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Weather, the Forgotten Factor in Business Cycle Analyses

Author

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  • Döhrn, Roland
  • an de Meulen, Philipp

Abstract

In periods of unusual weather, forecasters face a problem of interpreting economic data: Which part goes back to the underlying economic trend and which part arises from a special weather effect? In this paper, we discuss ways to disentangle weather-related from business cycle-related influences on economic indicators. We find a significant influence of weather variables at least on a number of monthly indicators. Controlling for weather effects within these indicators should thus create opportunities to increase the accuracy of indicator-based forecasts. Focusing on quarterly GDP growth in Germany, we find that the accuracy of the RWI short term forecasting model improves but advances are small and not significant.

Suggested Citation

  • Döhrn, Roland & an de Meulen, Philipp, 2015. "Weather, the Forgotten Factor in Business Cycle Analyses," Ruhr Economic Papers 539, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:539
    DOI: 10.4419/86788617
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    Citations

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    Cited by:

    1. Schreiber, Sven, 2017. "Weather adjustment of economic output," Discussion Papers 2017/5, Free University Berlin, School of Business & Economics.
    2. André Nunes Maranhão & Nicole Rennó Castro, 2023. "Dissecting Brazilian agriculture business cycles in high-dimensional and time-irregular span contexts," Empirical Economics, Springer, vol. 65(4), pages 1543-1578, October.
    3. Schreiber, Sven, 2018. "Weather-induced Short-term Fluctuations of Economic Output," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181622, Verein für Socialpolitik / German Economic Association.
    4. Döhrn, Roland & Barabas, György & Fuest, Angela & Gebhardt, Heinz & an de Meulen, Philipp & Micheli, Martin & Rujin, Svetlana & Zwick, Lina, 2015. "Die wirtschaftliche Entwicklung im Inland: Kräftige Expansion - nachlassender Schub im kommenden Jahr," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 66(1), pages 43-107.
    5. Döhrn, Roland & Barabas, György & Fuest, Angela & Gebhard, Heinz & Micheli, Martin & Rujin, Svetlana & Zwick, Lina, 2016. "Die wirtschaftliche Entwicklung im Inland: In schwierigem Fahrwasser," RWI Konjunkturberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, vol. 67(1), pages 37-110.
    6. Roland Döhrn & György Barabas & Angela Fuest & Heinz Gebhardt & Philipp an de Meulen & Martin Micheli & Svetlana Rujin & Lina Zwick, 2015. "Die wirtschaftliche Entwicklung im Inland: Kräftige Expansion – nachlassender Schub im kommenden Jahr," RWI Konjunkturbericht, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, pages 65, 03.
    7. Erik Haustein & Sven Schreiber, 2016. "Adjusting production indices for varying weather effects," IMK Working Paper 171-2016, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.

    More about this item

    Keywords

    weather; short term forecasting; bridge equations; forecast accuracy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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