As shown by Guimaraes, Figueiredo and Woodward (2003), a particular class of conditional logit models yield identical parameter estimates to a Poisson count data model. In Schmidheiny and Brülhart (2011), we have pointed out that the conditional logit model and the Poisson model can be seen as polar cases of a continuum of intermediate cases which emerge from a random utility nested logit model...

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...

We estimate random-parameter logit models of anglers ' choice of fishing site. The models generalize logit by allowing coefficients to vary randomly over anglers rather than being fixed. The models do not exhIbit the restrictive "independence from irrelevant alternatives property of logit and can represent any substitution pattern. Estimation explicitly accounts for the fact that the variation ...

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...

in order to investigate effective factors on bread waste and determine effect genial of each factor on probability of being each family in three categories of low-medium, high and extra high bread waste, the order logit model and the 352 families data from mashad city were taken in use. the samples have been selected using a simple random sampling method. the survey of marginal effect in order ...

The spatial model has been in use in political science for close to 30 years, and in that period it has achieved a place of prime importance as our paradigm of the process of candidatechoice used by voters. For much of this time political scientists have estimated models of candidatechoice using binary logit or probit, even in cases where there were more than two choices facing voters. Recently...

We compare multinomial logit and mixed logit models for data on California households’ revealed and stated preferences for automobiles. The stated preference data elicited households’ preferences among gas, electric, methanol, and CNG vehicles with various attributes. The mixed logit models provide a much better fit to these data, and forecasting exercises demonstrate substantial differences be...

This chapter examines different models commonly used to model probabilistic choice, such as eg the choice of one type of transportation from among many choices available to the consumer. Section 1 discusses derivation and limitations of conditional logit models. Section 2 discusses probit models and Section 3 discusses the nested logit (generalized extreme value models), which address some of t...