天气,商业周期分析中被遗忘的因素

Roland Doehrn, Philipp an de Meulen
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引用次数: 7

摘要

在异常天气期间,预报员面临着解释经济数据的问题:哪些部分可以追溯到潜在的经济趋势,哪些部分源于特殊的天气影响?在本文中,我们讨论了将天气相关因素与商业周期相关因素对经济指标的影响区分开来的方法。我们发现天气变量至少对一些月度指标有显著影响。因此,在这些指标范围内控制天气影响,就有机会提高基于指标的预报的准确性。关注德国的季度GDP增长,我们发现RWI短期预测模型的准确性有所提高,但进步很小且不显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weather, the Forgotten Factor in Business Cycle Analyses
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.
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