Publication Type
Journal Article
Version
submittedVersion
Publication Date
3-2024
Abstract
This paper provides a nonparametric test for deciding the dimensionality of a policy shock as manifest in the abnormal change in asset returns' stochastic covariance matrix, following the release of a macroeconomic announcement. We use high-frequency data in local windows before and after the event to estimate the covariance jump matrix, and then test its rank. We find a one-factor structure in the covariance jump matrix of the yield curve resulting from the Federal Reserve's monetary policy shocks prior to the 2007-2009 financial crisis. The dimensionality of policy shocks increased afterwards due to the use of unconventional monetary policy tools.
Keywords
Bootstrap, High-frequency data, Macroeconomic announcement, Rank test, Structural identification, Yield curve
Discipline
Econometrics
Research Areas
Econometrics
Publication
Review of Economics and Statistics
Volume
106
Issue
2
First Page
470
Last Page
482
ISSN
0034-6535
Identifier
10.1162/rest_a_01139
Publisher
Massachusetts Institute of Technology Press (MIT Press): 12 month embargo
Citation
LI, Jia; TODOROV, Viktor; and ZHANG, Qiushi.
Testing the dimensionality of policy shocks. (2024). Review of Economics and Statistics. 106, (2), 470-482.
Available at: https://ink.library.smu.edu.sg/soe_research/2563
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1162/rest_a_01139