L-Estimation Approach to Tobit Models with Endogeneity and Weakly Dependent Errors
Methodology
2025-09-10 v3
Abstract
This article introduces an L-estimator for the semiparametric Tobit model with endogenous regressors. The estimation procedure follows a two-stage approach: the first stage employs least squares, while the second stage utilizes the L-estimation technique. We establish the large-sample properties of the proposed estimators under weakly dependent data. The utility of the proposed methodology is demonstrated for various simulated data and a benchmark real data set.
Keywords
Cite
@article{arxiv.2405.19145,
title = {L-Estimation Approach to Tobit Models with Endogeneity and Weakly Dependent Errors},
author = {Swati Shukla and Subhra Sankar Dhar and Shalabh},
journal= {arXiv preprint arXiv:2405.19145},
year = {2025}
}
Comments
In the present version of the article, the following significant changes have been made. (1) The mathematical assumptions are more elaborately written. (2) The effect of the first stage has been incorporated in the theoretical results. (3) The dependent structure has been modified