This paper extends the Bayesian proxy SVAR model (BP-SVAR) of Caldara and Herbst (2019) to examine changes in the transmission of structural shocks in the presence of regime shifts in an economy. I provide a Metropolis-within-Gibbs sampling algorithm to approximate the posterior distribution of...

We study the comovement of international business cycles in a time series clustering model with regime-switching. We extend the framework of Hamilton and Owyang (2012) to include time-varying transition probabilities to determine what drives similarities in business cycle turning points. We find...

In this paper we extend the Bayesian Proxy VAR to incorporate time variation in the parameters. A Gibbs sampling algorithm is provided to approximate the posterior distributions of the model's parameters. Using the proposed algorithm, we estimate the time-varying effects of taxation shocks in...

Following Giraitis, Kapetanios, and Yates (2014b), this paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the data set constructed by Smets and Wouters (2007). We apply an indirect inference method to map from this TV VAR to time...