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This paper analyses the effect of job accessibility by public and private transport on labour market outcomes in the metropolitan area of Barcelona. Beyond employment, we consider the effect of job accessibility on job-education mismatch, which represents a relevant aspect of job quality. We adopt a recursive system of equations that models car availability, employment and mismatch. Public transport accessibility appears as an exogenous variable in the three equations. Even though it may reflect endogenous residential sorting, falsification proofs suggest that the estimated effect of public transport accessibility is not entirely driven by the endogenous nature of residential decisions.

Public transport smart cards are widely used around the world. However, while they provide information about various aspects of passenger behavior, they have not been properly exploited to predict demand. Indeed, traditional methods in economics employ linear unbiased estimators that pay little attention to accuracy, which is the main problem faced by the sector’s regulators. This paper reports the application of various supervised machine learning (SML) techniques to smart card data in order to forecast demand, and it compares these outcomes with traditional linear model estimates. We conclude that the forecasts obtained from these algorithms are much more accurate.

This study analyses the impact that job accessibility in public transport has on car ownership. An ordered probit explaining the number of cars per household is estimated as a function of head of household characteristics, household characteristics and job accessibility. The data used in the analysis come from the Microcensus of year 2001 of the Spanish Institute of Statistics for the areas of Barcelona and Madrid. Our results show a significant effect of accessibility on car ownership. Additionally, we carried out simulation exercises in which the expected number of vehicles decreases as accessibility improves. For instance, in the case of households living outside the central city, an improvement of accessibility up to the average level of the central city would offset the effect of the number of working adults on the expected number of vehicles.

This study analyses the impact that job accessibility in public transport has on car ownership. An ordered probit explaining the number of cars per household is estimated as a function of head of household characteristics, household characteristics and job accessibility. The data used in the analysis come from the Microcensus of year 2001 of the Spanish Institute of Statistics for the areas of Barcelona and Madrid. Our results show a significant effect of accessibility on car ownership. Additionally, we carried out simulation exercises in which the expected number of vehicles decreases as accessibility improves. For instance, in the case of households living outside the central city, an improvement of accessibility up to the average level of the central city would offset the effect of the number of working adults on the expected number of vehicles.