Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 2001,93
This paper improves previous sufficient conditions for stationarity obtained in the context of a general nonlinear vector autoregressive model with nonlinear autoregressive conditional heteroskedasticity. The results are proved by using the stability theory developed for Markov chains. Stationarity, existence of second moments of the stationary distribution, and useful mixing results are obtained by establishing appropriate versions of geometric ergodicity. The results are applied to a nonlinear error correction model to obtain an analog of Granger's representation theorem.
Geometric ergodicity Markov chain Mixing Nonlinear error correction model Nonlinear vector autoregressive process Stability