This paper develops methods of Bayesian inference in a sample selection model. The main feature of this model is that the outcome variable is only partially observed. We first present a Gibbs sampling algorithm for a model in which the selection and outcome errors are normally distributed. The...

Markov models introduce persistence in the mixture distribution. In time series analysis, the mixture components relate to different persistent states characterizing the state-specific time series process. Model specification is discussed in a general form. Emphasis is put on the functional form...

This paper develops a statistical model for measuring spatial interactions when estimating macroeconomic regimes and regime shifts. The model is applied to study the contagion and propagation of recessions in small regional economies in the United States from 1990 to 2015. The empirical analysis...

This paper extends the Bayesian semiparametric stochastic volatility (SV-DPM) model of Jensen and Maheu (2010). Instead of using a Dirichlet process mixture (DPM) to model return innovations, we use an infinite hidden Markov model (IHMM). This allows for time variation in the return density...

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...

We study the relationship between monetary policy and long-term rates in a structural, general equilibrium model estimated on both macro and yields data from the United States. Regime shifts in the conditional variance of productivity shocks, or "uncertainty shocks", are an important model...

Increasing interconnectedness of global economies has consistently generated a lot of interests among empirical macro-economists in their quest to properly understand the channels of international spillover and macroeconomic shocks and how such crises when they arise, are managed by Small Open...

We study the relationship between monetary policy and long‐term rates in a structural, general equilibrium model estimated on both macro‐ and yield‐data from the United States. Regime shifts in the conditional variance of productivity shocks, or "uncertainty shocks," are a crucial driver...

We propose a Bayesian Metropolis-Gibbs Monte Carlo Markov Chain (MCMC) algorithm to estimate parameters of a sample selection model in which the selected equation include a binary endogenous explanatory variable, using a three simultaneous equation model. We apply our methodology to...

Computer and web-based interviewing tools have made response times ubiquitous in marketing research. These data are used as an indicator of data quality by practitioners, and of latent processes related to memory, attributes and decision making by academics. We investigate a Poisson race model...