and zero otherwise; α
1996
equals one if the student is expected to graduate in 1996 or later and zero otherwise; and so forth, for each year from 1995 through 2001. Defined
in this way, the coefficients on the year dummies represent the average change in the dependent variable conditional on the covariates X
ijt
in the comparison cities from year t-1 to year t. The coefficient on the interaction between each α
t
and the D.C. dummy variable represents the change in the dependent variable from year t-1 to year
t in D.C. relative to the comparison cities. For example, in a model of applications to
DCTAG-eligible colleges, if DCTAG had a positive impact on the likelihood that a student applied to an eligible college, we would expect to see this reflected in posi-
tive, significant coefficients on α
2000
DC andor α
2001
DC that is, in positive, sig- nificant values of θ
2000
and θ
2001
. These two coefficients represent the change in the probability that a D.C. student applied to an eligible college between 1999 and 2000
and between 2000 and 2001, over and above any change in the probabilities for stu- dents in the comparison cities. The sum of the two coefficients θ
2000
plus θ
2001
rep- resents the total change in the probability of a D.C. high school graduate applying to
an eligible college between 1999 and 2001.
B. IPEDS Dataset
To examine college enrollments of students from D.C. and surrounding states, we use data from the Integrated Postsecondary Education Data System IPEDS, a dataset
maintained by the National Center for Education Statistics of the U.S. Department of Education. The IPEDS contains data on institutions that grant baccalaureate or higher
degrees, institutions that award two-year degrees, and less-than-two-year institutions. The IPEDS database consists of institution-level data collected through a set of annual
surveys that together provide information on a range of items. In our analysis, we use institution-level IPEDS data for two- and four-year institutions from 1996, 1998,
2000, and 2002 on fall enrollments of freshmen by state of residence and in- and out- of-state tuition rates. We augment the IPEDS data with measures of college selectiv-
ity; as described above, institutions are defined as “top-tier” based on their U.S. News and World Report college and university rankings for 1998.
6
Like our analysis of the SAT data, our analysis of the IPEDS data employs a dif- ference-in-differences approach in which we examine changes in enrollment patterns
among recent D.C. high school graduates following the introduction of the DCTAG program relative to the changes observed for a suitably-defined comparison group. For
our SAT analysis, the comparison group consists of high school graduates residing in large, heavily African-American cities in nearby states. Because the IPEDS database
identifies the number of college freshmen enrolled at reporting institutions by state but not by city of residence, our comparison group for the IPEDS analysis consists
of recent high school graduates from the nearby states of Maryland, Virginia, Connecticut, Delaware, New Jersey, North Carolina, and Pennsylvania. Appendix
Table A2 contains descriptive information regarding the schools contained in the IPEDS database.
Abraham and Clark
585
6. Analyses of the IPEDS data using the alternative measure of selectivity based on average SAT scores described above produce qualitatively similar results and therefore are not reported.
Unfortunately, since the IPEDS does not contain information by state of residence on either the number of upperclassmen or the number of students who graduate, we
are not able to examine DCTAG’s effects on retention or graduation rates, but only on the likelihood that students enroll as college freshmen. It would be of interest to know
how the program affects students’ decisions to remain in college and their success in completing college, and it may be possible to address these questions in future
research using different data sources.
IV. The Effects of DCTAG on College Application and Enrollment Decisions
