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Discrete choice theory, information theory and the multinomial logit and gravity models


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  • Anas, Alex


The strong "similarity" between "information minimizing" and "utility maximizing" models of spatial interaction has been known for some time (see Anas 1975, Williams, 1977), but the extent of this "similarity" has been underestimated. This paper proves that the two approaches are identical in that the multinomial logit model can be derived and identically estimated by either method. It is also proved that the doubly-constrained gravity model derived by Wilson (1967) is identical to a multinomial logit model of joint origin-destination choice, consistent with stochastic utility maximization. It follows that behaviorally valid "gravity models" can be estimated from disaggregated data on individual choices. In closure, "behavioral demand modeling", which follows McFadden (1973), and "entropy-maximizing modeling", which follows Wilson (1967), should be seen as two equivalent views of the same problem. The behavioral content of models estimated by either approach is entirely determined by the model specification and data aggregation beliefs of the analysts, and not by any inherent structural property of the models themselves.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 17 (1983)
Issue (Month): 1 (February)
Pages: 13-23

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Handle: RePEc:eee:transb:v:17:y:1983:i:1:p:13-23

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Cited by:
  1. Miren Lafourcade & Jacques-François Thisse, 2008. "New economic geography: A guide to transport analysis," Working Papers halshs-00586878, HAL.
  2. Eliasson, Jonas & Mattsson, Lars-Göran, 2000. "A model for integrated analysis of household location and travel choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 375-394, June.
  3. Jan Ubøe & Inge Thorsen & David McArthur, 2011. "Modelling intra-regional geographic mobility in a rural setting," ERSA conference papers ersa11p1243, European Regional Science Association.
  4. Akamatsu, Takashi & Takayama, Yuki & Ikeda, Kiyohiro, 2009. "Spatial Discounting, Fourier, and Racetrack Economy: A Recipe for the Analysis of Spatial Agglomeration Models," MPRA Paper 21738, University Library of Munich, Germany, revised 25 Dec 2009.
  5. A. Prinzie & D. Van Den Poel, 2007. "Random Forrests for Multiclass classification: Random Multinomial Logit," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/435, Ghent University, Faculty of Economics and Business Administration.
  6. Alisdair McKay & Filip Matejka, 2011. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," Boston University - Department of Economics - Working Papers Series WP2011-026, Boston University - Department of Economics.
  7. Andersson, Jonas & Jörnsten, Kurt & Strandenes, Siri Pettersen & Ubøe, Jan, 2009. "Modeling Freight Markets for Coal," Discussion Papers 2008/26, Department of Business and Management Science, Norwegian School of Economics.
  8. Jens Petter Gitlesen & Inge Thorsen & Jan Ubøe, 2004. "Misspecifications in modelling journeys to work," ERSA conference papers ersa04p420, European Regional Science Association.
  9. Babri, Sahar & McArthur, David Philip & Thorsen, Inge & Ubøe, Jan, 2013. "Optimum congestion pricing in a complex network," Discussion Papers 2013/4, Department of Business and Management Science, Norwegian School of Economics.
  10. Marc Gaudry & Emile Quinet, 2012. "Shannon's measure of information, path averages and the origins of random utility models in transport itinerary or mode choice analysis," PSE Working Papers halshs-00713168, HAL.
  11. Martínez, Francisco J. & Henríquez, Rodrigo, 2007. "A random bidding and supply land use equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 41(6), pages 632-651, July.
  12. Jörnsten, Kurt & Ubøe, Jan, 2005. "Efficient Statistical Equilibria in Markets," Discussion Papers 2005/2, Department of Business and Management Science, Norwegian School of Economics.
  13. Lefèvre, Benoit, 2009. "Long-term energy consumptions of urban transportation: A prospective simulation of "transport-land uses" policies in Bangalore," Energy Policy, Elsevier, vol. 37(3), pages 940-953, March.
  14. Jörnsten, Kurt & Ubøe, Jan, 2010. "Quantification of preferences in markets," Journal of Mathematical Economics, Elsevier, vol. 46(4), pages 453-466, July.
  15. Konno, Tomohiko, 2012. "An alternative explanation for the logit form probabilistic choice model from the equal likelihood hypothesis," Economics Letters, Elsevier, vol. 115(3), pages 519-522.
  16. Chang, Justin Sueun & Mackett, Roger Laurence, 2006. "A bi-level model of the relationship between transport and residential location," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 123-146, February.
  17. Glenn, Paul & Thorsen, Inge & Ubøe, Jan, 2004. "Wage payoffs and distance deterrence in the journey to work," Transportation Research Part B: Methodological, Elsevier, vol. 38(9), pages 853-867, November.
  18. Marc Gaudry & Emile Quinet, 2012. "Shannon's measure of information, path averages and the origins of random utility models in transport itinerary or mode choice analysis," Working Papers halshs-00713168, HAL.
  19. Gitlesen, Jens Petter & Thorsen, Inge & Ubøe, Jan, 2004. "Misspecifications due to aggregation of data in models for journeys-to-work," Discussion Papers 2004/13, Department of Business and Management Science, Norwegian School of Economics.
  20. Uboe, Jan & Lillestol, Jostein, 2007. "Benefit efficient statistical distributions on patient lists," Journal of Health Economics, Elsevier, vol. 26(4), pages 800-820, July.


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