Beaudry and Portier (2006) provide support for the "news view" of the business cycle, using a vector error correction model. We show that this result hinges on a cointegrating relationship between TFP and stock prices that is not stationary, thus making the estimates not reliable. If we alter...

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance, assuming known dates for variance changes is often...

Structural identification schemes are of essential importance to vector autoregressive (VAR) analysis. This paper tests a commonly used structural parameter identification scheme to assess whether it can properly capture fundamental and non-fundamental shocks to stock prices. In particular, five...

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance, assuming known dates for variance changes is often...

This paper investigates whether there are bubbles in stock prices. We do this using a previously studied structural vector autoregressive (SVAR) model claiming to distinguish fundamental and non-fundamental shocks to real stock prices. TheSVAR model relies on an identification restriction in...

We use a cointegrated structural vector autoregressive model to investigate the relation between euro area monetary policy and the stock market. Since there may be an instantaneous causal relation we consider long-run identifying restrictions for the structural shocks and also use (conditional)...