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A simple ordered data estimator for inverse density weighted expectations
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DOI：10.1016/j.jeconom.2005.08.005.png)
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Abstract
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We consider estimation of means of functions that are scaled by an unknown density, or equivalently, integrals of conditional expectations. The ordered data estimator we provide is root n consistent, asymptotically normal, and is numerically extremely simple, involving little more than ordering the data and summing the results. No sample-size-dependent smoothing is required. A similarly simple estimator is provided for the limiting variance. The proofs include new limiting distribution results for functions of nearest-neighbor spacings. Potential applications include endogenous binary choice, willingness to pay, selection, and treatment models. (c) 2005 Elsevier B.V. All rights reserved.
Keywords:
semiparametric
conditional expectation
density estimation
binary choice
binomial response
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