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ON THE REPRESENTATION OF THE NESTED LOGIT MODEL

Published online by Cambridge University Press:  11 January 2021

Alfred Galichon*
Affiliation:
New York University Sciences Po
*
Address correspondence to Alfred Galichon, Departments of Economics and Mathematics, New York University, New York, NY, USA; e-mail: [email protected].

Abstract

In this paper, we give a two-line proof of a long-standing conjecture of Ben-Akiva in his 1973 PhD thesis regarding the random utility representation of the nested logit model, thus providing a renewed and straightforward textbook treatment of that model. As an application, we provide a closed-form formula for the correlation between two Fréchet random variables coupled by a Gumbel copula.

Type
MISCELLANEA
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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Footnotes

Date: November 12, 2020 (First draft: 7/2019). Funding from NSF grant DMS-1716489 as well as ERC grant CoG-866274 is acknowledged. The author is thankful to the editor (Peter Phillips) and two anonymous reviewers, as well as Kenneth Train, Mogens Fosgerau, Lars-Göran Mattsson, Bernard Salanié and Jörgen Weibull for helpful comments, and especially to Matt Shum for pointing out the important reference to Cardell's paper after a first version of this paper was circulated.

References

REFERENCES

Ben-Akiva, M. (1973). The structure of travel demand models. PhD thesis, MIT.Google Scholar
Ben-Akiva, M. & Lerman, S. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press.Google Scholar
Bochner, S. (1937). Completely monotone functions of the Laplace operator for torus and sphereDuke Mathematical Journal 3, 488502.CrossRefGoogle Scholar
Cardell, S. (1997). Variance components structures for the extreme-value and logistic distributions with application to models of heterogeneity. Econometric Theory 13(2), 185213.CrossRefGoogle Scholar
Dishon, M. & Bendler, J. (1990). Tables of the inverse Laplace transform of the function e−s/β Journal of Research of the National Institute of Standards and Technology 95, 433467.CrossRefGoogle Scholar
Feller, W. (1971). An Introduction to Probability Theory and its Applications, vol. 2, 2nd Edition. Wiley.Google Scholar
Fosgerau, M., Lindberg, P.-O., Mattsson, L.-G., & Weibull, J. (2018). A note on the invariance of the distribution of the maximumJournal of Mathematical Economics 74, 5661.CrossRefGoogle Scholar
Hårsman, B. & Mattsson, L.-G.. Analyzing the returns to entrepreneurship by a modified Lazear model. Small Business Economics, first published online 14 August 2020. https://doi.org/10.1007/s11187-020-00377-1.CrossRefGoogle Scholar
Humbert, P. (1945). Nouvelles correspondances symboliques. Bulletin de la Société Math ématique de France 69, 121129.Google Scholar
Mattsson, L.-G., Weibull, J., & Lindberg, P.-O. (2014). Extreme values, invariance and choice probabilitiesTransportation Research Part B 59, 8195.CrossRefGoogle Scholar
McFadden, D. (1978). Modeling the choice of residential location. In Karlquist, A., et al. (ed.), Spatial Interaction Theory and Residential Location. North Holland.Google Scholar
Pollard, H. (1946). The representation of e−x/λ as a Laplace integral. Bulletin of the American Mathematical Society 52(10), 908910.CrossRefGoogle Scholar
Ridout, M. S. (2009). Generating random numbers from a distribution specified by its Laplace transform. Statistics and Computing 19, 439450.CrossRefGoogle Scholar
Tiago de Oliveira, J. (1958). Extremal distributions. Revista de Faculdada du Ciencia, Lisboa, Serie A 7, 215227.Google Scholar
Tiago de Oliveira, J. (1997). Statistical Analysis of the Extreme. Pendor.Google Scholar