This paper is concerned with Bayesian reduced rank regression when instruments are weak. There have been a number of studies on weak identification problem with the application of reduced rank regression combined with singular value decomposition (SVD) method in the Bayesian framework, see...

Economic policy decisions are often informed by empirical economic analysis. While the decision-maker is usually only interested in good estimates of outcomes, the analyst is interested in estimating the model. Accurate inference on the structural features of a model, such as cointegration, can...

This study addresses the complexity in modeling contingent valuation surveys with true zeros and non-ignorable missing responses including “don’t knows†and protest responses. An endogenous switching tobit model is specified to simultaneously estimate the parameters of the...

There is considerable disagreement in the empirical macro literature as to the degree of returns to scale in U.S. production. While many studies find evidence of a small degree of increasing returns, standard errors are typically large. This issue is of importance for assessing the possibility...

Markov switching GARCH models have been developed in order to address the statistical regularity observed in financial time series such as strong persistence of conditional variance. However, Maximum Likelihood Estimation faces a implementation problem since the conditional variance depends on...

This paper proposes a Structural Error Correction Model (SECM) that allows concurrent estimation of the structural parameters and analysis of cointegration. We amalgamate the Bayesian methods of Kleibergen and Paap (2002) for analysis of cointegration in the ECM, and the Bayesian methods of...

Kernel density estimation for multivariate data is an important technique that has a wide range of applications in econometrics and finance. However, it has received significantly less attention than its univariate counterpart. The lower level of interest in multivariate kernel density...

This paper presents Bayesian methodology for the estimation of a bivariate probit model with an endogenous effect and both parametric linear and flexible semiparametric exogenous effects. The model is prompted by an analysis of the utilisation of health services in Australia using data from the...

Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that allow relatively smooth cycles to be extracted. Posterior densities of...