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Regressão Quantil-sobre-Quantil em Painel×Painel OLS (Mínimos Quadrados Ordinários Agregados)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem2015 (QQ); panel applications from ~20181986-2003
Autor originalSim and Zhou (cross-section QQ); panel extension in applied energy/finance econometricsClassical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010)
TipoNonparametric quantile regressionLinear panel regression
Fonte seminalSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Outros nomesPanel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regressionpooled OLS, pooled ordinary least squares, panel least squares, POLS
Relacionados64
ResumoPanel quantile-on-quantile (QQ) regression jointly maps any quantile of the outcome distribution onto any quantile of the predictor distribution across multiple cross-sectional units observed over time. It generalises Sim and Zhou's (2015) cross-sectional QQ framework to a panel setting, revealing a full dependence surface rather than a single average effect, while accounting for individual heterogeneity through fixed or random effects correction.Panel OLS — also called Pooled OLS — applies the classical ordinary least squares estimator to panel data by stacking all cross-sectional units and time periods into a single sample. It estimates one common set of slope coefficients under the assumption that the intercept and slopes are homogeneous across units and time.
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ScholarGateComparar métodos: Panel Quantile-on-Quantile Regression · Panel OLS. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare