Missing Events in Event Studies:
Identifying the Effects of Partially-Measured News Surprises
DECEMBER 12, 2019
Abstract: Macroeconomic news announcements are elaborate and multi-dimensional. 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, are unobservable to the econometrician but nonetheless elicit a market response. We estimate the model by the Kalman filter, which efficiently combines OLSand 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.