This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

  1. Home
  2. Journals
  3. American Economic Review
  4. December 2020
  5. Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises

Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises

Download Full Text PDF

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, 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.

Citation

Gürkaynak, Refet S., Burçin Kisacikoğlu, and Jonathan H. Wright. 2020. "Missing Events in Event Studies: Identifying the Effects of Partially Measured News Surprises." American Economic Review, 110 (12): 3871-3912. DOI: 10.1257/aer.20181470

Additional Materials

JEL Classification

  • C51 Model Construction and Estimation
  • E43 Interest Rates: Determination, Term Structure, and Effects
  • E52 Monetary Policy
  • G12 Equities; Fixed Income Securities
  • G14 Information and Market Efficiency; Event Studies; Insider Trading