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Quantile-on-Quantile (QQ) 회귀×조건부 분위수 회귀×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도20151978
창시자Sim and ZhouKoenker & Bassett
유형Nonparametric quantile regressionConditional quantile regression
원전Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
별칭QQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regressionconditional quantile regression, regression quantiles, Kantil Regresyon
관련65
요약Quantile-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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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