This paper uses data on automobile purchases to compare two alternatives to the multinomial logit model. The results indicate that the nested logit model is likely to be superior to the more general Berry–Levinsohn–Pakes model for applications using aggregate-level data.  2000 Elsevier Science S.A. All rights reserved.

objective: poverty alleviation is an essential step to achieve economic development. this is why identification exercise is so crucial. traditionally, different aspects of insecurities have not be taken into poverty measurement. many types of insecurities have adverse impacts on household welfare. identifying vulnerability of household can serve identification of the poor households. methodolog...

Functional logistic regression has been developed to forecast a binary response variable from a functional predictor. In order to fit this model, it is usual to assume that the functional observations and the parameter function of the model belong to a same finite space generated by a basis of functions. This consideration turns the functional model into a multiple logit model whose design matr...

The so-called “mixed” or “heterogeneous” multinomial logit (MIXL) model has become popular in a number of fields, especially Marketing, Health Economics and Industrial Organization. In most applications of the model, the vector of consumer utility weights on product attributes is assumed to have a multivariate normal (MVN) distribution in the population. Thus, some consumers care more about som...

This paper describes a revenue management project with a major airline that operates in a fiercely competitive market involving two major hubs and having more than 30 parallel daily flights. The market has a number of unusual characteristics including (1) almost half of customers choose not to purchase the tickets after booking; (2) about half of customers purchase their tickets within 3 days o...

An exact formula for the expected compensating variation is derived for logit and nested-logit models with income effects. Intuition, examples, and an application are provided. The appendix contains a formal proof. The formula is applied to estimate the E[cv]s salmon anglers in Maine would associate with changes in catch rates at Maine and Canadian Rivers.

This article introduces a Markov chain Monte Carlo (MCMC) method for sampling the parameters of a multinomial logit model from their posterior distribution. Let yi ∈ {0, . . . ,M} denote the categorical response of subject i with covariates xi = (xi1, . . . , xip) T . Let X = (x1, . . . ,xn) T denote the design matrix, and let y = (y1, . . . , yn) T . Multinomial logit models relate yi to xi th...

3 Model Specification 5 3.1 Binary choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1.1 The binary probit model . . . . . . . . . . . . . . . . . . 6 3.1.2 The binary logit model . . . . . . . . . . . . . . . . . . . 7 3.2 More than two choices . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.1 The multinomial probit model . . . . . . . . . . . . . . . 8 3.2.2 The multinomi...

Understanding and accommodating heterogeneity in variance (also referred to as heteroscedasticity) and taste has become a major area of research within discrete choice analysis. Both scale and taste heterogeneity can be specified as continuous or discrete, the latter can be associated with socio economic characteristics (i.e. observed heterogeneity) or it can be derived probabilistically (i.e. ...

Gaussian process prior with an appropriate likelihood function is a flexible non-parametric model for a variety of learning tasks. One important and standard task is multi-class classification, which is the categorization of an item into one of several fixed classes. A usual likelihood function for this is the multinomial logistic likelihood function. However, exact inference with this model ha...