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date: 21 July 2019

Abstract and Keywords

This article is of two-fold interest with the goal of providing an overview of the field and aims at discussing the most recent research in the relevant field. It shows how the computational methods and modelling ideas are being used by Bayesian econometricians. It also discusses linear models and presents a review of the normal linear regression model, deriving marginal, conditional, and predictive posterior densities of interest. This article proceeds further to discuss hierarchical linear models and review approaches to handle endogeneity problems. It presents applications and posterior simulation strategies for nonlinear latent variable models and considers the analysis of treatment effects models and multinomial and multivariate probit models. This article briefly reviews basic Bayesian approaches to the analysis of duration data.

Keywords: computational methods, modeling, linear models, posterior simulation, probit models

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