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Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? An Investigation into the Case of Germany

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  • Jan Gottschalk
  • Willem Van Zandweghe

Abstract

Bivariate SVAR models employing long-run identifying restrictions are popular tools 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, the consistency of results from different bivariate SVAR models estimated for German data is evaluated using the FAUST and LEEPER (1997) test procedure. The principal result is that these models do not allow reliable inference on the sources of output fluctuations.

Suggested Citation

  • Jan Gottschalk & Willem Van Zandweghe, 2003. "Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? An Investigation into the Case of Germany," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 139(I), pages 55-81, March.
    • Handle: RePEc:ses:arsjes:2003-i-3
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    More about this item

    Keywords

    Business Cycle Fluctuations; Structural Vector Autoregression Models; Long-run Restrictions;
    All these keywords.

    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; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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