Chen, Xiaohong: Nonlinearity and Temporal Dependence
World Conference Econometric Society, 2000, Seattle

Marine Carrasco, CREST
Xiaohong Chen, London School of Economics
Lars P. Hansen, University of Chicago
Nonlinearity and Temporal Dependence
Session: C-11-18  Tuesday 15 August 2000  by Chen, Xiaohong
This paper studies how nonlinearities influence temporal dependence in scalar diffusion models. We focus on two notions of temporal dependence: beta-mixing and rho-mixing. We show that beta-mixing and rho-mixing with exponential decay are essentially equivalent concepts for scalar diffusions. For stationary diffusions that fail to be rho-mixing, we show that they are still beta-mixing except that the decay rates are slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. Some have spectral densities that diverge at frequency zero in a manner similar to that of stochastic processes with long memory. Finally we show how nonlinear, state-dependent, Poisson sampling alters the unconditional distribution as well as the temporal dependence.


File created by Jurgen Doornik with eswc2000.ox on 2-01-2001