We use a stochastic frontier production model to estimate the technical efficiency of the 21 more industrialized countries in the world for the wide period from 1966 to 2007. A Cobb-Douglas function with labour and capital as inputs, GDP as output and an efficiency term with exponential...

We argue that the failure to disentangle the evolution of the Canadian currency from the U.S. currency leads to potentially incorrect conclusions regarding the case of Dutch disease in Canada. We propose a new approach that is aimed at extracting both currency components and energy- and...

This paper proposes a Bayesian approach to assess if the data support candidate set-identifying restrictions for Vector Autoregressive models. The researcher is uncertain about the validity of some sign restrictions that she is contemplating to use. She therefore expresses her uncertainty with a...

We study the bank lending channel in Switzerland over three decades using unbalanced quarterly bank-individual data spanning 1987 to 2016. In contrast to the usual empirical approach, we take an agnostic stance on which bank characteristic drives the heterogenous lending response to interest...

This paper examines the determinants of motorcycle fatality rates using panel data and classical and Bayesian statistical methods. It focuses on five variables in particular: universal helmet laws, partial helmet laws, cell phone use, suicidal propensities, and beer consumption. Universal helmet...

This note provides the details of the estimation procedure in Br¨unner (2019). In Section 2 we derive the posterior distribution. Section 3 describes the MCMC algorithm used to obtain draws from the posterior distribution and in Section 4 we present the method for our model check. We conclude...

This paper considers a linear panel data model with time varying heterogeneity. Bayesian inference techniques organized around Markov chain Monte Carlo (MCMC) are applied to implement new estimators that combine smoothness priors on unobserved heterogeneity and priors on the factor structure of...

This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects. We construct a working likelihood using an asymmetric Laplace (AL) error distribution and combine it with suitable prior distributions to obtain...

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

Child birth leads to a break in a woman's employment history and is considered one reason for the relatively poor labor market outcomes observed for women compared to men. However, the time spent at home after child birth varies significantly across mothers and is likely driven by observed and,...