A rich class of parametric models is proposed for discrete choice data based on the scale mixture of multivariate normal distributions. The multinomial probit model is a special case in the class. The new models can be implemented in a Bayesian framework without much difficulty because of their special connections to the multinomial probit model. A Gibbs sampler with data augmentation is used t...

A Bayesian probit model with individual effects that exhibit spatial dependencies is set forth. Since probit models are often used to explain variation in individual choices, these models may well exhibit spatial interaction effects due to the varying spatial location of the decision makers. That is, individuals located at similar points in space may tend to exhibit similar choice behavior. The...

This paper aims to assess the possibility of predicting Croatian recessionary episodes using probit models. The authors first estimate a baseline static model using four leading indicators of recession (monetary base, unemployment, industrial production, and CROBEX stock market index). Lag lengths of up to 6 months are examined for each of the observed variables in the probit specification, and...

The relationship between the number of fibers injected intraperitoneally and the occurrence of peritoneal mesotheliomas in rats was investigated using data from a series of carcinogenicity studies with several fibrous dusts. Based on observed tumor incidences ranging between 10 and 90%, the hypothesis of a common slope of dose-response relationships (parallel probit lines in probit analysis) ca...

I look at data from an experiment in which people rank apples according to how they think they will taste. They are then blindfolded and rank how they actually taste. I estimate a multinomial rankordered probit model with correlated errors between the taste and visual rankings. I find that the errors for visual characteristics are correlated based on coloring, while the errors for taste are cor...

In this paper, we discuss the derivation and application of a bivariate ordered probit model with mixed effects. Our approach allows one to estimate the distribution of the effect (gamma) of an endogenous ordered variable on an ordered explanatory variable. By allowing gamma to vary over the population, our estimator offers a more flexible parametric setting to recover the causal effect of an e...

During the last two decades there has been an increase in using dynamic tariffs for billing household electricity consumption. This has questioned the suitability of traditional pricing schemes, such as two-part tariffs, since they contribute to create marked peak and offpeak demands. The aim of this paper is to assess if two-part tariffs are an efficient pricing scheme using Spanish household ...

This paper studies the importance of employer-specific determinants in escaping low earnings in Germany. To address the initial conditions problem and the endogeneity of employer retention, we model (intra-firm) low-pay transitions using a multivariate Probit model that accounts for selection into low-wage employment and non-random employer drop-out. Using data from the LIAB Linked Employer–Emp...

The Happiness Gains from Sorting and Matching in the Labor Market Sorting of people on the labor market not only assures the most productive use of valuable skills but also generates individual utility gains if people experience an optimal match between job characteristics and their preferences. Based on individual data on reported satisfaction with life it is possible to assess these latter ga...

In the present paper a mixed approach is proposed for the simulta neously estimation of regression and correlation structure parameters in multivariate probit models using generalized estimating equations for the former and pseudo score equations for the latter The nite sample proper ties of the corresponding estimators are compared to estimators proposed by Qu Williams Beck and Medendorp and Q...