September 2012
Intermediate to advanced
286 pages
8h 7m
English
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,
,
– 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:
Given the assumption of normality of the error terms, Equation (M.1) can be respecified as follows:
where
(M.3) ![]()
and
is the standard deviation of
for segment
, is the covariance between and for segment , and SBVN is the standard bivariate normal distribution. ...
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