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The main determinants of the demand for public transport: a comparative analysis of England and France using shrinkage estimators

  • Bresson, Georges
  • Dargay, Joyce
  • Madre, Jean-Loup
  • Pirotte, Alain

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.

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Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

Volume (Year): 37 (2003)
Issue (Month): 7 (August)
Pages: 605-627

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Handle: RePEc:eee:transa:v:37:y:2003:i:7:p:605-627
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  1. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-94, September.
  2. Lawrence R. Klein, 1989. "Developments and Prospects in Macroeconometric Modeling," Eastern Economic Journal, Eastern Economic Association, vol. 15(4), pages 287-304, Oct-Dec.
  3. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
  4. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  5. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  6. Swamy, P A V B & Tavlas, George S, 1995. " Random Coefficient Models: Theory and Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 9(2), pages 165-96, June.
  7. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2003. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," Empirical Economics, Springer, vol. 28(4), pages 795-811, November.
  8. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
  9. Joyce M. Dargay & Mark Hanly, 2002. "The Demand for Local Bus Services in England," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 36(1), pages 73-91, January.
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