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...

This paper uses kernel methods to estimate a seven variable time-varying (TV) vector autoregressive (VAR) model on the US data set constructed by Smets and Wouters. We use an indirect inference method to map from this TV VAR to time variation in implied Dynamic Stochastic General Equilibrium...

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...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

In this paper we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modeling VAR dynamics for non-stationary times series and estimation of time varying...

This paper investigates whether firms with direct access to capital markets 'help out' firms who are reliant on credit from banks by extending more trade credit when times are hard. In other words, is there a 'trade credit channel' that offsets the bank credit channel more familiar to monetary...

This paper outlines some problems with the methods often used to construct measures of real 'disequilibria' or 'gaps' (eg the output gap) and to examine their relationship with inflation. It then offers a structural vector autoregression alternative which is used to construct estimates of...

We identify a 'risk news' shock in a vector autoregression (VAR), modifying Barsky and Sims's procedure, while incorporating sign restrictions to simultaneously identify monetary policy, technology and demand shocks. The VAR-identifed risk news shock is estimated to account for around 2%-12% of...