: Peter Wanke et al.
Brazilian School of Public and Business Administration (FGV EBAPE)

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