Probit with heteroscedasticity: an application to Indian poverty analysis

This study argues that in limited dependent variable models, when there is heteroscedasticity, a probit model with a heteroscedastic structure should be estimated. The problem is illustrated using unit record data from the Indian National Sample Survey to analyse the determinants of poverty at household level. It is found that these biases are large even with large number of observations because in the limited dependent variable case, the bias does not vanish asymptotically when the assumption of homoscedasticity breaks down. Both regression coefficients and marginal effects differ widely between probit and hetprobit models in this study.