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THE LOGIT AS A MODEL OF PRODUCT DIFFERENTIATION

Oxford Economic Papers, 1992
The logit discrete choice model is argued to be flexible, tractable, and intuitively sound as a demand model of product differentiation under oligopoly. The free entry equilibrium product range is greater than or less than the social optimum, depending on cost and demand conditions and the degree of heterogeneity of consumer tastes.
Anderson, Simon P, De Palma, Andre
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Efficient MCMC for Binomial Logit Models

ACM Transactions on Modeling and Computer Simulation, 2013
This article deals with binomial logit models where the parameters are estimated within a Bayesian framework. Such models arise, for instance, when repeated measurements are available for identical covariate patterns. To perform MCMC sampling, we rewrite the binomial logit model as an augmented model which involves some latent variables called random ...
Agnes Fussl   +2 more
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Interpreting logit models

The Stata Journal: Promoting communications on statistics and Stata, 2022
The parameters of logit models are typically difficult to interpret, and the applied literature is replete with interpretive and computational mistakes. In this article, I review a menu of options to interpret the results of logistic regressions correctly and effectively using Stata.
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A Representative Consumer Theory of the Logit Model

International Economic Review, 1988
Discrete choice models (to be more precise: logit models) are usually employed to describe consumers' behavior when they are faced with a variety of mutually exclusive choices. Within this framework, total consumption is treated as given. In the present paper the authors first derive the demand functions and the direct utility function for a ...
Anderson, Simon Peter   +2 more
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Testing logit models in practice

Empirical Economics, 1991
The aim of the paper is to provide the practioner with easily implementable procedures, both numerical and graphical, to test the specification of the dichotomous, linear-in-coefficents logit model. We discuss the performance of these asymptotic methods in small samples on the basis of Monte-Carlo simulations and apply them to a cross-section study of ...
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The Logit Model

1990
In chapters 4, 5 and 6 the categorical variables appeared in the model in a symmetrical way. In many situations, for example in examples 6.1 and 6.2 in chapter 6, one of the variable is of special interest. For the survival data in example 6.1, survival is the variable of special interest, and the problem is to study if the other three variables have ...
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A polarized logit model

Transportation Research Part A: Policy and Practice, 2013
A novel logit-type discrete choice model is presented whose distinctive characteristic is that it "polarizes" or forces the prediction of choice probabilities towards values of 0 or 1. In real-world empirical tests this property enabled the new formulation, which we call the polarized logit model (PLM), to outperform the predictive capacity of other ...
De Grange, Louis   +3 more
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Generalized logit model

Transportation Research Part B: Methodological, 1991
The logit model is the simplest and best-known probabilistic choice model. Nevertheless according to the deficient flexibility there are problems of making use of the multinomial logit model. In this paper a generalized logit model, which is essentially more flexible than the traditional multinomial logit model, is presented.
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Ordered Logit Model

2014
The ordered logit model is a regression model for an ordinal response variable. The model is based on the cumulative probabilities of the response variable: in particular, the logit of each cumulative probability is assumed to be a linear function of the covariates with regression coefficients constant across response categories.
Grilli, Leonardo, Rampichini, Carla
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Logit and Probit Models

1992
Statistical models in which the endogenous random variables take only discrete values are known as discrete, categorical, qualitative — choice, or quanta! response models.1 This class of models was originally developed by psychologists and later adapted and extended by economists for describing consumers choices. These models have numerous applications
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