We propose a Bayesian procedure for multiple outlier detection in linear models avoiding the masking problem. Our proposal is illustrated with several examples in which our procedure outperforms other recent methods for multiple outlier detection. The posterior probabilities of each data point...

Advances in computing power allow the empirical researcher to use intensive computional techniques to solve and estimate nonlinear panel-data models, specifically those arising from nonlinear panel data such as Probit and Tobit models. In these cases, maximum-likelihood estimation can be...

We employ Bayesian approach to the analysis of economic growth in Poland. The results of estimation of a stochastic frontier model applied to production function of Polish voivodships in 2000 - 2004 are presented. Stochastic frontier approach allows to decompose growth into technological change,...

We apply Markov chain Monte Carlo methods to time series data on S&P 500 index returns, and to its option prices via a term structure of VIX indices, to estimate 18 different affine and non-affine stochastic volatility models with one or two variance factors, and where jumps are allowed in both...

We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider Bayesian approaches developed by Chao and Phillips, Geweke, Kleibergen and van Dijk, and...

We estimate impacts of rainfall and temperature on corn yields by fitting a linear spline model with endogenous thresholds. Using Gibbs sampling and the Metropolis - Hastings algorithm, we simultaneously estimate the thresholds and other model parameters. A hierarchical structure is applied to...

We compare the finite sample performance of a number of Bayesian and classical procedures for limited information simultaneous equations models with weak instruments by a Monte Carlo study. We consider Bayesian approaches developed by Chao and Phillips, Geweke, Kleibergen and van Dijk, and...