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A Recurrence Plot-Based Distance Measure Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Synchronicity Assessment Using a Non-parametric Dynamic Dissimilarity Measure

Authors : Patrick Crowley, Christopher Trombley

Published in: Translational Recurrences

Publisher: Springer International Publishing

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Abstract

In this paper, we introduce a non-parametric dynamic dissimilarity measure (DDM) of synchronicity based on recurrence plots, which is particularly suited to use in small samples. The measure attempts to capture the dissimilarity of the topology of the dynamics of time series, based on an epoch analysis of the cumulative sums of data series. The measure is applied to US State macroeconomic data and is used to assess how synchronous US State business cycle variables are with US aggregates.

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previous chapter Recurrence Quantification as an Analysis of Temporal Coordination with Complex Signals
next chapter Understanding the Interrelationship Between Commodity and Stock Indices Daily Movement Using ACE and Recurrence Analysis
Appendix
Available only for authorised users
Footnotes
1
Norbert Marwan’s website catalogues all the articles published using recurrence plots and RQA, and is a veritable mine of information on this topic. See http://​www.​recurrence-plot.​tk.
 
2
Crowley and Schultz [19] have termed this phenomena “intermittent synchronicity”.
 
3
Of course fiscal policy enacted by Congress can be aimed at a particular set of States (for example disaster relief after a hurricane), or its impact might incidentally give greater benefits to a specific state (for example defense spending in relation to the Californian economy). Similarly monetary policy that benefits financial institutions might have a greater impact on those regions of the country that have a greater concentration of financial industry (such as New York and Illinois).
 
4
There is little research as to the nature of the US monetary union in terms of its macroeconomic characteristics. This is partly due to the severe data limitations on availability of State macroeconomic data.
 
5
The original and seminal contribution here was made by [22].
 
6
Two series had to be spliced together to create this series. Details are available from the author on request.
 
7
We acknowledge one of the reviewers of this paper for suggesting this approach.
 
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Metadata
Title
Synchronicity Assessment Using a Non-parametric Dynamic Dissimilarity Measure
Authors
Patrick Crowley
Christopher Trombley
Copyright Year
2014
Book
Translational Recurrences

Print ISBN: 978-3-319-09530-1

Electronic ISBN: 978-3-319-09531-8

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-09531-8_12

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