Copulas and Temporal Dependence
Econometrica · 2010 · Volume 78 · Issue 1
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 sufficient conditions for a geometric rate of mixing in models of this kind. Geometricβ-mixing is established under a rather strong sufficient condition that rules out asymmetry and tail dependence in the copula function. Geometricρ-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 correlation, tail dependence
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