Most macroeconomic data are uncertain - they are estimates rather than perfect measures of underlying economic variables. One symptom of that uncertainty is the propensity of statistical agencies to revise their estimates in the light of new information or methodological advances. This paper...

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...

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...

We build a time varying DSGE model with financial frictions in order to evaluate changes in the responses of the macroeconomy to financial friction shocks. Using US data, we find that the transmission of the financial friction shock to economic variables, such as output growth, has not changed...

DSGE models have recently received considerable attention in macroeconomic analysis and forecasting. They are usually estimated using Bayesian methods, which require the computation of the likelihood function under the assumption that the parameters of the model remain fixed throughout the...