Forecasting the impact of transport improvements on commuting and residential choice

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Abstract

This paper develops a probabilistic, competing-destinations, assignment model that predicts changes in the spatial pattern of the working population as a result of transport improvements. The choice of residence is explained by a new non-parametric model, which represents an alternative to the popular multinominal logit model. Travel times between zones are approximated by a normal distribution function with different mean and variance for each pair of zones, whereas previous models only use average travel times. The model's forecast error of the spatial distribution of the Dutch working population is 7% when tested on 1998 base-year data. To incorporate endogenous changes in its causal variables, an almost ideal demand system is estimated to explain the choice of transport mode, and a new economic geography inter-industry model (RAEM) is estimated to explain the spatial distribution of employment. In the application, the model is used to forecast the impact of six mutually exclusive Dutch core-periphery railway proposals in the projection year 2020. © Springer-Verlag 2006.

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Elhorst, J. P., & Oosterhaven, J. (2006). Forecasting the impact of transport improvements on commuting and residential choice. Journal of Geographical Systems, 8(1), 39–59. https://doi.org/10.1007/s10109-005-0015-4

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