Estimation in Random Coefficient Autoregressive Models

16 Pages Posted: 11 Apr 2006

See all articles by Alexander Aue

Alexander Aue

University of Utah - Department of Mathematics

Lajos Horváth

University of Utah - Department of Mathematics

Josef Steinebach

University of Cologne - Department of Mathematics

Abstract

We propose the quasi-maximum likelihood method to estimate the parameters of an RCA(1) process, i.e. a random coefficient autoregressive time series of order 1. The strong consistency and the asymptotic normality of the estimators are derived under optimal conditions.

Suggested Citation

Aue, Alexander and Horváth, Lajos and Steinebach, Josef, Estimation in Random Coefficient Autoregressive Models. Journal of Time Series Analysis, Vol. 27, No. 1, pp. 61-76, January 2006. Available at SSRN: https://ssrn.com/abstract=875063 or http://dx.doi.org/10.1111/j.1467-9892.2005.00453.x

Alexander Aue

University of Utah - Department of Mathematics

1645 E. Campus Center
Salt Lake City, UT 84112
United States

Lajos Horváth (Contact Author)

University of Utah - Department of Mathematics ( email )

1645 E. Campus Center
Salt Lake City, UT 84112
United States
801 581-8159 (Phone)

Josef Steinebach

University of Cologne - Department of Mathematics ( email )

Albertus-Magnus-Platz
Cologne, 50923
Germany

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