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Estimation and Testing of Forecast Rationality with Many Moments

Author

Listed:
  • Tae-Hwy Lee

    (Department of Economics, University of California Riverside)

  • Tao Wang

    (Department of Economics, University of Victoria, Canada)

Abstract

We in this paper utilize P-GMM (Cheng and Liao, 2015) moment selection procedure to select valid and relevant moments for estimating and testing forecast rationality under the flexible loss proposed by Elliott et al. (2005). We motivate the moment selection in a large dimensional setting, explain the fundamental mechanism of P-GMM moment selection procedure, and elucidate how to implement it in the context of forecast rationality by allowing the existence of potentially invalid moment conditions. A set of Monte Carlo simulations is conducted to examine the finite sample performance of P-GMM estimation in integrating the information available in instruments into both the estimation and testing, and a real data analysis using data from the Survey of Professional Forecasters issued by the Federal Reserve Bank of Philadelphia is presented to further illustrate the practical value of the suggested methodology. The results indicate that the P-GMM post-selection estimator of forecaster’s attitude is comparable to the oracle estimator by using the available information efficiently. The accompanying power of rationality and symmetry tests utilizing P-GMM estimation would be substantially increased through reducing the influence of uninformative instruments. When a forecast user estimates and tests for rationality of forecasts that have been produced by others such as Greenbook, P-GMM moment selection procedure can assist in achieving consistent and more efficient outcomes.

Suggested Citation

  • Tae-Hwy Lee & Tao Wang, 2023. "Estimation and Testing of Forecast Rationality with Many Moments," Working Papers 202307, University of California at Riverside, Department of Economics.
    • Handle: RePEc:ucr:wpaper:202307
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    References listed on IDEAS

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    1. Ivana Komunjer & Michael T. Owyang, 2012. "Multivariate Forecast Evaluation and Rationality Testing," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1066-1080, November.
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    More about this item

    Keywords

    Forecast rationality; Moment selection; P-GMM; Relevance; Validity.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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