A Simple Ordered Data Estimator For Inverse Density Weighted Functions

Arthur Lewbel and Susanne Schennach

No 557, Boston College Working Papers in Economics from Boston College Department of Economics

Abstract: 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.

Keywords: Semiparametric; Conditional Expectation; Density Estimation; Binary Choice; Binomial Response (search for similar items in EconPapers)
JEL-codes: C14 C21 C25 J24 (search for similar items in EconPapers)
Date: 2003-04-04, Revised 2005-05-01
New Economics Papers: this item is included in nep-dcm and nep-ecm
Note: Previously circulated as "A Simple Ordered Data Estimator for Inverse Density Weighted Expectations"
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Forthcoming, Journal of Econometrics

Downloads: (external link)
http://fmwww.bc.edu/EC-P/wp557.pdf main text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:bocoec:557

Access Statistics for this paper

More papers in Boston College Working Papers in Economics from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().