Multivariate Forecast Evaluation and Rationality Testing
AbstractIn this paper, we propose a new family of multivariate loss functions to test the rationality of vector forecasts without assuming independence across variables. When only one variable is of interest, the loss function reduces to the flexible asymmetric family proposed by Elliott, Komunjer, and Timmerman (2008). Following their methodology, we derive~a GMM test for multivariate forecast rationality that allows the forecaster's loss to be nonseparable across variables and takes into account forecast estimation uncertainty. We use our test to study the joint rationality of macroeconomic forecasts in the growth rate of nominal output, CPI inflation rate, and short-term interest rate. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Bibliographic InfoArticle provided by MIT Press in its journal Review of Economics and Statistics.
Volume (Year): 94 (2012)
Issue (Month): 4 (November)
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Other versions of this item:
- Ivana Komunjer & Michael T. Owyang, 2007. "Multivariate forecast evaluation and rationality testing," Working Papers 2007-047, Federal Reserve Bank of St. Louis.
- Komunjer, Ivana & OWYANG, MICHAEL, 2007. "Multivariate Forecast Evaluation And Rationality Testing," University of California at San Diego, Economics Working Paper Series qt81w8m5sf, Department of Economics, UC San Diego.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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