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Causal change detection in possibly integrated systems: revisiting the money-income relationship

Causal change detection in possibly integrated systems: revisiting the money-income relationship
Causal change detection in possibly integrated systems: revisiting the money-income relationship
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 lag-augmented 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.
1479-8409
Shi, Shuping
a7438bac-31ee-4cde-be04-9f03a72c36ff
Hurn, Stan
d3fa9066-6f0e-4e61-9f6a-5b285c75d0b2
Phillips, Peter Charles Bonest
f67573a4-fc30-484c-ad74-4bbc797d7243
Shi, Shuping
a7438bac-31ee-4cde-be04-9f03a72c36ff
Hurn, Stan
d3fa9066-6f0e-4e61-9f6a-5b285c75d0b2
Phillips, Peter Charles Bonest
f67573a4-fc30-484c-ad74-4bbc797d7243

Shi, Shuping, Hurn, Stan and Phillips, Peter Charles Bonest (2019) Causal change detection in possibly integrated systems: revisiting the money-income relationship. Journal of Financial Econometrics. (In Press)

Record type: Article

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 lag-augmented 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.

Text
GrangerCausality_Level_Jan2019_pcb - Accepted Manuscript
Restricted to Repository staff only until 7 February 2021.
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Accepted/In Press date: 7 February 2019

Identifiers

Local EPrints ID: 428265
URI: https://eprints.soton.ac.uk/id/eprint/428265
ISSN: 1479-8409
PURE UUID: 58ce27c4-a690-4a93-bb7d-62e3d6bf2312
ORCID for Peter Charles Bonest Phillips: ORCID iD orcid.org/0000-0003-2341-0451

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Date deposited: 19 Feb 2019 17:30
Last modified: 25 May 2019 00:32

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