The Tobit model is a statistical model proposed by James Tobin (1958) to describe the relationship between a non-negative dependent variable and an independent variable (or vector) . The term Tobit was derived from Tobin's name by truncating and adding -it by analogy with the probit model.
The model supposes that there is a latent (i.e. unobservable) variable . This variable linearly depends on via a parameter (vector) which determines the relationship between the independent variable (or vector) and the latent variable (just as in a linear model). In addition, there is a normally distributed error term to capture random influences on this relationship. The observable variable is defined to be equal to the latent variable whenever the latent variable is above zero and zero otherwise.
where is a latent variable:
Read more about Tobit Model: Consistency, Interpretation, Variations of The Tobit Model, The Likelihood Function, See Also
Famous quotes containing the word model:
“Socrates, who was a perfect model in all great qualities, ... hit on a body and face so ugly and so incongruous with the beauty of his soul, he who was so madly in love with beauty.”
—Michel de Montaigne (1533–1592)