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Weather adjustment of economic output

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  • Schreiber, Sven

Abstract

While recurring and regular variations of weather conditions are implicitly addressed by standard seasonal adjustment procedures of economic time series, extraordinary weather outcomes are not. We propose a way of measuring aggregate abnormal weather conditions based on available local measurements and a straightforward regression-based framework to analyze their impact on German monthly total industrial and construction-sector production data, and find noticeable effects. In the historical - and seasonally adjusted - construction sector growth data the extra explanatory power of the weather regressors over a benchmark univariate autoregressive model even exceeds 50% of the variation. The estimated effects of weather deviations can be subtracted from the already seasonally adjusted data to obtain (seasonally as well as) weather adjusted series, which might capture economic developments better. The estimated adjustments are quantitatively relevant also for aggregate output (GDP).

Suggested Citation

  • Schreiber, Sven, 2017. "Weather adjustment of economic output," Discussion Papers 2017/5, Free University Berlin, School of Business & Economics.
    • Handle: RePEc:zbw:fubsbe:20175
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    References listed on IDEAS

    as
    1. Schreiber, Sven & Soldatenkova, Natalia, 2016. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 166-187.
    2. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.
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    4. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    5. 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.
    6. Michael Boldin & Jonathan H. Wright, 2015. "Weather-Adjusting Economic Data," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 46(2 (Fall)), pages 227-278.
    7. Dombi, Akos & Grigoriadis, Theocharis, 2017. "Ancestry, Diversity & Finance: Evidence from Transition Economies," Discussion Papers 2017/4, Free University Berlin, School of Business & Economics.
    8. 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.
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    More about this item

    Keywords

    weather; business cycle; nowcasting;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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