Semiparametric Generalized Least Squares in the Multivariate Nonlinear Regression Model

B-Tier
Journal: Econometric Theory
Year: 1992
Volume: 8
Issue: 2
Pages: 203-222

Score contribution per author:

2.018 = (α=2.02 / 1 authors) × 1.0x B-tier

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

Abstract

Asymptotically efficient estimates for the multiple equations nonlinear regression model are obtained in the presence of heteroskedasticity of unknown form. The proposed estimator is a generalized least squares based on nonparametric nearest neighbor estimates of the conditional variance matrices. Some Monte Carlo experiments are reported.

Technical Details

RePEc Handle
repec:cup:etheor:v:8:y:1992:i:02:p:203-222_01
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-25