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Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice

In: New Directions in Spatial Econometrics

Author

Listed:
  • Denis Bolduc

    (Université Laval)

  • Richard Laferrière

    (Université de Montréal)

  • Gino Santarossa

    (Université Laval)

Abstract

In this chapter we use empirical examples to demonstrate the usefulness of the generalized error component framework suggested in Bolduc et al. (1992) for dealing with the problem of correlation among the errors of a regression based on travel flow data. This methodology augments Standard error component decompositions with first-order spatial autoregressive processes, i.e., SAR(l), with the purpose of allowing for the different sources of misspecification generally associated with this type of model. The error component approach splits the error term into a sum of one component related to the zones in origin, one component associated with the zones in destination and a remainder. The interdependencies among the errors are modeled with the help of SAR(l) processes. This decompositional approach extends the previous works by Brandsma and Ketellapper (1979) and Bolduc et al. (1989) which also relied on spatial autoregressive processes to model the error correlation.

Suggested Citation

  • Denis Bolduc & Richard Laferrière & Gino Santarossa, 1995. "Spatial Autoregressive Error Components in Travel Flow Models: An Application to Aggregate Mode Choice," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 4, pages 96-108, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-79877-1_4
    DOI: 10.1007/978-3-642-79877-1_4
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    Citations

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    Cited by:

    1. David M. Brasington & Diane Hite, 2005. "Demand for Environmental Quality: A Spatial Hedonic Approach," Departmental Working Papers 2005-08, Department of Economics, Louisiana State University.
    2. Brasington, David M. & Hite, Diane, 2005. "Demand for environmental quality: a spatial hedonic analysis," Regional Science and Urban Economics, Elsevier, vol. 35(1), pages 57-82, January.
    3. David Brasington, 2005. "School Choice and the Flight to Private Schools: To What Extent Are Public and Private Schools Substitutes?," Departmental Working Papers 2005-02, Department of Economics, Louisiana State University.
    4. David Brasington & Don Haurin, 2005. "Capitalization of Parent, School, and Peer Group Components of School Quality into House Price," Departmental Working Papers 2005-04, Department of Economics, Louisiana State University.
    5. Christoph Hammer & Aurélien Fichet de Clairfontaine, 2016. "Trade Costs and Income in European Regions," Department of Economics Working Papers wuwp220, Vienna University of Economics and Business, Department of Economics.
    6. Frank Goetzke, 2008. "Network Effects in Public Transit Use: Evidence from a Spatially Autoregressive Mode Choice Model for New York," Urban Studies, Urban Studies Journal Limited, vol. 45(2), pages 407-417, February.
    7. F. Bavaud & M. Kordi & C. Kaiser, 2018. "Flow autocorrelation: a dyadic approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(1), pages 95-111, July.
    8. David Brasington & Donald R. Haurin, 2006. "Educational Outcomes and House Values: A Test of the value added Approach," Journal of Regional Science, Wiley Blackwell, vol. 46(2), pages 245-268, May.
    9. Jacob J. de Vries & Peter Nijkamp & Piet Rietveld, 2000. "Alonso's General Theory of Movement: Advances in Spatial Interaction Modeling," Tinbergen Institute Discussion Papers 00-062/3, Tinbergen Institute.
    10. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    11. Wang, Chih-Hao & Akar, Gulsah & Guldmann, Jean-Michel, 2015. "Do your neighbors affect your bicycling choice? A spatial probit model for bicycling to The Ohio State University," Journal of Transport Geography, Elsevier, vol. 42(C), pages 122-130.

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