CONDITIONAL MOMENT RESTRICTIONS IN CENSORED AND TRUNCATED REGRESSION MODELS

B-Tier
Journal: Econometric Theory
Year: 2001
Volume: 17
Issue: 5
Pages: 863-888

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

Censored and truncated regression models with unknown distribution are important in econometrics. This paper characterizes the class of all conditional moment restrictions that lead to √n-consistent estimators for these models. The semiparametric efficiency bound for each conditional moment restriction is derived. In the case of a nonzero bound it is shown how an estimator can be constructed and that an appropriately weighted version can attain the efficiency bound. These estimators also work when the disturbance is independent of the regressors. The paper discusses combining conditional moment restrictions for more efficient estimation in this case.

Technical Details

RePEc Handle
repec:cup:etheor:v:17:y:2001:i:05:p:863-888_17
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-26