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Estimation in nonstationary random coefficient autoregressive models

  • István Berkes
  • Lajos Horváth
  • Shiqing Ling

We investigate the estimation of parameters in the random coefficient autoregressive (RCA) model X_k = (ϕ + b_k)X_k - 1 + e_k, where (ϕ, omega-super-2, σ-super-2) is the parameter of the process, , . We consider a nonstationary RCA process satisfying E log |ϕ + b_0| >= 0 and show that σ-super-2 cannot be estimated by the quasi-maximum likelihood method. The asymptotic normality of the quasi-maximum likelihood estimator for (ϕ, omega-super-2) is proven so that the unit root problem does not exist in the RCA model. Copyright 2009 Blackwell Publishing Ltd

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Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 30 (2009)
Issue (Month): 4 (07)
Pages: 395-416

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Handle: RePEc:bla:jtsera:v:30:y:2009:i:4:p:395-416
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