Testing for a Unit Root in Autoregressive Moving-average Models with Missing Data

Testing for a single autoregressive unit root in an autoregressive moving‐average (ARMA) model is considered in the case when data contain missing values. The proposed test statistics are based on an ordinary least squares type estimator of the unit root parameter which is a simple approximation of...

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Veröffentlicht in:Journal of time series analysis 1998-09, Vol.19 (5), p.601-608
Hauptverfasser: Shin, Dong Wan, Sarkar, Sahadeb
Format: Artikel
Sprache:eng
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Zusammenfassung:Testing for a single autoregressive unit root in an autoregressive moving‐average (ARMA) model is considered in the case when data contain missing values. The proposed test statistics are based on an ordinary least squares type estimator of the unit root parameter which is a simple approximation of the one‐step Newton–Raphson estimator. The limiting distributions of the test statistics are the same as those of the regression statistics in AR(1) models tabulated by Dickey and Fuller (Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 74 (1979), 427–31) for the complete data situation. The tests accommodate models with a fitted intercept and a fitted time trend.
ISSN:0143-9782
1467-9892
DOI:10.1111/1467-9892.00111