Publication Type
Journal Article
Version
submittedVersion
Publication Date
12-2020
Abstract
This paper re-examines changes in the causal link between money and income in the United States over the past half century (1959-2014). Three methods for the data-driven discovery of change points in causal relationships are proposed, all of which can be implemented without prior detrending of the data. These methods are a forward recursive algorithm, a rolling window algorithm, and a recursive evolving algorithm all of which utilize subsample tests of Granger causality within a lagaugmented vector autoregressive framework. The limit distributions for these subsample Wald tests are provided. Bootstrap methods are developed to control family-wise size in the implementation of the recursive testing algorithms. The results from a suite of simulation experiments suggest that the recursive evolving window algorithm provides the most reliable results, followed by the rolling window method. The forward expanding window procedure is shown to have the worst performance. Both the rolling window and recursive evolving approaches find evidence of Granger causality running from money to income during the Volcker period in the 1980s. The forward algorithm does not find any evidence of causality over the entire sample period.
Keywords
money-income causality, subsample Wald tests, time-varying Granger causality
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Financial Econometrics
Volume
18
Issue
1
First Page
158
Last Page
180
ISSN
1479-8409
Identifier
10.1093/jjfinec/nbz004
Publisher
Oxford University Press (OUP): Policy F - Oxford Open Option D
Citation
1
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/10.1093/jjfinec/nbz004