Semiparametic Nonlinear Least-Squares Estimation of Truncated Regression Models

B-Tier
Journal: Econometric Theory
Year: 1992
Volume: 8
Issue: 1
Pages: 52-94

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

This article provides a semiparametric method for the estimation of truncated regression models where the disturbances are independent of the regressors before truncation. This independence property provides useful information on model identification and estimation. Our estimate is shown to be -consistent and asymptotically normal. A consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.

Technical Details

RePEc Handle
repec:cup:etheor:v:8:y:1992:i:01:p:52-94_01
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-25