2017-13 | June 2017
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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.
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Wilson, Daniel J. 2017. "Clearing the Fog: The Predictive Power of Weather for Employment Reports and their Asset Price Responses," Federal Reserve Bank of San Francisco Working Paper 2017-13. Available at https://doi.org/10.24148/wp2017-13