EFFICIENCY BOUNDS FOR SEMIPARAMETRIC ESTIMATION OF INVERSE CONDITIONAL-DENSITY-WEIGHTED FUNCTIONS

B-Tier
Journal: Econometric Theory
Year: 2009
Volume: 25
Issue: 3
Pages: 847-855

Score contribution per author:

2.011 = (α=2.01 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Consider the unconditional moment restriction E[m(y, υ, w; π0)/fV|w (υ|w) −s (w; π0)] = 0, where m(·) and s(·) are known vector-valued functions of data (y┬, υ, w┬)┬. The smallest asymptotic variance that $\root \of n $-consistent regular estimators of π0 can have is calculated when fV|w(·) is only known to be a bounded, continuous, nonzero conditional density function. Our results show that “plug-in” kernel-based estimators of π0 constructed from this type of moment restriction, such as Lewbel (1998, Econometrica 66, 105–121) and Lewbel (2007, Journal of Econometrics 141, 777–806), are semiparametric efficient.

Technical Details

RePEc Handle
repec:cup:etheor:v:25:y:2009:i:03:p:847-855_09
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-25