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Quantile ARDL×Method of Moments Quantile Regression×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan20062004
GrondleggerRoger Koenker and Zhijie XiaoRoger Koenker and colleagues
TypeConditional distribution modelDistribution regression
Oorspronkelijke bronKoenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. DOI ↗
AliassenQuantile ARDLGMM quantile regression
Verwant33
SamenvattingQARDL (Quantile Autoregressive Distributed Lag) combines quantile regression with ARDL modeling to estimate conditional relationships at different points of the distribution, revealing heterogeneous short-run and long-run effects. Introduced by Koenker and Xiao (2006) and refined by Cho et al. (2015), it captures how the effect of explanatory variables on outcomes varies across quantiles, essential for understanding tail behavior and distributional impacts rather than just mean effects.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.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: QARDL · Method of Moments Quantile Regression. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare