Compara mètodes

	Regressió Quantil-sobre-Quantil amb Trencament Estructural	Prova de talls estructurals ARDL amb límits
Camp	Econometria	Econometria
Família	Regression model	Regression model
Any d'origen	2015-2020s	2001–2010s
Autor original	Extension combining Sim & Zhou (2015) QQR framework with Bai-Perron structural break methodology	Pesaran, Shin & Smith (bounds framework); structural break extensions by Bahmani-Oskooee, Enders & Jones, and others
Tipus	Nonparametric quantile regression with structural breaks	Cointegration / bounds test
Font seminal	Sim, N., and Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8.	Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326.
Àlies	SB-QQR, structural-break QQ regression, quantile-on-quantile with structural breaks, QQR with regime shifts	SB-ARDL bounds test, ARDL bounds test with structural break, Fourier ARDL bounds test, break-augmented bounds testing
Relacionats	6	6
Resum	Structural Break Quantile-on-Quantile Regression (SB-QQR) extends the quantile-on-quantile framework of Sim and Zhou (2015) by allowing regression slopes to differ across regimes separated by structural breaks. It maps how the effect of a predictor's quantile on an outcome's quantile changes not only across the full distributional space but also across distinct historical periods or policy regimes.	The structural break ARDL bounds test extends the Pesaran, Shin and Smith (2001) bounds testing framework to accommodate one or more structural breaks in the long-run relationship between time-series variables. By incorporating break dummies or smooth Fourier terms into the ARDL error-correction equation, it allows researchers to test for cointegration even when the data have experienced shifts in intercept or slope caused by policy changes, crises, or regime switches.