Bandingkan metode

	Model MA Struktural Break	Model ARIMA (Autoregressive Integrated Moving Average)
Bidang	Ekonometrika	Ekonometrika
Keluarga	Regression model	Regression model
Tahun asal	1989–1992	1970
Pencetus	Perron (1989); Zivot & Andrews (1992)	George Box and Gwilym Jenkins
Tipe	Time series model with structural change	Time series forecasting model
Sumber perintis	Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361–1401.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Alias	MA model with structural change, broken MA model, MA with regime shift, structural break moving average	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Terkait	5	6
Ringkasan	A Moving Average (MA) time series model augmented to accommodate one or more structural breaks — abrupt shifts in the mean, variance, or MA coefficients occurring at known or unknown break dates. Ignoring structural breaks in an MA process inflates forecast errors and distorts inference on the error dynamics.	The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.