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Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models

Author

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  • Markku Lanne

    (University of Helsinki and CREATES)

  • Henri Nyberg

    (University of Helsinki)

Abstract

We propose a new generalized forecast error variance decomposition with the property that the proportions of the impact accounted for by innovations in each variable sum to unity. Our decomposition is based on the well-established concept of the generalized impulse response function. The use of the new decomposition is illustrated with an empirical application to U.S. output growth and interest rate spread data.

Suggested Citation

  • Markku Lanne & Henri Nyberg, 2014. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," CREATES Research Papers 2014-17, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2014-17
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    References listed on IDEAS

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    More about this item

    Keywords

    Forecast error variance decomposition; generalized impulse response function; output growth; term spread;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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