Smoothed Estimating Equations for Instrumental Variables Quantile Regression

David Kaplan and Yixiao Sun

No 1314, Working Papers from Department of Economics, University of Missouri

Abstract: The moment conditions or estimating equations for instrumental variables quantile regression involves the discontinuous indicator function. We instead use smoothed estimating equations, with bandwidth h. This is known to allow higher-order expansions that justify bootstrap refinements for inference. Computation of the estimator also becomes simpler and more reliable, especially with (more) endogenous regressors. We show that the mean squared error of the vector of estimating equations is minimized for some h > 0, which also reduces the mean squared error of the parameter estimators. The same h also minimizes higher-order type I error for a χ2 test, leading to improved size-adjusted power. Our plug-in bandwidth consistently reproduces all of these properties in simulations.

Keywords: bandwidth choice; higher-order properties; instrumental variables; quantile regression; smoothing (search for similar items in EconPapers)
JEL-codes: C01 C12 C13 C21 C26 (search for similar items in EconPapers)
Date: 2013-09-05
New Economics Papers: this item is included in nep-ecm
Note: Length: 34 pgs.
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Citations: View citations in EconPapers (12)

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Related works:
Journal Article: SMOOTHED ESTIMATING EQUATIONS FOR INSTRUMENTAL VARIABLES QUANTILE REGRESSION (2017)
Working Paper: Smoothed estimating equations for instrumental variables quantile regression (2016)
Working Paper: SMOOTHED ESTIMATING EQUATIONS FOR INSTRUMENTAL VARIABLES QUANTILE REGRESSION (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:umc:wpaper:1314

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