In Structural Vector Autoregressive (SVAR) models, heteroskedasticity can be exploited to identify structural parameters statistically. In this paper, we propose to capture time variation in the second moment of structural shocks by a stochastic volatility (SV) model, assuming that their log variances follow latent AR(1) processes. Estimation is performed by Gaussian Maximum Likelihood and an e...

Causal inference in multivariate time series is confounded by subsampling in time between the true causal scale and the observed data sampling rate. In practice, this presents challenges for inferring causal interaction between time series due to differences in sampling rates across time series and generally low sampling rates due to technological limitations. To determine instantaneous and lag...

We identify structural vector autoregressive (SVAR) models by combining sign restrictions with information in external instruments and proxy variables. We incorporate the proxy variables by augmenting the SVAR with equations that relate them to the structural shocks. Our modeling framework allows to simultaneously identify different shocks using either sign restrictions or an external instrumen...

The author evaluates the ability of a variety of output-gap estimators to accurately measure the output gap in a model economy. A small estimated model of the Canadian economy is used to generate artificial data. Using output and inflation data generated by this model, the author uses each output-gap estimation methodology to construct an estimate of the true output gap. He then evaluates the m...

In this paper we apply the method of inferred causation for macroeconomic analysis. First we introduce briefly the theory of inferred causation developed by Pearl and Verma (1991). We apply this method to the identification of structural vector autoregression (SVAR) models. In an example of monetary policy analysis we demonstrate how causal information embedded in the data can be used to identi...

This paper investigates changes in the conduct of U.S. monetary policy. Monetary policy is modeled in the context of the Bernanke-Mihov (1998) structural VAR (SVAR) extended to allow explicitly for the Fed’s forward looking behavior. This is achieved by including its realtime forecasts on in‡ation and unemployment (the “Greenbook” forecasts). Stability tests that exploit the SVAR identifying re...

This paper builds a structural VARMA (SVARMA) model for investigating Canadian monetary policy. Despite the support for a VARMA model for monetary policy analysis, the traditional VAR and SVAR models have predominantly been used in the literature mainly due to difficulties associated with the identification and estimation of such a model. Using the scalar component model (SCM) proposed by Athan...