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A Critical Note on the Forecast Error Variance Decomposition

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  • Seymen, Atilim

Abstract

The paper questions the reasonability of using forecast error variance decompositions for assessing the role of different structural shocks in business cycle fluctuations. It is shown that the forecast error variance decomposition is related to a dubious definition of the business cycle. A historical variance decomposition approach is proposed to overcome the problems related to the forecast error variance decomposition.

Suggested Citation

  • Seymen, Atilim, 2008. "A Critical Note on the Forecast Error Variance Decomposition," ZEW Discussion Papers 08-065, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:7388
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    Citations

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    Cited by:

    1. Wozniak Marcin, 2020. "Forecasting the unemployment rate over districts with the use of distinct methods," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-20, April.
    2. Gachet, Ivan & Maldonado, Diego & Pérez, Wilson, 2008. "Determinantes de la Inflación en una Economía Dolarizada: El Caso Ecuatoriano [Determinants of Inflation in a Dollarized Economy: The Case of Ecuador]," MPRA Paper 17101, University Library of Munich, Germany.
    3. BigBen Chukwuma Ogbonna, 2016. "Inflation, exchange rate and efficacy of monetary policy in Nigeria: The empirical evidence," Academicus International Scientific Journal, Entrepreneurship Training Center Albania, issue 13, pages 40-53, January.
    4. Seymen, Atilim & Kappler, Marcus, 2009. "The role of structural common and country-specific shocks in the business cycle dynamics of the G7 countries," ZEW Discussion Papers 09-015, ZEW - Leibniz Centre for European Economic Research.

    More about this item

    Keywords

    Business Cycles; Structural Vector Autoregression Models; Forecast Error Variance Decomposition; Historical Variance Decomposition;
    All these keywords.

    JEL classification:

    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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