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

Analytic Approach 23
The differences between the two sets of results estimate the effects of increased educational
attainment on government revenues over an individual’s lifetime, holding his or
her characteristics constant.
We use a similar approach to estimate the effects of increased educational attainment
on the costs of subsidized housing. We use the model of housing subsidy utilization
to estimate the probability that an individual with given demographic characteristics
and education level would utilize assisted housing in each year of his or her life
from school-leaving age to age 79. Assuming that the unit housing cost per person is
constant across education levels and demographic groups, the expected housing subsidy
is equal to the likelihood of utilization, as predicted by the model, times the average
program cost per person. We then discount the estimates for each year of an individual’s
life to age 18, using appropriate survival rates. The result is an estimate of the
present value at age 18 of the assisted housing benefits that would be paid to an individual
from that demographic group between school-leaving and age 79, given his or
her education level. We then compare the results for an individual with a given level of
education and characteristics against the corresponding results for an individual with
the same characteristics but a higher level of education. The differences between the
two sets of results estimate the effects of increasing the individual’s level of education
on the assisted housing benefits paid an individual over his or her lifetime, holding his
or her characteristics constant.
For each of the other social support and insurance programs, we use the probit
model for that program to estimate the likelihood that an individual with given characteristics
and education level will participate in that program in each year of his or her
life from school-leaving age to age 79. We then use the model of the annual income
the individual will receive from that program if they participate in any given year. We
multiply the likelihood that the individual will participate in the program in each year
by the estimated benefits that the individual would receive in that year if he or she participated
to estimate the expected value of the program benefits paid to the individual
in each year. We discount the estimates for each year of an individual’s life to age 18,
using appropriate survival rates. The result is an estimate of the present value at age 18
of the benefits an individual from that demographic group will receive between school
leaving and age 79, given his or her education level. We then compare the results for an
individual with a given level of education and characteristics against the corresponding
results for an individual with the same characteristics but a higher level of education
to estimate the effects of educational attainment on the program’s costs over the individual’s
lifetime, holding his or her characteristics constant.
As noted previously, we model per-person correctional spending as the product
of per-person incarceration expenditure and the likelihood of individual incarceration,
assuming that the probability of incarceration equals the number of prisoners in each
population category divided by the sum of the general population and the number