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Evaluation of the Survey of Professional Forecasters in the Greenbook’s Loss Function

Author

Listed:
  • Tae-Hwy Lee

    (University of California)

  • Yiyao Wang

    (University of Chicago)

Abstract

We aim to find a forecast in the Survey of Professional Forecasters (SPF) that is closest to the Greenbook forecast of the Federal Reserve Board. To do it, we look for an SPF cross-sectional percentile that is not encompassed by the Greenbook forecast under the Greenbook’s estimated asymmetric quadratic loss function with allowing asymmetry to be time-varying. To evaluate each SPF percentile in terms of the Greenbook’s asymmetric quadratic loss function, we introduce the encompassing test for the asymmetric least square regression (Newey and Powell, Econometrica 55(4):819–847, 1987). From the analysis of the US quarterly real output and inflation forecasts over the past four decades, we find that almost all SPF percentiles are encompassed by the Greenbook forecast in full data period. However there is evidence in sub-periods that many SPF percentiles are not encompassed by Greenbook. Among them, the best SPF percentile that is not encompassed by Greenbook and is closest to Greenbook for real output growth forecast is near the median of the SPF percentiles, while the best SPF percentile for inflation forecast is far below the median in the left tail of the SPF cross-sectional distribution. It indicates that the common practice of using the SPF median can be misleading.

Suggested Citation

  • Tae-Hwy Lee & Yiyao Wang, 2019. "Evaluation of the Survey of Professional Forecasters in the Greenbook’s Loss Function," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 345-360, June.
    • Handle: RePEc:spr:jqecon:v:17:y:2019:i:2:d:10.1007_s40953-018-0141-8
    DOI: 10.1007/s40953-018-0141-8
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    References listed on IDEAS

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    More about this item

    Keywords

    Asymmetric least squares; Encompassing test; Estimating asymmetric quadratic loss function; Forecast averaging; Model averaging;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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