This note warns against the use of noncausal VARs as a reliable test for indeterminacy. By means of a simple example, we show that determinate models may well entail nonfundamental ARMA equilibrium reduced forms - which only (and uniquely) depend on the fundamental structural shocks -, whereas...

In a recent paper, Mertens and Ravn (2010) study the effects of anticipated fiscal policy shocks in a structural vector autoregressive model. The authors maintain that (i) the lag polynomial associated with news shocks is a cyclotomic polynomial and (ii) the matrix B(L) which transforms a...

This paper assesses SVARs as relevant tools at identifying the aggregate effects of news shocks. When the econometrician and private agents’ information sets are not aligned, the dynamic responses identified from SVARs are biased. However, the bias vanishes when news shocks account for the...

This paper assesses SVARs as relevant tools at identifying the aggregate effects of news shocks. When the econometrician and private agents’ information sets are not aligned, the dynamic responses identified from SVARs are biased. However, the bias vanishes when news shocks account for the...

In a recent paper, Mertens and Ravn (2010) study the effects of anticipated fiscal policy shocks in a structural vector autoregressive model. The authors maintain that (i) the lag polynomial associated with news shocks is a cyclotomic polynomial and (ii) the matrix B(L) which transforms a...

The present paper shows that there is a simple way to check whether a DSGE model can be represented by a finite order VAR. This consists in verifying that the eigenvalues of a certain matrix defined in Fernandez-Villaverde et al. (2007) are all equal to zero. Further we show that this condition...

This paper investigates the reliability of SVARs to identify the dynamic effects of news shocks. We show analytically that the dynamics implied by SVARs, using both long–run and short–run restrictions, are biased. However, the bias vanishes as long as news shocks account for most of the...