Stability results for nonlinear vector autoregressions with an application to a nonlinear error correction model
AbstractThis 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. --
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Bibliographic InfoPaper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 2001,93.
Date of creation: 2001
Date of revision:
Geometric ergodicity; Markov chain; Mixing; Nonlinear error correction model; Nonlinear vector autoregressive process; Stability;
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- De Gooijer, Jan G. & Vidiella-i-Anguera, Antoni, 2004. "Forecasting threshold cointegrated systems," International Journal of Forecasting, Elsevier, vol. 20(2), pages 237-253.
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