A General Asymptotic Theory for Time Series Models

Shiqing Ling and Michael McAleer
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Shiqing Ling: Department of Mathematics, Hong Kong University of Science and Technology

No CIRJE-F-670, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: This paper develops a general asymptotic theory for the estimation of strictly stationary and ergodic time series models. Under simple conditions that are straightforward to check, we establish the strong consistency, the rate of strong convergence and the asymptotic normality of a general class of estimators that includes LSE, MLE, and some M-type estimators. As an application, we verify the assumptions for the long-memory fractional ARIMA model. Other examples include the GARCH(1,1) model, random coefficient AR(1) model and the threshold MA(1) model.

New Economics Papers: this item is included in nep-ecm, nep-ets and nep-pke
Date: 2009-09

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Persistent link: http://EconPapers.repec.org/RePEc:tky:fseres:2009cf670

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