The central finding of the recent structural vector autoregression (SVAR) literature with a differenced specification of hours is that technology shocks lead to a fall in hours. Researchers have used this finding to argue that real business cycle models are unpromising. We subject this SVAR specification to a natural economic test and show that when applied to data from a multiple-shock busines...

The main substantive finding of the recent structural vector autoregression literature with a differenced specification of hours (DSVAR) is that technology shocks lead to a fall in hours. Researchers have used these results to argue that business cycle models in which technology shocks lead to a rise in hours should be discarded. We evaluate the DSVAR approach by asking, is the specification de...

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...

In this paper we present the Large Inverse Cholesky (LIC) method, an efficient method for computing the coefficient matrices of a Structural Vector Autoregressive (SVAR) model.

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...