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चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।

संरचनात्मक ब्रेक एनएआरडीएल×सदिश त्रुटि सुधार मॉडल (VECM)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष2014–20181987
प्रवर्तकShin, Yu & Greenwood-Nimmo (NARDL base); structural break extensions by subsequent applied researchersRobert F. Engle and Clive W. J. Granger
प्रकारNonlinear cointegration with structural breaksMultivariate time-series model
मौलिक स्रोतShin, 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. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
उपनामSB-NARDL, NARDL with structural breaks, nonlinear ARDL with break, asymmetric ARDL structural breakVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
संबंधित65
सारांशStructural 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 Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.
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  3. PUBLISHED

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