Appendix M

Estimation of Tobit Model with Selection

(Source: Thomas [1])

The basic assumptions are that the error terms in Equations 5.4 and 5.5 are bivariate normal – that is, img, img– and are not correlated with the regressors. Therefore, a truncated bivariate normal distribution is used to derive the likelihood function for the Tobit model with selection. Specifically, an individual's conditional likelihood function is as follows:

(M.1) equation

Given the assumption of normality of the error terms, Equation (M.1) can be respecified as follows:

(M.2) equation

where

(M.3) equation

and img is the standard deviation of img for segment img, is the covariance between and for segment , and SBVN is the standard bivariate normal distribution. ...

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