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...

This paper analyses the effects of discretionary fiscal policy by presenting new empirical evidence for Germany within a structural vector autoregression (SVAR) framework. Following Blanchard and Perotti (2002), the SVAR model is identified by applying institutional information. We find no compelling evidence for the effectiveness of discretionary fiscal policy. Cutting taxes does not tend to s...

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...

This study examines the nature of competition between the two leading brands of a national small size market by estimating shortand long-term competitive reactions via a Structural VAR (SVAR) model. The primary findings indicate how the two competitors react, which marketing instruments are used, and when competitive reactions affect crossand own-sales. The empirical results suggest that compet...

This paper examines the usefulness of applying structural vector autoregressions (SVARs) to the study of business cycles. The SVAR approach aims to provide robust inferences, by imposing only weak theoretical restrictions. We illustrate that the robustness of conclusions drawn from SVAR exercises are questionable. We also examine the problem of identification failure in structural VAR models. ©...

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...

The intertemporal current account approach predicts that the current account of a small open economy is independent of global shocks, and that responses of the current account to countryspecific shocks depend on the persistence of the shocks. The author shows that these predictions impose cross-equation restrictions (CERS) on a structural vector autoregression (SVAR). To test the CERs, the auth...

This paper fills a gap in the literature by investigating whether temporary agency employment substitutes regular employment. To take into account the interaction between the two employment forms, we identify a SVAR model with correlated innovations by volatility regimes. We show that a positive shock to temporary agency employment increases overall employment, but also leads to substitution of...

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...