Abstract
This paper examines the relationship between Transportation Services Index (TSI), Dow Jones Transportation Average Index (DJT), and Industrial Production Index (IND) for the United States of America by using monthly data in the period from January 2000 to March 2019. The long-run nexus is demonstrated through the cointegration test and dynamic cointegrating regression (Dynamic OLS), both with structural breaks. The results show that the long-run relations proved by both tests from IND to TSI, IND to DJT, and two-sided between DJT and TSI. More importantly, the Granger-causality relationship is revealed with the forward, rolling, and recursive evolving window algorithms. This is the first study in the literature investigating the causality ties in transportation measures using the novel econometric methodology, following the algorithms. The rolling and recursive causality results detect bi-directional causality between IND and TSI, IND and DJT, and TSI and DJT. Then we come up with some suggestions that the transportation institutions should modulate the transportation sector's financial structure and intensify to adjust industry structures within transportation mobility before, during, and after recessionary periods.