Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking high school, college, and earnings registries spanning the state of Texas, we identify relative college value-added by comparing the outcomes of students who apply to and are admitted by the same set of institutions, as this approach strikingly balances observable student potential across college treatments and renders our extensive set of covariates irrelevant as controls. Methodologically, we develop a framework for identifying and interpreting value-added under varying assumptions about match effects and sorting gains. Empirically, we estimate a relatively tight, though non-degenerate, distribution of relative value-added across the wide diversity of Texas public universities. Selectivity poorly predicts value-added within student choice sets, with only a fleeting selectivity earnings premium fading to zero after a few years in the labor market. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Colleges that boost BA completion, especially in STEM majors, also tend to boost earnings. Finally, we probe the potential for (mis)match effects by allowing value-added schedules to vary by student characteristics. [Additional financial support was received from the Robert H. Topel Faculty Research Fund at the University of Chicago Booth School of Business.]