Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? The Case of Germany

Bivariate SVAR models employing long-run identifying restrictions are often used to investigate the source of business cycle fluctuations. Their advantage is the simplicity in use and interpretation. However, their low dimension may also lead to a failure of the identification procedure, with the result that the identified shocks are a mixture of the ‘true’ shocks. To investigate this issue, we evaluate for German data the consistency of results from different bivariate SVAR models employing the same long-run identifying restrictions. We find that these models do not offer reliable evidence on the sources of output fluctuations.