This paper aims to provide a non-technical introduction into the SVAR methodology. Particular emphasize is put on the approach to identification in SVAR models, which is compared to identification in simultaneous equation models. It is shown that SVAR models are useful tools to analyze the dynamics of a model by subjecting it to an unexpected shock, whereas simultaneous equation models are bett...

Conditional heteroskedasticity can be exploited to identify the structural vector autoregressions (SVAR) but the implications for inference on structural impulse responses have not been investigated in detail yet. We consider the conditionally heteroskedastic SVAR-GARCH model and propose a bootstrap-based inference procedure on structural impulse responses. We compare the finite-sample properti...

The purpose of this paper is to provide an introduction to the methodology known as Structural Vector Autoregression (SVAR) analysis and to examine its applicability in the context of Irish macroeconomics. The SVAR approach has been developed over the last decade to interpret business cycle fluctuations and to help identify the effects of different economic policies. It is an extension on the t...

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. ©...

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...

Conventional structural vector autoregressive (SVAR) models with Gaussian errors are not identified, and additional identifying restrictions are typically imposed in applied work. We show that the Gaussian case is an exception in that a SVAR model whose error vector consists of independent non-Gaussian components is, without any additional restrictions, identified and leads to (essentially) uni...

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper we propose general-to-specific model selection procedures to overcome these limitations. After showing that single-equation ...