Stephen R. Cosslett

Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model

is a given function of the exogenous variables z and unknown parameters 9, representing the systematic component of the utility difference, and F is the distribution function of the random component of the utility difference. This paper describes a method of estimating the parameters 9 without assuming any functional form for the distribution function F, and proves that this estimator is consistent. F is also consistently estimated. The method uses maximum likelihood estimation in which the likelihood is maximized not only over the parameter 9 but also over a space which contains all distribution functions.

Efficiency bounds for distribution-free estimators of the binary choice and the censored regression models

Lower bounds are derived for the asymptotic variances of regular distribution-free (or semiparametric) estimators of the parameters of the binary-choice model and the censored-regression (Tobit) model. A semiparametric estimator is one that does not require any assumption about the distribution of the stochastic error term in the model, apart from regularity conditions. Comparison of the bounds with the corresponding asymptotic Cramer-Rao bounds for the classical parametric problem shows the loss of information due to lack of a priori knowledge of the functional form of the error distribution. Copyright 1987 by The Econometric Society.

Serial correlation in latent discrete variable models

Abstract We consider the problems of estimation and testing in models with serially correlated discrete latent variables. A particular case of this is the time series regression model in which a discrete explanatory variable is measured with error. Test statistics are derived for detecting serial correlation in such a model. We then show that the likelihood function can be evaluated by a recurrence relation, and thus maximum likelihood estimation is computationally feasible. An illustrative example of these methods is given, followed by a brief discussion of their applicability to a Markov model of switching regressions.

Environmental Quality Preference and Benefit Estimation in Multinomial Probit Models: A Simulation Approach

Simulated maximum likelihood is used to estimate a random parameter multinomial probit model of destination choice for recreational fishing trips, formulated to accommodate varying tastes and varying perceptions of environmental quality across individuals. The restricted likelihood ratio test strongly rejects the independent probit model, which is similar to the independent logit model in both the parameter and benefit estimates. Furthermore, both the Krinsky-Robb and bootstrapping procedures suggest that the benefit (standard deviation) of an environmental policy is found to be markedly lower (higher) when heterogeneous preferences are taken into account. Copyright 1998, Oxford University Press.

A Race Against the Clock: Auctioneer Strategies and Selling Mechanisms in Live Outcry Auctions

Using data from an original survey of practicing auctioneers, this paper examines the effect of binding time constraints on the auctioneer’s selling strategy in an outcry auction. We present a time-allocation model in which the length of time allocated to the sale of an item must be traded off against its realized price. This is applied to (1) the relationship between time allocation and the ex ante value of an item; (2) the effect of the reported variation over time of the number of bidders present, on both the time allocation and the order in which items of differing value are presented for sale; and (3) the auctioneer’s use of various bidding processes, such as batching and selling by choice, from the perspective of the auctioneer’s time-revenue tradeoff. Our results corroborate and provide theoretical underpinning for observed auctioneer behavior.