A Simple Ordered Data Estimator For Inverse Density Weighted Functions
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 endogeneous binary choice, willingness to pay, selection, and treatment models.
|Date of creation:||04 Apr 2003|
|Date of revision:||01 May 2005|
|Publication status:||forthcoming, Journal of Econometrics|
|Note:||Previously circulated as "A Simple Ordered Data Estimator for Inverse Density Weighted Expectations"|
|Contact details of provider:|| Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA|
Web page: http://fmwww.bc.edu/EC/
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