4.4 Article

Quantile regression with nonadditive fixed effects

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Summary: This paper develops generalized method of moments (GMM) estimation and inference procedures for quantile regression models. The proposed GMM estimator allows simultaneous estimation across multiple quantiles, leading to efficiency gains compared to standard methods. As an alternative, a minimum distance estimator over a given subset of quantiles is also proposed. The paper also provides specification tests for the imposed restrictions, and the estimators and tests are simple to implement in practice. Numerical evidence from Monte Carlo simulations is used to evaluate the finite sample properties of the methods. Finally, the methods are applied to estimate the effects of smoking on birthweight of live infants at the extreme bottom of the conditional distribution.

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