Copulas and Temporal Dependence

Brendan Beare

University of California at San Diego, Economics Working Paper Series from Department of Economics, UC San Diego

Abstract: An emerging literature in time series econometrics concerns the modeling of potentially nonlinear temporal dependence in stationary Markov chains using copula functions. We obtain sucient conditions for a geometric rate of mixing in models of this kind. Geometric beta-mixing is established under a rather strong sucient condition that rules out asymmetry and tail dependence in the copula function. Geometric rho-mixing is obtained under a weaker condition that permits both asymmetry and tail dependence. We verify one or both of these conditions for a range of parametric copula functions that are popular in applied work.

Keywords: copula; Markov chain; maximal correlation; mean square contingency; mixing; canonical correlatin; tail dependence (search for similar items in EconPapers)
Date: 2009-03-23
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Citations: View citations in EconPapers (6)

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Related works:
Journal Article: Copulas and Temporal Dependence (2010)
Working Paper: Copulas and Temporal Dependence (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:ucsdec:qt87p829d4

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