방법 비교

	구조적 단절 NARDL	ARIMA 모형 (자기회귀 누적 이동평균)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	2014–2018	1970
창시자	Shin, Yu & Greenwood-Nimmo (NARDL base); structural break extensions by subsequent applied researchers	George Box and Gwilym Jenkins
유형	Nonlinear cointegration with structural breaks	Time series forecasting model
원전	Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
별칭	SB-NARDL, NARDL with structural breaks, nonlinear ARDL with break, asymmetric ARDL structural break	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
관련	6	6
요약	Structural Break NARDL extends the Nonlinear Autoregressive Distributed Lag (NARDL) bounds-testing framework by explicitly accommodating one or more structural breaks in the long-run relationship. It separates positive and negative changes in the regressor, tests for cointegration, and allows regime shifts, providing a richer picture of asymmetric and break-sensitive dynamics between variables.	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.