Jack Mountjoy
Assistant Professor of Economics and Robert H. Topel Faculty Scholar
University of Chicago Booth School of Business
Primary Research Fields
Curriculum Vitae
Contact
Assistant Professor of Economics and Robert H. Topel Faculty Scholar
University of Chicago Booth School of Business
Primary Research Fields
- Labor Economics
- Applied Econometrics
- Economics of Education
Curriculum Vitae
Contact
PublicationsAmerican Economic Review, 112(8), August 2022Abstract: Two-year community colleges enroll nearly half of all first-time undergraduates in the United States, 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. This paper develops a new instrumental variables approach to identifying causal effects along multiple treatment margins, and applies it to linked education and earnings registries to 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 immediate 4-year entry.
Working Paperswith Ivan Canay and Magne Mogstad Revised and resubmitted, Review of Economic StudiesComment and replyAbstract: The decisions of judges, lenders, journal editors, and other gatekeepers often lead to significant disparities 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 (1957,1993) proposed an outcome test of bias based on differences in post-decision outcomes across groups, inspiring a large and growing empirical literature. We carefully examine what researchers can learn about bias in decision making from such outcome tests. We show that models of decision making underpinning outcome tests can be usefully recast as Roy models, since potential outcomes enter directly into the decision maker’s choice equation. Different members of the Roy model family, however, are distinguished by the tightness of the link between potential outcomes and decisions, and we show that these distinctions have important implications for defining bias, deriving logically valid outcome tests of such bias, and identifying the marginal outcomes that the test requires.
with Brent Hickman Abstract: 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 administrative high school records, college applications, admissions decisions, enrollment spells, degree completions, and quarterly earnings spanning the Texas population, 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, generalizing the constant treatment effects assumption typically employed in the value-added literature. 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: a fleeting selectivity earnings premium fades to zero after a few years in the labor market, and more selective colleges tend to have lower value-added on STEM degree completion. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Educational impacts predict labor market impacts: colleges with larger earnings value-added also tend to be colleges that boost persistence, BA completion, and STEM degrees along the way. Finally, we probe the potential for (mis)match effects by allowing each college's relative value-added to vary flexibly by student characteristics. At first glance, Black students appear to face small negative returns to choosing more selective colleges, but this pattern of modest "mismatch" is entirely driven by the availability of two large historically Black universities with low selectivity but 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.
Work in Progress
- Improving Educational Pathways to Social Mobility: Evidence from Norway's Reform 94 (preprint) (appendix)
Working Paperswith Ivan Canay and Magne Mogstad Revised and resubmitted, Review of Economic StudiesComment and replyAbstract: The decisions of judges, lenders, journal editors, and other gatekeepers often lead to significant disparities 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 (1957,1993) proposed an outcome test of bias based on differences in post-decision outcomes across groups, inspiring a large and growing empirical literature. We carefully examine what researchers can learn about bias in decision making from such outcome tests. We show that models of decision making underpinning outcome tests can be usefully recast as Roy models, since potential outcomes enter directly into the decision maker’s choice equation. Different members of the Roy model family, however, are distinguished by the tightness of the link between potential outcomes and decisions, and we show that these distinctions have important implications for defining bias, deriving logically valid outcome tests of such bias, and identifying the marginal outcomes that the test requires.
with Brent Hickman Abstract: 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 administrative high school records, college applications, admissions decisions, enrollment spells, degree completions, and quarterly earnings spanning the Texas population, 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, generalizing the constant treatment effects assumption typically employed in the value-added literature. 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: a fleeting selectivity earnings premium fades to zero after a few years in the labor market, and more selective colleges tend to have lower value-added on STEM degree completion. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Educational impacts predict labor market impacts: colleges with larger earnings value-added also tend to be colleges that boost persistence, BA completion, and STEM degrees along the way. Finally, we probe the potential for (mis)match effects by allowing each college's relative value-added to vary flexibly by student characteristics. At first glance, Black students appear to face small negative returns to choosing more selective colleges, but this pattern of modest "mismatch" is entirely driven by the availability of two large historically Black universities with low selectivity but 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.
Work in Progress
- Pay vs. Productivity
- Long-Run Impacts of Charter School Attendance