The Benefits to Taxpayers from Increases in Students - RAND ...

96 The Benefits to Taxpayers from Increases in Students’ Educational Attainment
Program Utilization and Benefits Model
We divide the expected value of benefits received from a social program into two parts:
(1) the probability of utilizing a program, i.e., receiving social support income, and
(2) the expected amount of the benefit, conditional on utilization of the program.
For any given program, whether or not a person benefits from it is a dichotomous
outcome and needs to be estimated separately from the benefit itself. Estimating the
benefit on the entire population would yield erroneous estimates, since a lot of nonparticipating
individuals would bias the picture. How the benefit level varies with personal
attributes can only be assessed by analyzing those who receive any benefit.
For each program, the first part of the model is the individual’s likelihood of program
utilization as a function of education level and other demographics. The second
part of the model is annual income from the program, conditional on positive program
income, again as a function of education level and other characteristics.
We estimate the model in two parts. The first part consists of a probit regression
in which the response variable equals 1 in the case of program utilization in 2002
and 0 otherwise. The second part of the estimation is an OLS regression in which the
response variable is the respective program benefit of (or tax paid by) the individual in
2002. As incomes and, consequently, program benefits are not distributed normally,
the second part of the model is typically run on transformed data (logarithmic).
The independent variables are as follows:
• a set of dummies indicating the level of educational attainment:
–– less than high school graduate
–– some college
–– bachelor’s degree or more
• age and age-squared
• interactions between educational attainment variables and age variables
• a set of race/ethnicity dummies for Asians, blacks, Hispanics, and Native
Americans
• a dummy for U.S.-born versus resident status.
Age is included as quadratic to allow for nonlinear effects of age, particularly as
relates to cumulative experience in the labor market. Further, age and education status
are interacted to allow for the slope on educational attainment to vary with age.
In all regressions, the intercept refers to the reference case of U.S.-born, white
individuals who graduated from high school.
We run separate models for men and women, consistent with human-capital
models of labor market outcomes. The fact that there are only small subsamples prevents
us from running models for groups based on race/ethnicity and place of birth.
Depending on the nature of the social program in question, we run separate models
for the elderly and non-elderly.