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A Measure Of Comovement For Economic Variables: Theory And Empirics

Christophe Croux, Mario Forni () and Lucrezia Reichlin ()

The Review of Economics and Statistics, 2001, vol. 83, issue 2, 232-241

Abstract: This paper proposes a measure of dynamic comovement between (possibly many) time series and names it cohesion. The measure is defined in the frequency domain and is appropriate for processes that are costationary, possibly after suitable transformations. In the bivariate case, the measure reduces to dynamic correlation and is related, but not equal, to the well known quantities of coherence and coherency. Dynamic correlation on a frequency band equals (static) correlation of bandpass-filtered series. Moreover, long-run correlation and cohesion relate in a simple way to co-integration. Cohesion is useful to study problems of business-cycle synchronization, to investigate short-run and long-run dynamic properties of multiple time series, and to identify dynamic clusters. We use state income data for the United States and GDP data for European nations to provide an empirical illustration that is focused on the geographical aspects of business-cycle fluctuations. © 2001 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Date: 2001
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Related works:
Working Paper: A measure of co-movement for economic variables: theory and empirics (2001)
Working Paper: A Measure of Comovement for Economic Variables: Theory and Empirics (1999) Downloads
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The Review of Economics and Statistics is currently edited by Amitabh Chandra, Olivier Coibion, Bryan S. Graham, Shachar Kariv, Amit K. Khandelwal, Asim Ijaz Khwaja, Brigitte C. Madrian and Rohini Pande

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