| dc.description.abstract | Abstract:
In this paper we develop a full information maximum likelihood method for the estimation of a joint
model for the choice of length of schooling and the corresponding earnings equation. The model for
schooling is assumed to be an ordered probit model, whereas the earnings equation is allowed to be
very general with explanatory variables that are flexible transformations of schooling and experience.
The coefficients associated with length of schooling and experience are allowed to be random and all
the random terms of the model may be correlated. Under normality assumptions, we show that the
joint probability distribution for schooling and earnings can be expressed on a closed form that is
tractable for empirical analysis.
Keywords: Schooling choice, earnings equation, treatment effects, self-selection, ordered probit,
random coefficients, full information maximum likelihood . The relationship between schooling and earnings is one of the most frequently studied in
empirical economics. A large number of these studies build upon versions of the earnings
equation proposed by Mincer (1974). A key parameter in the Mincer earnings equation
is the coefficient associated with years of schooling. This coefficient is meant to capture
the differences is earnings caused by differences in schooling. However, to give a causal
interpretation of the parameters of the earnings equation, one must take into account that
the independent variable “years of schooling” is endogenous because it is the outcome of
a choice variable: level of schooling. | en_US |
