Regression modelRobust regression

Method of Moments Quantile Regression

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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Sources

  1. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. DOI: 10.1016/j.jmva.2004.04.008
  2. Machado, J. A., & Mata, J. (2005). Low wage workers and the wage Kuznets curve: Heterogeneity across quantiles. International Journal of Manpower, 26(7-8), 694-712. DOI: 10.1108/01437720510627225

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Referenced by

ScholarGateMethod of Moments Quantile Regression (Method of Moments for Quantile Regression). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/method-of-moments-quantile-regression