This paper discusses the representability of discrete logit-type models including multinomial logit and nested logit model from a mathematical approach. It is shown that the logit-type models can be reconstructed from mathematical approximation theory with sigmoidal functions widely used in Neural Network modeling without the basic assumptions such as IIA and iid, and the distribution (or densi...

Though individual demand and supply equations can readily be expressed in logit models, closed-form solutions for equilibrium shares and prices are intractable due to the presence of products of polynomial and exponential terms. This hinders the employment of logit models in theoretical studies, and also makes it difficult to develop reduced-form expressions for share and price as a function of...

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimat...

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-lognormal random effects model, a two-part logit-truncated normal random effects model, a two-pa...

Logit dynamics [Blume, Games and Economic Behavior, 1993] is a randomized best response dynamics where at every time step a player is selected uniformly at random and she chooses a new strategy according to the “logit choice function”, i.e. a probability distribution biased towards strategies promising higher payoffs, where the bias level corresponds to the degree of rationality of the agents. ...

We estimate an insurer-specific preference function which rationalizes hospital referrals for privately insured births in California. The function is additively separable in: a hospital price paid by the insurer, the distance traveled, and plan- and severity-specific hospital fixed effects (capturing hospital quality). We use an inequality estimator that allows for errors in price and detailed ...

In 2011, Lake Erie experienced a record-setting harmful algal bloom (HAB), posing significant risks to ecosystem services, including its $1.5 billion sport fishing industry. Using a mail survey of 3,000 Ohio recreational anglers and a choice experiment, this article provides the first empirical evidence in the US to link HABs to damages to Great Lakes recreational anglers. We account for the he...

The Multinomial Logit, discrete choice model of transport demand, has several restrictions when compared with the more general Multinomial Probit model. The most famous of these are that unobservable components of utilities should be mutually independent and homoskedastic. Correlation can be accommodated to a certain extent by the Hierarchical Logit model, but the problem of heteroskedasticity ...

Logit dynamics are a family of randomized best response dynamics based on the logit choice function [21] that is used to model players with limited rationality and knowledge. In this paper we study the all-logit dynamics, where at each time step all players concurrently update their strategies according to the logit choice function. In the well studied one-logit dynamics [7] instead at each ste...

The currently available transport modeling tools are used to evaluate the effects of behavior change. aim this study is analyze interaction between mode choice and travel an individual—more specifically, identify which variables has greatest effect on choice. This realized by using a multinomial logit model (MNL) nested (NL) based utility function. function contains activity characteristics, tr...