Recurrence and Eigenfunction Methods for Non-Trivial Models of Discrete Binary Choice

Identification of Discrete Choice Models for Bundles and Binary Games∗

We study nonparametric identification of single-agent discrete choice models for bundles and binary games of complete information. We provide conditions under which we can recover both the interaction effects and the distributions of potentially correlated unobservables across goods in single-agent models and across players in games. We establish similarities in identification between these two...

Binary Choice Models with Discrete Regressors: Identification and Misspecification

In semiparametric binary response models, support conditions on the regressors are required to guarantee point identification of the parameter of interest. For example, one regressor is usually assumed to have continuous support conditional on the other regressors. In some instances, such conditions have precluded the use of these models; in others, practitioners have failed to consider whether...

Non–trivial Intertwined Second–order Recurrence Relations

In a recently published book, it is shown that there are essentially seven different non– trivial systems of three intertwined second–order recurrence relations, but the solutions are not given. In this note we present explicit solutions to all seven systems. AMS Classification: 11B39, 11B37

Discrete Choice Models for Non-Intrusive Quality Assessment

Non-intrusive signal quality assessment in general, and its application to speech signal processing, in particular, builds extensively upon statistical regression models. Commonly, the raw preference scores used for fitting these models belong to a categorical scale. Averaging the scores over a number of test subjects results in smooth, close-to-continuous ratings, thus justifying the use of re...

Data Models for Discrete Choice