Areas of Expertise
- Tax Policy
- Economic Policy
- Labor and Employment
- Program Evaluation
- Public Finance
- Quantitative Methods
Jesse Rothstein is a public and labor economist. His research focuses on education and tax policy, and particularly on the way that public institutions ameliorate or reinforce the effects of children’s families on their academic and economic outcomes. Within education, he has conducted studies on teacher evaluation; on the value of school infrastructure spending; on affirmative action in college and graduate school admissions; and on the causes and consequences of racial segregation. He has also written about the effects of unemployment insurance on job search and labor force participation; the role of structural factors in impeding recovery from the Great Recession; and the incidence of the Earned Income Tax Credit.
Rothstein's work has been published in the American Economic Review, the Quarterly Journal of Economics, the Journal of Public Economics, the Chicago Law Review, and the American Economic Journal: Economic Policy, among other outlets. He has a Ph.D. in economics from the University of California, Berkeley, and an MPP from the Goldman School, and he is a Research Associate of the National Bureau of Economic Research. In 2009-2010 he served as a Senior Economist for the Council of Economic Advisers and then as Chief Economist at the U.S. Department of Labor.
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Four years after the beginning of the Great Recession, the labor market remains historically weak. Many observers have concluded that "structural" impediments to recovery bear some of the blame. The author reviews such structural explanations, but after analyzing U.S. data on unemployment and productivity, he finds there is little evidence supporting these hypotheses. He finds that the bulk of the evidence is more consistent with the hypothesis that continued poor performance is primarily attributable to shortfalls in the aggregate demand for labor.
More than 2 years after the official end of the Great Recession, the labor market remains historically weak. One candidate explanation is supply-side effects driven by dramatic expansions of unemployment insurance (UI) benefit durations, to as long as 99 weeks. This paper investigates the effect of these extensions on job search and reemployment. I use the longitudinal structure of the Current Population Survey to construct unemployment exit hazards that vary across states, over time, and between individuals with differing unemployment durations. I then use these hazards to explore a variety of comparisons intended to distinguish the effects of UI extensions from other determinants of employment outcomes. The various specifications yield quite similar results. UI extensions had significant but small negative effects on the probability that the eligible unemployed would exit unemployment. These effects are concentrated among the long-term unemployed. The estimates imply that UI extensions raised the unemployment rate in early 2011 by only about 0.1 to 0.5 percentage point, much less than implied by previous analyses, with at least half of this effect attributable to reduced labor force exit among the unemployed rather than to the changes in reemployment rates that are of greater policy concern.
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In the early 2000s, a highly selective university introduced a “no-loans” policy under which the loan component of financial aid awards was replaced with grants. We use this natural experiment to identify the causal effect of student debt on employment outcomes. In the standard life-cycle model, young people make optimal educational investment decisions if they are able to finance these investments by borrowing against future earnings; the presence of debt has only income effects on investment decisions. We find that debt causes graduates to choose substantially higher-salary jobs and reduces the probability that students choose low-paid “public interest” jobs. We also find some evidence that debt affects students' academic decisions during college. Our estimates suggest that recent college graduates are not life-cycle agents. Two potential explanations are that young workers are credit constrained or that they are averse to holding debt. We find suggestive evidence that debt reduces students' donations to the institution in the years after they graduate and increases the likelihood that a graduate will default on a pledge made during her senior year; we argue this result is more likely consistent with credit constraints than with debt aversion.
Despite extensive public infrastructure spending, surprisingly little is known
about its economic return. In this paper, we estimate the value of school facility
investments using housing markets: standard models of local public goods imply
that school districts should spend up to the point where marginal increases would
have zero effect on local housing prices. Our research design isolates exogenous
variation in investments by comparing school districts where referenda on bond
issues targeted to fund capital expenditures passed and failed by narrow margins. We extend this traditional regression discontinuity approach to identify the dynamic treatment effects of bond authorization on local housing prices, student
achievement, and district composition. Our results indicate that California school
districts underinvest in school facilities: passing a referendum causes immediate, sizable increases in home prices, implying a willingness to pay on the part of marginal homebuyers of $1.50 or more for each $1 of capital spending. These
effects do not appear to be driven by changes in the income or racial composition of
homeowners, and the impact on test scores appears to explain only a small portion
of the total housing price effect.
The EITC is intended to encourage work. But EITC-induced increases in labor supply may drive wages down. I simulate the economic incidence of the EITC. In each scenario that I consider, a large portion of low-income single mothers’ EITC payments is captured by employers through reduced wages. Workers who are EITC ineligible also see wage declines. By contrast, a traditional Negative Income Tax (NIT) discourages work, and so induces large transfers from employers to their workers. With my preferred parameters, $1 in EITC spending increases after-tax incomes by $0.73, while $1 spent on the NIT yields $1.39.
Growing concerns over the inadequate achievement of U.S. students have
led to proposals to reward good teachers and penalize (or ﬁre) bad ones. The
leading method for assessing teacher quality is “value added” modeling (VAM),
which decomposes students’ test scores into components attributed to student
heterogeneity and to teacher quality. Implicit in the VAM approach are strong
assumptions about the nature of the educational production function and the
assignment of students to classrooms. In this paper, I develop falsiﬁcation tests
for three widely used VAM speciﬁcations, based on the idea that future teachers
cannot inﬂuence students’ past achievement. In data from North Carolina, each
of the VAMs’ exclusion restrictions is dramatically violated. In particular, these
models indicate large “effects” of ﬁfth grade teachers on fourth grade test score
gains. I also ﬁnd that conventional measures of individual teachers’ value added
fade out very quickly and are at best weakly related to long-run effects. I discuss
implications for the use of VAMs as personnel tools.
Nonrandom assignment of students to teachers can bias value-added estimates of teachers’ causal effects. Rothstein (2008, 2010) shows that typical value-added models indicate large counterfactual effects of ﬁfthgrade teachers on students’ fourth-grade learning, indicating that classroom assignments are far from random.This article quantiﬁes the resulting biases in estimates of ﬁfth-grade teachers’ causal effects from several valueadded models, under varying assumptions about the assignment process. If assignments are assumed to depend only on observables, the most commonly used speciﬁcations are subject to important bias, but other feasible speciﬁcations are nearly free of bias. I also consider the case in which assignments depend on unobserved variables. I use the across-classroom variance of observables to calibrate several models of the sorting process. Results indicate that even the best feasible value-added models may be substantially biased, with the magnitude of the bias depending on the amount of information available for use in classroom assignments.
Data from college admissions tests can provide a valuable measure of student achievement, but the non-representativeness of test-takers is an important concern. We examine selectivity bias in both state-level and school-level SAT and ACT averages. The degree of selectivity may differ importantly across and within schools, and across and within states. To identify within-state selectivity, we use a control function approach that conditions on scores from a representative test. Estimates indicate strong selectivity of test-takers in “ACT states,” where most college-bound students take the ACT, and much less selectivity in SAT states. To identify within- and between-school selectivity, we take advantage of a policy reform in Illinois that made taking the ACT a graduation requirement. Estimates based on this policy change indicate substantial positive selection into test participation both across and within schools. Despite this, school-level averages of observed scores are extremely highly correlated with average latent scores, as across-school variation in sample selectivity is small relative to the underlying signal. As a result, in most contexts the use of observed school mean test scores in place of latent means understates the degree of between-school variation in achievement but is otherwise unlikely to lead to misleading conclusions.
The Supreme Court has held repeatedly that race-based preferences in public university admissions are constitutional. But debates over the wisdom of affirmative action continue. Opponents of these policies argue that preferences are detrimental to minority students -- that by placing these students in environments that are too competitive, affirmative action hurts their academic and career outcomes.
This article examines the so-called "mismatch" hypothesis in the context of law school admissions. We discuss the existing scholarship on mismatch, identifying methodological limitations of earlier attempts to measure the effects of affirmative action. Using a simpler, more robust analytical strategy, we find that the data are inconsistent with large mismatch effects, particularly with respect to employment outcomes. While moderate mismatch effects are possible, they are concentrated among the students with the weakest entering academic credentials.
To put our estimates in context, we simulate admissions under race-blind rules. Eliminating affirmative action would dramatically reduce the number of black law students, particularly at the most selective schools. Many potentially successful black law students would be excluded, far more than the number who would be induced to pass the bar exam by the elimination of mismatch effects. Accordingly, we find that eliminating affirmative action would dramatically reduce the production of black lawyers.
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Schelling (“Dynamic Models of Segregation,” Journal of Mathematical Sociology 1 (1971), 143–186) showed that extreme segregation can arise from social interactions in white preferences: once the minority share in a neighborhood exceeds a “tipping point,” all the whites leave. We use regression discontinuity methods and Census tract data from 1970 through 2000 to test for discontinuities in the dynamics of neighborhood racial composition. We find strong evidence that white population flows exhibit tipping-like behavior in most cities, with a distribution of tipping points ranging from 5% to 20% minority share. Tipping is prevalent both in the suburbs and near existing minority enclaves. In contrast to white population flows, there is little evidence of nonlinearities in rents or housing prices around the tipping point. Tipping points are higher in cities where whites have more tolerant racial attitudes.
Racial segregation is often blamed for some of the achievement gap between blacks and whites. We study the effects of school and neighborhood segregation on the relative SAT scores of black students across different metropolitan areas, using large microdata samples for the 1998–2001 test cohorts. Our models include detailed controls for the family background of individual test-takers, school-level controls for selective participation in the test, and city-level controls for racial composition, income, and region. We find robust evidence that the black–white test score gap is higher in more segregated cities. Holding constant family background and other factors, a shift from a highly segregated city to a nearly integrated city closes about one-quarter of the raw black–white gap in SAT scores. Specifications that distinguish between school and neighborhood segregation suggest that neighborhood segregation has a consistently negative impact while school segregation has no independent effect, though we cannot reject equality of the two effects. Additional tests indicate that much of the effect of neighborhood segregation operates through neighbors' incomes, not through race per se. Data on enrollment in honors courses suggest that within-school segregation increases when schools are more highly integrated, potentially offsetting the benefits of school desegregation and accounting for our findings.
Good Principals or Good Peers: Parental Valuation of School Characteristics, Tiebout Equilibrium, an
School choice policies may, by aligning administrators’ incentives with parental demand, yield improved efﬁciency in educational production (Milton Friedman, 1962; John E. Chubb and Terry M. Moe, 1990). But Eric A. Hanushek (1981) cautions: “If the efﬁciency of our school systems is due to poor incentives for teachers and administrators coupled with poor decision-making by consumers, it would be unwise to expect much from programs that seek to strengthen ‘market forces’ in the selection of schools” (p. 35, emphasis added). Poor decision-making is not required; parents may rationally choose schools with “pleasant surroundings, athletic facilities, cultural advantages” (ibid., p. 34) over those that most efﬁciently pursue academic performance; they may prefer poorly run schools with good peer groups over those that are more effective but enroll worse students (J. Douglas Willms and Frank H. Echols, 1992, 1993); or they may simply be unable to identify effective schools (Thomas J. Kane and Douglas O. Staiger, 2002). Any factor that leads parents to choose any but the most effective available schools will tend to dilute the incentives for efﬁcient management that choice might otherwise create.
This study examines the distribution of student outcomes across schools within metropolitan housing markets for evidence on parental demand. Economists have long noted that parents’ choices among residential locations are potentially informative about how more complete choice systems may operate (Charles M. Tiebout, 1956; Melvin V. Borland and Roy M. Howsen, 1992; Caroline M. Hoxby, 2000; Rothstein, 2005). I ask whether school effectiveness plays a sufﬁciently important role in these decisions to create meaningful incentives for more productive school management.
In Grutter v. Bollinger, Justice O’Connor conjectured that in 25 years affirmative action in college admissions will be unnecessary. We project the test score distribution of black and white college applicants 25 years from now, focusing on the role of black–white family income gaps. Economic progress alone is unlikely to narrow the achievement gap enough in 25 years to produce today’s racial diversity levels with race-blind admissions. A return to the rapid black–white test score convergence of the 1980s could plausibly cause black representation to approach current levels at moderately selective schools, but not at the most selective schools.
In her opinion in Grutter v. Bollinger, Justice Sandra Day O’Connor concluded that affirmative action in college admissions is justifiable, but not in perpetuity: “We expect that 25 years from now, the use of racial preferences will no longer be necessary to further the interest [in student body diversity] approved today.”
The rate at which racial gaps in precollegiate academic achievement can plausibly be expected to erode is a matter of considerable uncertainty. In this essay, we attempt to evaluate the plausibility of Justice O’Connor’s conjecture by projecting the racial composition of the 2025 elite college applicant pool. Our projections extrapolate past trends on two important margins: Gaps between the economic resources of black and white students’ families, and narrowing of test score gaps between black and white students with similar family incomes. Just as the last decades have seen considerable narrowing of gaps on each margin, further progress can be expected over the next quarter century.
Our central question is whether this progress will plausibly be fast enough to validate Justice O’Connor’s prediction. We are well aware of the hazards inherent in our exercise: No such distant projections can be definitive. Nevertheless, by relying on reasonable historical assumptions that are arguably optimistic, we develop a baseline case for assessing the likelihood of O’Connor’s forecast.
We conclude that under reasonable assumptions, African American students will continue to be substantially underrepresented among the most qualified college applicants for the foreseeable future. The magnitude of the underrepresentation is likely to shrink—in our most optimistic simulation, somewhat over half of the gap that would be opened by the elimination of race preferences will be closed by the projected improvement in black achievement.
Still, it seems unlikely that today’s level of racial diversity will be achievable without some form of continuing affirmative action. If the Supreme Court follows through with O’Connor’s stated intention to ban affirmative action in 25 years, and if colleges do not adjust in other ways (such as reducing the importance of numerical qualifications to admissions), we project substantial declines in the representation of African Americans among admitted students at selective institutions.
Our analysis proceeds from the assumption that the most likely future course will resemble past trends. Substantial changes in educational policy, in school effectiveness, and in income inequality would all have important effects on black test score distributions and on the admissions landscape.
The methods used in most SAT validity studies cannot be justified by any sample selection assumptions and are uninformative about the source of the SAT's predictive power. A new omitted variables estimator is proposed; plausibly consistent estimates of the SAT's contribution to predictions of University of California freshman grade point averages are about 20% smaller than the usual methods imply. Moreover, much of the SAT's predictive power is found to derive from its correlation with high school demographic characteristics: The orthogonal portion of SAT scores is notably less predictive of future performance than is the unadjusted score.
Articles and Op-Eds
The New York Times, June 13, 2014
Dr. Jesse Rothstein
Date: May 30, 2012 Duration: 83 minutes
Larry Summers, Harvard, Robert M. Stern, Goldman School, AnnaLee Saxenian, UC Berkeley School of Information, Jesse Rothstein, Goldman School
Event: 2012 Wildavsky Forum
Date: April 13, 2012 Duration: 107 minutes
Jesse Rothstein, Edward H. Haertel, Audrey Amrein-Beardsley, Linda Darling-Hammond, Bethany Little
Event: AERA Hill Briefing
Date: September 14, 2011 Duration: 116 minutes