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Correcting the January optimism effect

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  • Philip Hans Franses

Abstract

Each month, various professional forecasters give forecasts for next year's real gross domestic product (GDP) growth and unemployment. January is a special month, when the forecast horizon moves to the following calendar year. Instead of deleting the January data when analyzing forecast updates, I propose a periodic version of a test regression for weak‐form efficiency. An application of this periodic model for many forecasts across a range of countries shows that in January GDP forecast updates are positive, whereas the forecast updates for unemployment are negative. I document that this January optimism about the new calendar year is detrimental to forecast accuracy. To empirically analyze Okun's law, I also propose a periodic test regression, and its application provides more support for this law.

Suggested Citation

  • Philip Hans Franses, 2020. "Correcting the January optimism effect," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 927-933, September.
    • Handle: RePEc:wly:jforec:v:39:y:2020:i:6:p:927-933
    DOI: 10.1002/for.2670
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    References listed on IDEAS

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    Cited by:

    1. Arbab Khalid Cheema & Wenjie Ding & Qingwei Wang, 2023. "The cross-section of January effect," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 513-530, October.

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