Autori
Ruidong, Han
Xinghui, Wang
Shuhe, Hu

Titolo
Asymptotics of the weighted least squares estimation for AR(1) processes with applications to confidence intervals
Periodico
Statistical methods & applications : Journal of the Italian Statistical Society
Anno: 2018 - Volume: 27 - Fascicolo: 3 - Pagina iniziale: 479 - Pagina finale: 490

For the first-order autoregressive model, we establish the asymptotic theory of the weighted least squares estimations whether the underlying autoregressive process is stationary, unit root, near integrated or even explosive under a weaker moment condition of innovations. The asymptotic limit of this estimator is always normal. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. An empirical likelihood confidence interval is proposed for interval estimations of the autoregressive coefficient. The results improve the corresponding ones of Chan et al. (Econ Theory 28:705–717, 2012). Some simulations are conducted to illustrate the proposed method.



SICI: 1618-2510(2018)27:3<479:AOTWLS>2.0.ZU;2-P

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