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A link based network route choice model with unrestricted choice set

  • Fosgerau, Mogens
  • Frejinger, Emma
  • Karlstrom, Anders

This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the multinomial logit form but with infinitely many alternatives. The model can be consistently estimated and used for prediction in a computationally efficient way. Similarly to the path size logit model, we propose an attribute called link size that corrects utilities of overlapping paths but that is link additive. The model is applied to data recording path choices in a network with more than 3,000 nodes and 7,000 links.

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File URL: http://mpra.ub.uni-muenchen.de/48707/1/MPRA_paper_48707.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 48707.

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Date of creation: Jul 2013
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Handle: RePEc:pra:mprapa:48707
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  1. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
  2. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
  3. Mogens Fosgerau & Daniel L. McFadden & Michel Bierlaire, 2012. "Choice Probability Generating Functions," NBER Working Papers 17970, National Bureau of Economic Research, Inc.
  4. Mogens Fosgerau, 2004. "Investigating the distribution of the value of travel time savings," Urban/Regional 0411006, EconWPA.
  5. Akamatsu, Takashi, 1996. "Cyclic flows, Markov process and stochastic traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 30(5), pages 369-386, October.
  6. Flötteröd, Gunnar & Bierlaire, Michel, 2013. "Metropolis–Hastings sampling of paths," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 53-66.
  7. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.
  8. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
  9. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
  10. DeSerpa, A C, 1971. "A Theory of the Economics of Time," Economic Journal, Royal Economic Society, vol. 81(324), pages 828-46, December.
  11. Frejinger, E. & Bierlaire, M., 2007. "Capturing correlation with subnetworks in route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 363-378, March.
  12. David A. Hensher, 2001. "Measurement of the Valuation of Travel Time Savings," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 35(1), pages 71-98, January.
  13. Melo, Emerson, 2012. "A representative consumer theorem for discrete choice models in networked markets," Economics Letters, Elsevier, vol. 117(3), pages 862-865.
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