VAERS is a postmarketing surveillance program, collecting information about adverse events (possible harmful side effects) that occur after administration of vaccines to ascertain whether …

Calculating Long-Run E ects in an SVAR Suppose Z t = ( y t; x t) 0 Then the long-run e ect of the shock on y t is the sum of its e ects of y t, y t+1, y t+2 and so on. The long-run e ect is the sum …

Sep 11, 2009 · Given the results on the power and size properties of long-run VARs, we conclude that these VARs are useful for discriminating between macro models. Several recent papers …

The goal of researchers using structural vector autoregressions (SVARs) with long-run restrictions is to guide the development of new business cycle models. This procedure uses a simple time …

Aug 2, 2021 · In this blog, we look closely at the identification problem posed by structural vector autoregressive models and its solution. In particular, we cover: What is the structural VAR …

Much less is known about the power of structural VARs. This paper attempts to fill in this gap by exploring the power of long-run struc-tural VARs against a set of DSGE models that vary in …

The Power of Long-Run Structural VARs. Christopher Gust and Robert Vigfusson. Abstract: Are structural vector autoregressions (VARs) useful for discriminating between macro models? …

Apr 8, 2024 · To address these problems, we develop a flexible class of additively time-separable nonlinear SVARs, which subsume models with threshold-type endogenous regime switching, …

Nov 1, 2008 · We have disproved the main claim of the literature on SVARs with long-run restrictions: that the SVAR procedure can confidently distinguish between promising and …

optimal VAR method depends on the horizon: Bayesian VARs tend to perform well at short horizons, least-squares VARs at intermediate horizons, and the two methods are …