One of the main criticisms to game theory concerns the assumption of full rationality. Logit dynamics is a decentralized algorithm in which a level of irrationality (a.k.a. “noise”) is introduced in players’ behavior. In this context, the solution concept of interest becomes the logit equilibrium, as opposed to Nash equilibria. Logit equilibria are distributions over strategy profiles that poss...

Empirical studies on household car ownership have used two types of discrete choice modelling structures, the ordered and the unordered. In ordered structures such as the ordered logit and ordered probit models, the choice of the number of household-vehicles arises from a uni-dimensional latent index that reflects the propensity of a household to own vehicles. Unordered response models, on the ...

In an environment with strategic interaction, multiple equilibria yields a coordination problem and strategic uncertainty, even in the idealized setting of complete information. The resulting disequilibrium of beliefs leads to coordination failure, as demonstrated by many experiments. This paper examines two such coordination problems: the threshold game with a unitary public good and the marke...

The study analyzed farm households’ access and utilization of government health facilities in Kogi State, Nigeria. Specifically, it described the socioeconomic characteristics of farm households, determined the level of accessibility to health facilities by farm households, and determined the factors that drive farm households’ utilization of government health facilities. A two staged random sa...

Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of two or more categories an outcome of interest lies. For binary data (two categories) probit and logit models or semiparametric methods are used. For multinomial data (more than two categories) that are unordered, common models are multinomial and...

We consider the assortment optimization problem under the classical two-level nested logit model. We establish a necessary and sufficient condition for the optimal assortment, and use this optimality condition to develop a simple greedy algorithm that iteratively removes at most one product from each nest, until the optimality condition is satisfied. Our algorithm also exploits the beautiful “l...