The Flexible Inverse Logit (FIL) Model

A Generalization of Quantal Response Equilibrium via Perturbed Utility

“…We also provide the reader with several classes of perturbations that allow flexibility in best responses and can be used in the study of games. Other perturbations that may be useful are developed for discrete choice analysis in [9,10]. Although many of the models presented have many parameters, one can simplify estimation by making homogeneity assumptions across individuals.…”

“…On the practical side, it may be easier to place restrictions on perturbation functions than restricting the additive error term of QRE since analytical results for integrating error distributions are known only in some special cases. In contrast, rich classes of analytical perturbation functions are studied in [9,10]. These perturbation functions can be seen as generalizations of the entropy function that is often used to study limited attention.…”

Identification of Random Coefficient Latent Utility Models

“…Heckman [2001] attributes the first use toDomenich and McFadden [1975] in economics. 2 SeeNevo [2000], p. 524-526. il Kim [2014 has established identification in the special case where intercept location coefficients are 0.3 Recent work includesGentzkow [2007],McFadden and Fosgerau [2012],Fosgerau et al [2019],Allen and Rehbeck [2019a],Ershov et al [2018],Monardo [2019],Iaria and Wang [2019], andWang [2020]. This work is an outgrowth of the discrete choice additive random utility model[McFadden, 1981] and differs from classic continuous demand systems (e.g Deaton and Muellbauer [1980]…”