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Aggregation with multinomial probit and estimation of disaggregate models with aggregate data: A new methodological approach

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  • Bouthelier, Fernando
  • Daganzo, Carlos F.

Abstract

This paper describes an analytic aggregation procedure for disaggregate demand models similar to the one proposed in earlier publications by Westin (1974) and McFadden and Reid (1975). The technique, which uses a multivariate normal approximation for the distribution of the vector of attributes, is based on the multinomial profit algorithm proposed by Daganzo, Bouthelier and Sheffi (1977) and can be applied to an arbitrary number of alternatives. The procedure is computationally so efficient that it enables us to calibrate disaggregate models with aggregate data by maximum likelihood using the same or slightly modified codes developed for disaggregated data. The paper also contains a small scale numerical example intended to illustrate the important highlights of the aggregation-estimation problem.

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  • Bouthelier, Fernando & Daganzo, Carlos F., 1979. "Aggregation with multinomial probit and estimation of disaggregate models with aggregate data: A new methodological approach," Transportation Research Part B: Methodological, Elsevier, vol. 13(2), pages 133-146, June.
    • Handle: RePEc:eee:transb:v:13:y:1979:i:2:p:133-146
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    Cited by:

    1. Richard Connors & David Watling, 2015. "Assessing the Demand Vulnerability of Equilibrium Traffic Networks via Network Aggregation," Networks and Spatial Economics, Springer, vol. 15(2), pages 367-395, June.
    2. Yasemin Boztug & Lutz Hildebrandt, 2005. "A Market Basket Analysis Conducted with a Multivariate Logit Model," SFB 649 Discussion Papers SFB649DP2005-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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