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Swati Shukla

Publications and source records attributed to Swati Shukla.

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L-Estimation Approach to Tobit Models with Endogeneity and Weakly Dependent Errors

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.

stat.ME

Generalized M-Estimation in Censored Regression Model under Endogeneity

We propose and study M-estimation to estimate the parameters in the censored regression model in the presence of endogeneity, i.e., the Tobit model. In the course of this study, we follow two-stage procedures: the first stage consists of applying control function procedures to address the issue of endogeneity using instrumental variables, and the second stage applies the M-estimation technique to estimate the unknown parameters involved in the model. The large sample properties of the proposed estimators are derived and analyzed. The finite sample properties of the estimators are studied through Monte Carlo simulation and a real data application related to women's labor force participation.

stat.ME