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Cross-Quantilogram×Kvantilna regresija metodom momenata×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20122004
TvoracOliver Linton and Yoon-Jin WhangRoger Koenker and colleagues
VrstaCorrelation measureDistribution regression
Temeljni izvorLinton, O., & Whang, Y. J. (2012). Quantile comparisons of time series data. Journal of Econometrics, 170(2), 242-257. link ↗Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. DOI ↗
Drugi naziviGMM quantile regression
Srodne33
SažetakThe cross-quantilogram extends the cross-correlogram concept to quantile pairs of two time series, measuring dependence at different quantile levels. Introduced by Linton and Whang (2012), it captures how shocks at specific quantile levels in one series relate to movements in another, enabling asymmetric dependence analysis. This approach is particularly valuable when downside and upside risk correlations differ materially.Method of Moments Quantile Regression combines moment-based estimation (GMM) with quantile regression to estimate distribution parameters while handling endogeneity, panel structure, and dynamic relationships. Introduced by Koenker (2004) and developed by Machado and Mata (2005), it enables distributional analysis (not just mean regression) in complex settings like dynamic panels and instrumental-variable contexts. This approach is powerful for understanding heterogeneity in treatment effects and policy impacts.
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ScholarGateUsporedite metode: Cross-Quantilogram · Method of Moments Quantile Regression. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare