Modeling the Impact of Macroeconomic Factors on Multimodal Transport Demand: A Cointegration Approach

In this paper we investigate the relationships between multimodal transportation demand and macroscopic socio-economic variables in Beijing using a time-series cointegration and error correction approach. The results indicate that gross domestic product (GDP), and the ratio of urban to total population, have co-integrating relationships with the highway and civil aviation passenger turnover rate, respectively, while urban public transport ridership exhibits long-term equilibrium with GDP and registered private cars. As expected, long run demand elasticities are higher than their short run counterparts except for the case of bus ridership. In addition, demand elasticity varies greatly among different modes of transport, demonstrating the necessity to consider the performances in various modes separately. Lastly, the error correction model (ECM) shows that the coefficients of the residuals representing the speed of adjustment towards the long run equilibrium are negative and statistically significant, confirming the co-integrating relationships mentioned above. The findings of this study can help better understand the determinants of transport demand and are also helpful to policy makers adopting efficient planning and operation strategies.