Jack Mountjoy
Assistant Professor of Economics
and Robert H. Topel Faculty Scholar
University of Chicago Booth School of Business
Primary Research Fields
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Research
- "Community Colleges and Upward Mobility" (R&R, American Economic Review)
Abstract: Two-year community colleges enroll nearly half of all first-time undergraduates, but to ambiguous effect: low persistence rates and the potential for diverting students from 4-year institutions cast ambiguity over 2-year colleges’ contributions to upward mobility. Developing a new multivariate instrumental variables approach applied to linked administrative education and earnings records, I disentangle the net impacts of 2-year college access into two competing causal margins: significant value-added for 2-year entrants who otherwise would not have attended college, but negative impacts on students diverted from 4-year entry. 2-year access particularly boosts the upward mobility of disadvantaged students, who experience less 4-year diversion.
with Marianne Bertrand and Magne Mogstad (Accepted, Journal of Labor Economics)
Abstract: We study the impacts of a major reform to vocational secondary education that aimed to move beyond the tradeoff between providing occupational skills and closing off academic opportunities. Norway’s Reform 94 integrated more general education into the vocational track, offered vocational students a pathway to college, and increased access to apprenticeships. We identify reform impacts through a difference-in-discontinuity research design applied to linked population registries. The reform substantially increased initial vocational enrollment, but with divergent consequences by gender. Overall, the reform succeeded at improving social mobility, particularly for disadvantaged men, but it somewhat exacerbated the gender gap in adult earnings.
with Brent Hickman (new draft coming soon)
Abstract: Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We estimate relative value-added of individual colleges to disentangle causal college impacts from student sorting in producing these outcome disparities. Linking administrative registries of high school records, college applications, admissions decisions, enrollment spells, degree completions, and quarterly earnings spanning the Texas population, we identify 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 student ability measures across college treatments and renders our extensive set of student covariates irrelevant as controls. We estimate a relatively tight, though non-degenerate, distribution of value-added across the wide diversity of Texas public universities. Selectivity is a poor indicator of value-added, with a negative selectivity effect on STEM major completion and only a fleeting selectivity earnings premium that fades out completely after a few years in the labor market. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity, but residual differences in value-added remain that are not neatly summarized by differences in observable quality measures. Examining potential mechanisms, colleges that ultimately boost earnings also tend to boost persistence, BA completion, and STEM degrees along the way. Finally, we probe the potential for (mis)match effects by allowing value-added to vary flexibly by student characteristics, including race, gender, family income, and pre-college measures of cognitive and non-cognitive skills. At first glance, Black students appear to face small negative returns to attending more selective colleges, but this pattern of modest "mismatch" is driven by the availability of two large historically Black universities with above-average value-added. Across the non-HBCUs, Black students face similar returns to selectivity, and indistinguishable value-added schedules more generally, compared to their peers from other backgrounds.
with Ivan Canay and Magne Mogstad (submitted) (comment and reply)
Abstract: The decisions of judges, lenders, journal editors, and other gatekeepers often lead to disparities in outcomes across affected groups. An important question is whether, and to what extent, these group-level disparities are driven by relevant differences in underlying individual characteristics, or by biased decision makers. Becker (1957) proposed an outcome test for bias leading to a large body of related empirical work, with recent innovations in settings where decision makers are exogenously assigned to cases and vary progressively in their decision tendencies. We carefully examine what can be learned about bias in decision making in such settings. Our results call into question recent conclusions about racial bias among bail judges, and, more broadly, yield four lessons for researchers considering the use of outcome tests of bias. First, the so-called generalized Roy model, which is a workhorse of applied economics, does not deliver a logically valid outcome test without further restrictions, since it does not require an unbiased decision maker to equalize marginal outcomes across groups. Second, the more restrictive "extended" Roy model, which isolates potential outcomes as the sole admissible source of analyst-unobserved variation driving decisions, delivers both a logically valid and econometrically viable outcome test. Third, this extended Roy model places strong restrictions on behavior and the data generating process, so detailed institutional knowledge is essential for justifying such restrictions. Finally, because the extended Roy model imposes restrictions beyond those required to identify marginal outcomes across groups, it has testable implications that may help assess its suitability across empirical settings.