手法を比較

	構造的ブレーク NARDL	自己回帰和分移動平均モデル (ARIMA Model)
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	2014–2018	1970
提唱者	Shin, Yu & Greenwood-Nimmo (NARDL base); structural break extensions by subsequent applied researchers	George Box and Gwilym Jenkins
種類	Nonlinear cointegration with structural breaks	Time series forecasting model
原典	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.
別名	SB-NARDL, NARDL with structural breaks, nonlinear ARDL with break, asymmetric ARDL structural break	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
関連	6	6
概要	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.