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

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  • van Zandweghe, Willem
  • Gottschalk, Jan

Abstract

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.

Suggested Citation

  • van Zandweghe, Willem & Gottschalk, Jan, 2001. "Do Bivariate SVAR Models with Long-Run Identifying Restrictions Yield Reliable Results? The Case of Germany," Kiel Working Papers 1068, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwkwp:1068
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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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