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Testing for a Unit Root in Autoregressive Moving‐average Models with Missing Data
Author(s) -
Shin Dong Wan,
Sarkar Sahadeb
Publication year - 1998
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00111
Subject(s) - autoregressive model , mathematics , unit root , estimator , statistics , autoregressive–moving average model , unit root test , series (stratigraphy) , ordinary least squares , asymptotic distribution , star model , missing data , time series , econometrics , autoregressive integrated moving average , cointegration , paleontology , biology
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.