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Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts

Author

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  • Michael P. Clements

    (ICMA Centre, Henley Business School, University of Reading)

Abstract

If learning-by-doing is important for macro-forecasting, newcomers might be different to regular, established particants. Stayers may also differ from the soon-to-leave. We test these conjectures for macro-forecasters point predictions of output growth and inflation, and for their histogram forecasts. A bootstrap approach is used to overcome the problems associated with the relatively small numbers of joiners and leavers. Controlling for the numbers of forecasters with the bootstrap approach is required to correctly determine whether there are systematic differences between experienced forecasters and newcomers, and between stayers and leavers.

Suggested Citation

  • Michael P. Clements, 2020. "Do Survey Joiners and Leavers Differ from Regular Participants? The US SPF GDP Growth and Inflation Forecasts," ICMA Centre Discussion Papers in Finance icma-dp2020-01, Henley Business School, University of Reading.
    • Handle: RePEc:rdg:icmadp:icma-dp2020-01
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    Cited by:

    1. Clements, Michael P., 2025. "Inconsistent survey histograms and point forecasts revisited," Journal of Economic Behavior & Organization, Elsevier, vol. 236(C).
    2. Anis Ochi & Yosra Saidi & Mohamed Ali Labidi, 2023. "Non-linear Threshold Effect of Governance Quality on Economic Growth in African Countries: Evidence from Panel Smooth Transition Regression Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 14(4), pages 4707-4729, December.
    3. Hana Braitsch & James Mitchell & Taylor Shiroff, 2024. "Practice Makes Perfect: Learning Effects with Household Point and Density Forecasts of Inflation," Working Papers 24-25, Federal Reserve Bank of Cleveland.
    4. Klein, Tony, 2021. "Agree to Disagree? Predictions of U.S. Nonfarm Payroll Changes between 2008 and 2020 and the Impact of the COVID19 Labor Shock," QBS Working Paper Series 2021/07, Queen's University Belfast, Queen's Business School.
    5. repec:upd:utmpwp:042 is not listed on IDEAS
    6. Toshitaka Sekine & Frank Packer & Shunichi Yoneyama, 2022. "Individual Trend Inflation," IMES Discussion Paper Series 22-E-14, Institute for Monetary and Economic Studies, Bank of Japan.
    7. Mohamed Ali Labidi & Anis Ochi & Yosra Saidi, 2024. "Relationship Analysis Between FDI and Economic Growth in African Countries: Does Governance Quality Matter?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(4), pages 16511-16540, December.
    8. Michael P. Clements, 2020. "Are Some Forecasters’ Probability Assessments of Macro Variables Better Than Those of Others?," Econometrics, MDPI, vol. 8(2), pages 1-16, May.
    9. Klein, Tony, 2022. "Agree to disagree? Predictions of U.S. nonfarm payroll changes between 2008 and 2020 and the impact of the COVID19 labor shock," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 264-286.

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    JEL classification:

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

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