Estimation in Nonstationary Random Coefficient Autoregressive Models

22 Pages Posted: 20 Jun 2009

See all articles by István Berkes

István Berkes

affiliation not provided to SSRN

Lajos Horváth

University of Utah - Department of Mathematics

Shiqing Ling

Hong Kong University of Science & Technology (HKUST) - Department of Mathematics

Date Written: 0000

Abstract

0kk−1kkWe investigate the estimation of parameters in the random coefficient autoregressive (RCA) model X = (ϕ + b)X + e, where (ϕ, ω2, σ2) is the parameter of the process, , . We consider a nonstationary RCA process satisfying E log |ϕ + b| ≥ 0 and show that σ2 cannot be estimated by the quasi-maximum likelihood method. The asymptotic normality of the quasi-maximum likelihood estimator for (ϕ, ω2) is proven so that the unit root problem does not exist in the RCA model. k k k−1 k

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Suggested Citation

Berkes, István and Horváth, Lajos and Ling, Shiqing, Estimation in Nonstationary Random Coefficient Autoregressive Models (0000). Journal of Time Series Analysis, Vol. 30, Issue 4, pp. 395-416, July 2009. Available at SSRN: https://ssrn.com/abstract=1423149 or http://dx.doi.org/10.1111/j.1467-9892.2009.00615.x

István Berkes (Contact Author)

affiliation not provided to SSRN

No Address Available

Lajos Horváth

University of Utah - Department of Mathematics ( email )

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

Shiqing Ling

Hong Kong University of Science & Technology (HKUST) - Department of Mathematics

Rm. 3461, Lift 25-26
Clear Water Bay
Kowloon
Hong Kong

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