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This paper adopts a dynamic general nesting spatial panel data model with common factors to explore the effect of population density, real household income per capita, car fleet per capita, and real price of gasoline on departmental traffic per light vehicle in France over the period 1990–2009. Spatial heterogeneity is modeled by a translog function in the first three explanatory variables, which are dominated by variation in the cross-sectional domain, while the real price of gasoline, which is dominated by variation in the time domain, is treated as an observable common factor. Additional unobservable common factors are controlled for by principal components with heterogenous coefficients, building on previous work of Shi and Lee (2017a), thereby, generalizing the dynamic spatial panel data model with spatial and time period fixed applied in recent studies. It is found that the spatial lag in the dependent variable becomes insignificant due to these extensions. This paper explains the wider implications of this finding for spatial econometric modeling of cross-sectional dependence. In addition, the elasticities of the first three explanatory variables are shown to vary across space and time and to follow a plausible structure. Among other, an important result is that the long run income elasticity of car traffic diminished from 1.0 in 1990 to 0.4 in 2003, and then remained almost constant until the end of our sample period in 2009, i.e., during the peak-car traffic period. [ABSTRACT FROM AUTHOR]

This study analyses the impacts of changes in fares, service supply, income and other factors on the demand for public transport on the basis of panels of English counties and French urban areas. The analysis is based on dynamic econometric models, so that both short- and long-run elasticities are estimated. Conventional approaches (i.e. fixed- and random-effect models) rely on the hypothesis that elasticities are the same for all areas. Having shown that this hypothesis is not valid for these data sets, the heterogeneity amongst areas is accounted for using a random-coefficients approach, and Bayesian shrinkage estimators.Estimated elasticities for France and England are compared, by using a common set of variables, similar time period and a common methodology. The results show a considerable variation in elasticities among areas within each country. The major conclusion is that public transport demand is relatively sensitive to fare changes, so that policy measures aimed at fare reduction (subsidisation) can play a substantial role in encouraging the use of public transport, thus reducing the use of private cars. [Copyright &y& Elsevier]