This paper identifies and develops the class of Gaussian copula models for marginal
regression analysis of non-normal dependent observations. The class provides a natural …

This chapter develops a framework for quantile regression in binary longitudinal data
settings. A novel Markov chain Monte Carlo (MCMC) method is designed to fit the model and …

The multivariate probit model (MVP) is a popular classic model for studying binary
responses of multiple entities. Nevertheless, the computational challenge of learning the …

The last decade has seen a dramatic increase in the popularity of product search engines,
yet the analysis of consumer behavior at such sites remains a challenging research problem …

This article develops a framework for estimating multivariate treatment effect models in the
presence of sample selection. The methodology deals with several important issues …

Bank rescue programs are designed to provide assistance to struggling financial
intermediaries during financial crises. A complicating factor is that participating banks are …

The information processing literature provides a wealth of laboratory evidence on the effects
that the choice task and individual characteristics have on the extent to which consumers …

Purpose The purpose of this paper is to examine whether people who engage in religious
activities are more generous in terms of both religious and secular giving …

Abstract This chapter introduces Markov Chain Monte Carlo (MCMC) methods for empirical
corporate finance. These methods are very useful for researchers interested in capital …

For over three decades, vector autoregressions have played a central role in empirical
macroeconomics. These models are general, can capture sophisticated dynamic behavior …