The Unintended Consequences of Encouraging Work: Tax Incidence and the EITC

The EITC is designed to encourage work. But EITC-induced increases in labor supply may drive wages down, shifting the intended transfer toward employers and hurting non- EITC low-skill workers. I exploit variation across family types and skill levels to identify the eect of a large EITC expansion in the mid 1990s. Ceteris paribus, low-skill single mothers keep only $0.70 of every dollar they receive. Employers of low-skill labor capture$0.72, $0.30 from single mothers plus$0.43 from ineligible workers whose after-tax incomes fall when the EITC is expanded. The net transfer to low-skill workers is less than $0.28 per dollar spent.

Does Competition Among Public Schools Benefit Students and Taxpayers? A Comment on Hoxby (2000)

In an influential paper, Hoxby (2000) studies the relationship between the degree of so-called "Tiebout choice" among local school districts within a metropolitan area and average test scores. She argues that choice is endogenous to school quality, and instruments with the number of larger and smaller streams. She finds a large positive effect of choice on test scores, which she interprets as evidence that school choice induces greater school productivity. This paper revisits Hoxby's analysis. I document several important errors in Hoxby's data and code. I also demonstrate that the estimated choice effect is extremely sensitive to the way that "larger streams" are coded. When Hoxby's hand count of larger streams is replaced with any of several alternative, easily replicable measures, there is no significant difference between IV and OLS, each of which indicates a choice effect near zero. There is thus little evidence that schools respond to Tiebout competition by raising productivity. A data appendix for this paper is available online

Racial Segregation and the Black-White Test Score Gap

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 fully segregated to a completely 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 but that school segregation has no independent effect (though we cannot reject equality of the two effects). We find similar results using Census-based data on schooling outcomes for youth in different cities. 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.

Permanent Income and the Black-White Test Score Gap

Analysts often examine the black-white test score gap conditional on family income. Typically only a current income measure is available. We argue that the gap conditional on permanent income is of greater interest, and we describe a method for identifying this gap using an auxiliary data set to estimate the relationship between current and permanent income. Current income explains only about half as much of the black-white test score gap as does permanent income, and the remaining gap in math achievement among families with the same permanent income is only 0.2 to 0.3 standard deviations in two commonly used data sets. When we add permanent income to the controls used by Fryer and Levitt (2006), the unexplained gap in 3rd grade shrinks below 0.15 standard deviations, less than half of what is found with their controls.

Racial Segregation and the Black-White Test Score Gap

Segregation, desegregation, SAT scores, cities, urban economics

Mismatch in Law School

An important criticism of affirmative action policies in admissions is that they may hurt minority students who are thereby induced to attend selective schools. We use two comparisons to identify so-called “mismatch” effects in law schools, with consistent results. Black students attain better employment outcomes than do whites with similar credentials. Any mismatch effects on graduation and bar exam passage rates are confined to the bottom quintile of the entering credentials distribution, where selection bias is an important, potentially confounding factor. Elite law schools’ use of affirmative action thus does not appear to generate mismatch effects.

Constrained After College: Student Loans and Early Career Occupational Choices

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 future 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.

The Augmented Synthetic Control Method

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The "synthetic control" is a weighted average of control units that balances the treated unit's pre-treatment outcomes as closely as possible. A critical feature of the original proposal is to use SCM only when the fit on pre-treatment outcomes is excellent. We propose Augmented SCM as an extension of SCM to settings where such pre-treatment fit is infeasible. Analogous to bias correction for inexact matching, Augmented SCM uses an outcome model to estimate the bias due to imperfect pre-treatment fit and then de-biases the original SCM estimate. Our main proposal, which uses ridge regression as the outcome model, directly controls pre-treatment fit while minimizing extrapolation from the convex hull. This estimator can also be expressed as a solution to a modified synthetic controls problem that allows negative weights on some donor units. We bound the estimation error of this approach under different data generating processes, including a linear factor model, and show how regularization helps to avoid over-fitting to noise. We demonstrate gains from Augmented SCM with extensive simulation studies and apply this framework to estimate the impact of the 2012 Kansas tax cuts on economic growth. We implement the proposed method in the new augsynth R package

Race, Income and College in 25 Years: The Continuing Legacy of Segregation and Discrimination

The rate at which racial gaps in pre-collegiate academic achievement can plausibly be expected to erode is a matter of great interest and much uncertainty. In her opinion in Grutter v. Bollinger, Supreme Court Justice O’Connor took a firm stand: “We expect that 25 years from now, the use of racial preferences will no longer be necessary . . .” We evaluate the plausibility of Justice O’Connor’s forecast, by projecting the racial composition and SAT distribution of the elite college applicant pool 25 years from now. We focus on two important margins: First, changes in the black-white relative distribution of income, and second, narrowing of the test score gap between black and white students within family income groups. Other things equal, progress on each margin can be expected to reduce the racial gap in qualifications among students pursuing admission to the most selective colleges. Under plausible assumptions, however, projected economic progress will not yield nearly as much racial diversity as is currently obtained with race-sensitive admissions. Simulations that assume additional increases in black students’ test scores, beyond those deriving from changes in family income, yield more optimistic estimates. In this scenario, race-blind rules approach the black representation among admitted students seen today at moderately selective institutions, but continue to fall short at the most selective schools. Maintaining a critical mass of African American students at the most selective institutions would require policies at the elementary and secondary levels or changes in parenting practices that deliver unprecedented success in narrowing the test score gap in the next quarter century.