消除迷雾:天气对就业报告及其资产价格反应的预测能力

IF 8.1 1区经济学 Q1 ECONOMICS

American Economic Review-Insights Pub Date : 2017-06-14 DOI:10.1257/AERI.20180432

Daniel J. Wilson

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引用次数: 7

摘要

本文利用大量的细粒度数据——超过100万个县月的观测数据——来估计天气对当地就业影响的动态面板数据模型。然后对拟合的县模型进行汇总，并用于生成天气对全国月度就业影响的样本内和样本外（nowcast）估计值。这些即时广播只使用给定就业报告之前可用的就业和天气数据，不仅可以显著预测就业报告中的意外成分，还可以预测就业报告发布当天的股票和债券市场回报。（JEL C53、G12、G17、H63、Q54、R23）

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Clearing the Fog: The Predictive Power of Weather for Employment Reports and Their Asset Price Responses

This paper exploits vast granular data—with over one million county-month observations—to estimate a dynamic panel data model of weather’s local employment effects. The fitted county model is then aggregated and used to generate in-sample and rolling out-of-sample (nowcast) estimates of the weather effect on national monthly employment. These nowcasts, which use only employment and weather data available prior to a given employment report, are significantly predictive not only of the surprise component of employment reports but also of stock and bond market returns on the days of employment reports. (JEL C53, G12, G17, H63, Q54, R23)

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来源期刊

American Economic Review-Insights ECONOMICS-

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期刊介绍： The journal American Economic Review: Insights (AER: Insights) is a publication that caters to a wide audience interested in economics. It shares the same standards of quality and significance as the American Economic Review (AER) but focuses specifically on papers that offer important insights communicated concisely. AER: Insights releases four issues annually, covering a diverse range of topics in economics.