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Multivariate forecast evaluation and rationality testing

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  • Ivana Komunjer
  • Michael T. Owyang
Abstract
In this paper, we propose a new family of multivariate loss functions that can be used to test the rationality of vector forecasts without assuming independence across individual variables. When only one variable is of interest, the loss function reduces to the flexible asymmetric family recently proposed by Elliott, Komunjer, and Timmermann (2005). Following their methodology, we derive a GMM test for multivariate forecast rationality that allows the forecast errors to be dependent, and takes into account forecast estimation uncertainty. We use our test to study the rationality of macroeconomic vector forecasts in the growth rate in nominal output, the CPI inflation rate, and a short-term interest rate.

Suggested Citation

  • Ivana Komunjer & Michael T. Owyang, 2007. "Multivariate forecast evaluation and rationality testing," Working Papers 2007-047, Federal Reserve Bank of St. Louis.
    • Handle: RePEc:fip:fedlwp:2007-047
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    More about this item

    Keywords

    time series analysis; Forecasting;

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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