How McFadden met Rockafellar and learned to do more with less

Journal of Mathematical Economics(2021)

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摘要
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.
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关键词
Additive random utility model,Discrete choice,Convex duality,Demand inversion,Partial identification
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