How McFadden met Rockafellar and learned to do more with less

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Standard

How McFadden met Rockafellar and learned to do more with less. / Sørensen, Jesper R.-V.; Fosgerau, Mogens.

I: Journal of Mathematical Economics, Bind 100, 102629, 2022.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Sørensen, JR-V & Fosgerau, M 2022, 'How McFadden met Rockafellar and learned to do more with less', Journal of Mathematical Economics, bind 100, 102629. https://doi.org/10.1016/j.jmateco.2021.102629

APA

Sørensen, J. R-V., & Fosgerau, M. (2022). How McFadden met Rockafellar and learned to do more with less. Journal of Mathematical Economics, 100, [102629]. https://doi.org/10.1016/j.jmateco.2021.102629

Vancouver

Sørensen JR-V, Fosgerau M. How McFadden met Rockafellar and learned to do more with less. Journal of Mathematical Economics. 2022;100. 102629. https://doi.org/10.1016/j.jmateco.2021.102629

Author

Sørensen, Jesper R.-V. ; Fosgerau, Mogens. / How McFadden met Rockafellar and learned to do more with less. I: Journal of Mathematical Economics. 2022 ; Bind 100.

Bibtex

@article{7140332edacb425da48a8b8fe5dc0b8d,
title = "How McFadden met Rockafellar and learned to do more with less",
abstract = "We exploit the power of convex analysis to synthesize and extend a range of important results concerning the additive random utility model of discrete choice. With no restrictions on the joint distribution of random utility components or the functional form of systematic utility components, we formulate general versions of the Williams-Daly-Zachary theorem for demand and the Hotz-Miller demand inversion theorem. Based on these theorems, we provide necessary and sufficient conditions for demand and its inverse to reduce to functions. These conditions jointly imply that demand is a continuous function with a continuous inverse.",
keywords = "Faculty of Social Sciences, Additive random utility model, discrete choice, convex duality, demand inversion, partial indentification",
author = "S{\o}rensen, {Jesper R.-V.} and Mogens Fosgerau",
year = "2022",
doi = "10.1016/j.jmateco.2021.102629",
language = "English",
volume = "100",
journal = "Journal of Mathematical Economics",
issn = "0304-4068",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - How McFadden met Rockafellar and learned to do more with less

AU - Sørensen, Jesper R.-V.

AU - Fosgerau, Mogens

PY - 2022

Y1 - 2022

N2 - We exploit the power of convex analysis to synthesize and extend a range of important results concerning the additive random utility model of discrete choice. With no restrictions on the joint distribution of random utility components or the functional form of systematic utility components, we formulate general versions of the Williams-Daly-Zachary theorem for demand and the Hotz-Miller demand inversion theorem. Based on these theorems, we provide necessary and sufficient conditions for demand and its inverse to reduce to functions. These conditions jointly imply that demand is a continuous function with a continuous inverse.

AB - We exploit the power of convex analysis to synthesize and extend a range of important results concerning the additive random utility model of discrete choice. With no restrictions on the joint distribution of random utility components or the functional form of systematic utility components, we formulate general versions of the Williams-Daly-Zachary theorem for demand and the Hotz-Miller demand inversion theorem. Based on these theorems, we provide necessary and sufficient conditions for demand and its inverse to reduce to functions. These conditions jointly imply that demand is a continuous function with a continuous inverse.

KW - Faculty of Social Sciences

KW - Additive random utility model

KW - discrete choice

KW - convex duality

KW - demand inversion

KW - partial indentification

U2 - 10.1016/j.jmateco.2021.102629

DO - 10.1016/j.jmateco.2021.102629

M3 - Journal article

VL - 100

JO - Journal of Mathematical Economics

JF - Journal of Mathematical Economics

SN - 0304-4068

M1 - 102629

ER -

ID: 288611818