Quantile Regression under Misspecification

51 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Sensitivity to Missing Data Assumptions: Theory and an Evaluation of the U.S. Wage Structure (2010, methodology): “We begin our investigation of the sensitivity of these findings to alternative missing data assumptions by revisiting the results of Angrist et al. (2006) regarding changes across Decennial Censuses in the quantile specific returns to schooling.”
Instrumental quantile regression inference for structural and treatment effect models (2006, unknown): “those in Angrist et al. (2003). Proof.”
Inference on Directionally Differentiable Functions (2014, unknown): “Under appropriate restrictions, the estimator θ̂n for θ0 converges in distribution in ` ∞([ , 1 − ]) for any > 0 (Angrist et al., 2006).11 Hence, we may test shape restrictions on θ0 by letting H ≡ {θ : [ , 1− ]→ R : 〈θ, θ〉H ∞} 〈θ1, θ2〉H ≡ ∫ 1− θ1(τ)θ2(τ)dτ , (69) and considering appropriate…”