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• W2889616835 abstract "Macroeconomic news announcements are elaborate and multidimensional. We consider a framework in which jumps in asset prices around announcements reflect both the response to observed surprises in headline numbers and to latent factors, reflecting other news in the release. Non-headline news, for which there are no expectations surveys, is unobservable to the econometrician but nonetheless elicits a market response. We estimate the model by the Kalman filter, which efficiently combines OLS and heteroskedasticity-based event study estimators in one step. With the inclusion of a single latent surprise factor, essentially all yield curve variance in event windows are explained by news. (JEL C51, E43, E52, G12, G14)" @default.
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• W2889616835 date "2020-12-01" @default.
• W2889616835 modified "2023-10-17" @default.
• W2889616835 title "Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises" @default.
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• W2889616835 doi "https://doi.org/10.1257/aer.20181470" @default.
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