There is a fast growing literature that set-identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variables to a particular structural shock (sign-restricted SVARs). Most methods that have been used to construct...

Introduction: Common approaches in cost-effectiveness analyses do not adjust for confounders. In nonrandomized studies this can result in biased results. Parametric models such as regression models are commonly applied to adjust for confounding, but there are several issues which need to be...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

Bayesian inference in moment condition models is difficult to implement. For these models, a posterior distribution cannot be calculated because the likelihood function has not been fully specified. In this paper, we obtain a class of likelihoods by formal Bayesian calculations that take into...

This paper analyses features of 28 provincial growth-cycles in China’s economy from March 1989 to July 2009. We study the multivariate synchronization of provincial cycles and the selection of the number of cycles phases’ by means of panel Markov-switching models. We obtain evidence that...

The expected value of the log of a Bayesian’s posterior assessment of the true state of nature, computed under the probability law of the true state, is always at least as large as the log of the prior.

We develop a reliable Bayesian inference for the RIF-regression model of Firpo, Fortin and Lemieux (Econometrica, 2009) in which we first estimate the log wage distribution by a mixture of normal densities. This approach is pursued so as to provide better estimates in the upper tail of the wage...

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral- t family of conditionally conjugate priors for hierarchical standard deviation parameters, and then consider noninformative and weakly informative...

Multiple regression is frequently used across the various social sciences to analyze cross-sectional data. However, it can often times be challenging to justify the assumption of common regression coefficients across all respondents. This manuscript presents a heterogeneous Bayesian regression...

This paper analyzes to what extent changes in monetary policy regimes influence the business cycle in a small open economy and investigates the impact of policy breaks on the estimation procedure. We estimate a DSGE model on Swedish data, explicitly taking into account the monetary regime change...