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This paper simulates a system of socioeconomic status (SES)-based affirmative action in college admissions and examines the extent to which it can produce racial diversity in selective colleges. Using simulation models, we investigate the potential relative effects of race- and/or SES-based affirmative action policies, alongside targeted, race-based recruitment, on the racial and socioeconomic distribution of students in colleges. These simulations suggest three important patterns: (1) neither SES-based affirmative action nor race recruiting policies on their own can reproduce levels of racial diversity achieved by race-based affirmative action; however, SES-based affirmative action in combination with targeted recruitment, although likely expensive, shows the potential to yield racial diversity levels comparable to race-based affirmative action; (b) the use of affirmative action policies by some colleges reduces the diversity of similar-quality colleges that do not have such policies; (c) overall, the combination of SES-based affirmative action and race recruiting results in slightly fewer Black and Hispanic students that are academically overmatched than under race-based affirmative action, but the schools that use the combination policy also see an overall reduction in the academic achievement of the students they enroll.

The creation of racially diverse colleges at all levels of selectivity has proven to be no small task, even with the legal use of race-conscious affirmative action. As evidenced in the postsecondary destinations of the high school class of 2004, very selective schools (those with Barron's Selectivity rankings of 1, 2 or 3) have many more White, and many fewer Black and Hispanic, students than the population of 18-year-olds overall. However, the trend of decreasing diversity with increasing selectivity is not strictly monotonic: the most selective schools (Barron's 1s) are slightly more diverse than the schools just below them in the selectivity rankings. In these Barron's 1 schools there is suggestive evidence of successful (race-based) affirmative action policies. Given the apparently modest results of explicitly race-based affirmative action, the construction of race-neutral policies that replicate, or even improve upon, these levels of diversity presents a daunting challenge. The goal of this study is to inform the current affirmative action debate with evidence from sophisticated simulation models in which the authors vary how colleges weigh race and class in the admission decision process. This model is able to take into account many of the complexities and interrelated dynamics of the college admissions process, such as uncertainty over college or student quality, learning over time, and strategic application submission. Results from the simulations suggest at least three important patterns: (1) unless SES-based affirmative action policies use a very large bump, these policies are unlikely to result in the same racial composition in colleges as under current race-based affirmative action policies; (2) socioeconomic affirmative action results in a moderate-to-substantial reduction in the average resources of students enrolled at elite colleges, and are thus effective at increasing socioeconomic diversity; and (3) information plays a large, and perhaps previously unrecognized, role in the sorting of minority students into colleges; the application behavior of students responded much more effectively to affirmative action policies when those policies were made explicit to students. Three figures are appended.

There is currently a great deal of interest in the potential of reductions in or elimination of the cost of college attendance for students (here referred to as college subsidies) to increase equitable access to higher education. A number of Democratic presidential candidates have advanced proposals for such programs. However, because colleges and students differ in ways that are likely related to how subsidies might affect enrollment and because there is a large amount of interdependence between colleges and students over time (i.e. "spillover"), we cannot directly extrapolate from the relatively small number of moderately large-scale subsidy programs that have been rigorously evaluated to predict the effects of programs with alternative specifications (e.g. eligibility requirements or scale) on enrollment patterns. Therefore, we turn to a computational modeling approach ("Agent-based modeling") that allows us to explicitly simulate individual college and student decisions over time. Our model is grounded in a strong body of evidence about how students and colleges make application, admissions, and enrollment decisions given different salient attributes (e.g. family resources) and imperfect information. We use the model to explore the potential impact of different prospective college subsidy programs. We find that when subsidies have substantial effects, these tend to have direct effects (i.e. an increase in eligible students' enrollment in subsidized colleges) as well as indirect effects (i.e. a decrease in eligible students' enrollment in unsubsidized colleges). Program impacts are strongest when the programs themselves are limited in scope: smaller than full-scale (i.e. national-level programs), with eligibility restricted to higher-achieving students, and not all colleges subsidized.