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Publication# Discrete choice models with multiplicative error terms

Abstract

We propose a multiplicative specification of a discrete choice model that renders choice probabilities independent of the scale of the utility. The model outperforms the classical additive formulation over a range of data sets.

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Related concepts (12)

Related publications (15)

Related MOOCs (2)

Discrete choice

In economics, discrete choice models, or qualitative choice models, describe, explain, and predict choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be a continuous variable. In the continuous case, calculus methods (e.g. first-order conditions) can be used to determine the optimum amount chosen, and demand can be modeled empirically using regression analysis.

Logistic regression

In statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).

Data set

A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files.

Selected Topics on Discrete Choice

Discrete choice models are used extensively in many disciplines where it is important to predict human behavior at a disaggregate level. This course is a follow up of the online course “Introduction t

Selected Topics on Discrete Choice

Discrete choice models are used extensively in many disciplines where it is important to predict human behavior at a disaggregate level. This course is a follow up of the online course “Introduction t

Michel Bierlaire, Shadi Sharif Azadeh, Meritxell Pacheco Paneque, Bernard Gendron

The integration of discrete choice models in optimization is appealing to operators and policy makers (the supply) because it provides a better understanding of the preferences of clients (the demand) while planning for their systems. Notwithstanding the c ...

2017This is an overview of a program of stochastic deformation of the mathematical tools of classical mechanics, in the Lagrangian and Hamiltonian approaches. It can also be regarded as a stochastic version of Geometric Mechanics.The main idea is to construct ...

2012This thesis tackles new challenges associated with the disaggregate modeling of the human behavior. Decision-aid tools help in making decisions, by providing quantitative insights on the decisions and associated consequences. They are useful in complex sit ...