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Structural Break Quantile-on-Quantile Regression×Regresheni ya Kuantili-juu-ya-Kuantili (QQ)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili2015-2020s2015
MwanzilishiExtension combining Sim & Zhou (2015) QQR framework with Bai-Perron structural break methodologySim and Zhou
AinaNonparametric quantile regression with structural breaksNonparametric quantile regression
Chanzo asiliaSim, N., and Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗
Majina mbadalaSB-QQR, structural-break QQ regression, quantile-on-quantile with structural breaks, QQR with regime shiftsQQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Zinazohusiana66
MuhtasariStructural 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.Quantile-on-quantile regression is a nonparametric technique that estimates how the quantiles of one variable depend on the quantiles of another. By combining standard quantile regression with local linear smoothing, it produces a full two-dimensional surface of slope coefficients indexed by both the quantile of the outcome and the quantile of the predictor, revealing heterogeneous and asymmetric dependency structures invisible to standard regression.
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  3. PUBLISHED

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ScholarGateLinganisha mbinu: Structural Break Quantile-on-Quantile Regression · Quantile-on-Quantile Regression. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare