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 -