A Measure of Comovement for Economic Variables: Theory and Empirics

By Christophe Croux, M. Forni, L. Reichlin. Review of Economics and Statistics, 2001

395 citations recorded by the source corpus.

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.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/cee8878b87206f11f55cb31bc2567ac86b699825

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Citations in the corpus

Will business cycles in the Euro Area converge: a critical survey of empirical research (2008, methodology): “Croux et al. (2001) suggest that for more than two series, one should look at the cohesion of these series, defined as the (weighted) average of the binary dynamic correlation coefficients.”
Measuring Synchronicity and Co-Movement of Business Cycles with an Application to the Euro Area (2007, methodology): “…the extracted cycles by their corresponding trend components, we construct the output gap series used in the empirical analysis below.7 7Since Croux et al. (2001) show that synchronicity of cycles differs across frequency bands, we examined whether our results are sensitive to the…”
Do european business cycles look like one (2008, background): “…examples are the studies of Agresti and Mojon (2001), Artis, Krolzig, and Toro (2002), Artis, Kontolemis, and Osborn (1997), Bergman (2004), Camacho, Perez-Quiros, and Saiz (2004), Croux, Forni, and Reichlin (2001), Dueker and Wesche (2003), Guha and Banerji (1998), and Harding and Pagan (2002).”
Quantile coherency: A general measure for dependence between cyclical economic variables (2015, neutral): “This dependence stays hidden when classical measures based on linear correlation and traditional cross-spectral analysis are used; see Croux et al. (2001), Ning and Chollete (2009) and Fan and Patton (2014).”
The Impact of the Global Financial Crisis on Business Cycles in Asian Emerging Economies (2010, neutral): “An alternative measure of synchronization in the case of business cycles is dynamic correlation, as was proposed by Croux et al. (2001).”