Testing for unit roots in autoregressive-moving average models of unknown order

By S. E. Said, D. Dickey. 1984

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Citations in the corpus

Deep Learning Stock Volatility with Google Domestic Trends (2015, background): “Additionally, it is worth noting here that all these 25 time series are stationary in the sense that their unit-root null hypotheses have p-values less than 0.05 in the Augmented Dickey-Fuller test [13].”
ON THE ASYMPTOTICS OF ADF TESTS FOR UNIT ROOTS (2002, methodology): “extended by Said and Dickey([5]) to allow for finite ARMA processes of unknown order.”
On the sustainability of current account deficits: evidence from four ASEAN countries (2003, methodology): “The classical unit root tests, namely, the Augmented Dickey-Fuller (ADF) test (see Dickey and Fuller, 1981; Said and Dickey, 1984) and the Phillips and Perron (1988) test provide convenient procedures to determine the univariate properties of time series data.”
Testing Models of Low‐Frequency Variability (2006, methodology): “with additional lags as in Said and Dickey (1984) , by grafting stationary ARMA models”
Residual‐Based Block Bootstrap for Unit Root Testing (2003, methodology): “Under some assumptions on the rate with which p increases, Said and Dickey (1984) showed that in the unit root case and if = 0, ˆ � DF �C = 1+OP �n −1� . An extension of the arguments presented there”
Testing for cointegration using the Johansen methodology when variables are near-integrated: size distortions and partial remedies (2010, unknown): “Table 4 provides the results from the traditional augmented Dickey– Fuller (ADF) test ( Said and Dickey 1984 ), the KPSS test (Kwiatkowski et al. 1992) and the Zivot and Andrews (1992) test.”
DATA DEPENDENT RULES FOR SELECTION OF THE NUMBER OF LEADS AND LAGS IN THE DYNAMIC OLS COINTEGRATING REGRESSION (2008, unknown): “[19] Said, S.”
Non-Stationary Frequency Analysis of Extreme Water Level: Application of Annual Maximum Series and Peak-over Threshold Approaches (2017, methodology): “The test focus is on determining whether β equals to zero (which means that the timeseries has a unit root) (Said and Dickey 1984).”
Testing for a unit root in the nonlinear STAR framework (2003, methodology): “Assumingthat these serially correlated errors enter in a linear fashion, then following the well-established Dickey and Fuller (1979) and Said and Dickey (1984) corrections, we may extend model (7 )t o”