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

Refet Gürkaynak, Burçin Kısacıkoğlu () and Jonathan H. Wright

No 7229, CESifo Working Paper Series from CESifo Group Munich

Abstract: Macroeconomic news announcements are elaborate and multi-dimensional. We consider a framework in which jumps in asset prices around macroeconomic news and monetary policy announcements reflect both the response to observed surprises in headline numbers and latent factors, reflecting other details of the release. The details of the 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 essentially combines OLS- and heteroscedasticity-based event study estimators in one step, showing that those methods are better thought of as complements rather than substitutes. The inclusion of a single latent factor greatly improves our ability to explain asset price movements around announcements.

Keywords: event study; bondmarkets; high-frequency data; identification (search for similar items in EconPapers)
JEL-codes: E43 E52 E58 G12 G14 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-cba and nep-mac
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Citations: View citations in EconPapers (2) Track citations by RSS feed

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Working Paper: Missing Events in Event Studies: Identifying the Effects of Partially-Measured News Surprises (2018) Downloads
Working Paper: Missing Events in Event Studies: Identifying the Effects of Partially-Measured News Surprises (2018) Downloads
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