Copulas and Temporal Dependence

• 成果类型: Article
• 署名作者: Beare, Brendan K.
• 署名单位: University of California System; University of California San Diego
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA8152
• 发表日期: 2010
• 页码: 395-410
• 关键词: CENTRAL-LIMIT-THEOREM; models

摘要

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. Geometric beta-mixing is established under a rather strong sufficient condition that rules out asymmetry and tail dependence in the copula function. Geometric -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.