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.