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Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? The Case of Germany Author info | Abstract | Publisher info | Download info | Related research | Statistics Jan Gottschalk
Willem Van Zandweghe
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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.
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Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number
1068.
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Length: 52 pages
Date of creation: Aug 2001Date of revision:
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Keywords: Business Cycle Fluctuations ; Structural Vector Autoregression Models ; Long-run Restrictions ; Find related papers by JEL classification: E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
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