Working Paper: CEPR ID: DP13153
Authors: Refet S. Gurkaynak; Burcin Ksackoglu; Jonathan H. Wright
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 heteroskedasticity-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; bond markets; high-frequency data; identification
JEL Codes: E43; E52; E58; G12; G14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| macroeconomic news announcements (E60) | significant jumps in asset prices (G19) |
| observed surprises + latent factors (D80) | substantial portion of yield curve movements (E43) |
| headline surprises (Y60) | better understanding of asset price reactions (G19) |
| traditional OLS methods (C51) | fail to capture full extent of asset price changes (G19) |
| heteroskedasticity-based identification method (C21) | more accurate measure of asset price response (G19) |
| observed and latent news (G14) | hump-shaped response from expected short rates (E43) |