Diane Whitmore Schanzenbach

Bio: Diane Whitmore Schanzenbach is an academic researcher from Northwestern University. The author has contributed to research in topics: Food Stamp Program & Class size. The author has an hindex of 35, co-authored 111 publications receiving 6508 citations. Previous affiliations of Diane Whitmore Schanzenbach include University of Illinois at Urbana–Champaign & National Bureau of Economic Research.

How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star

Abstract: In Project STAR, 11,571 students in Tennessee and their teachers were randomly assigned to classrooms within their schools from kindergarten to third grade. This article evaluates the long-term impacts of STAR by linking the experimental data to administrative records. We first demonstrate that kindergarten test scores are highly correlated with outcomes such as earnings at age 27, college attendance, home ownership, and retirement savings. We then document four sets of experimental impacts. First, students in small classes are significantly more likely to attend college and exhibit improvements on other outcomes. Class size does not have a significant effect on earnings at age 27, but this effect is imprecisely estimated. Second, students who had a more experienced teacher in kindergarten have higher earnings. Third, an analysis of variance reveals significant classroom effects on earnings. Students who were randomly assigned to higher quality classrooms in grades K–3—as measured by classmates' end-of-class test scores—have higher earnings, college attendance rates, and other outcomes. Finally, the effects of class quality fade out on test scores in later grades, but gains in noncognitive measures persist.

How Does Your Kindergarten Classroom Affect Your Earnings? Evidence from Project Star

Abstract: In Project STAR, 11,571 students in Tennessee and their teachers were randomly assigned to classrooms within their schools from kindergarten to third grade This article evaluates the long-term impacts of STAR by linking the experimental data to administrative records We first demonstrate that kindergarten test scores are highly correlated with outcomes such as earnings at age 27, college attendance, home ownership, and retirement savings We then document four sets of experimental impacts First, students in small classes are significantly more likely to attend college and exhibit improvements on other outcomes Class size does not have a significant effect on earnings at age 27, but this effect is imprecisely estimated Second, students who had a more experienced teacher in kindergarten have higher earnings Third, an analysis of variance reveals significant classroom effects on earnings Students who were randomly assigned to higher quality classrooms in grades K–3—as measured by classmates' end-of-class test scores—have higher earnings, college attendance rates, and other outcomes Finally, the effects of class quality fade out on test scores in later grades, but gains in noncognitive measures persist

Long Run Impacts of Childhood Access to the Safety Net

Abstract: A growing economics literature establishes a causal link between in utero shocks and health and human capital in adulthood. Most studies rely on extreme negative shocks such as famine and pandemics. We are the first to examine the impact of a positive and policy-driven change in economic resources available in utero and during childhood. In particular, we focus on the introduction of a key element of the U.S. safety net, the Food Stamp Program, which was rolled out across counties in the U.S. between 1961 and 1975. We use the Panel Study of Income Dynamics to assemble unique data linking family background and county of residence in early childhood to adult health and economic outcomes. The identification comes from variation across counties and over birth cohorts in availability of the food stamp program. Our findings indicate that the food stamp program has effects decades after initial exposure. Specifically, access to food stamps in childhood leads to a significant reduction in the incidence of "metabolic syndrome" (obesity, high blood pressure, and diabetes) and, for women, an increase in economic self-sufficiency. Overall, our results suggest substantial internal and external benefits of the safety net that have not previously been quantified.

Inside the War on Poverty: The Impact of Food Stamps on Birth Outcomes

Abstract: This paper evaluates the health impact of a signature initiative of the War on Poverty: the roll out of the modern Food Stamp Program (FSP) during the 1960s and early 1970s Using variation in the month the FSP began operating in each US county, we find that pregnancies exposed to the FSP three months prior to birth yielded deliveries with increased birth weight, with the largest gains at the lowest birth weights These impacts are evident with difference-in-difference models and event study analyses Estimated impacts are robust to inclusion of county fixed effects, time fixed effects, measures of other federal transfer spending, state by year fixed effects, and county-specific linear time trends We also find that the FSP rollout leads to small, but statistically insignificant, improvements in neonatal infant mortality We conclude that the sizeable increase in income from Food Stamp benefits improved birth outcomes for both whites and African Americans, with larger impacts for births to African American mothers

Left Behind By Design: Proficiency Counts and Test-Based Accountability

Abstract: We show that within the Chicago Public Schools, both the introduction of NCLB in 2002 and the introduction of similar district-level reforms in 1996 generated noteworthy increases in reading and math scores among students in the middle of the achievement distribution but not among the least academically advantaged students. The stringency of proficiency requirements varied among the programs implemented for different grades in different years, and our results suggest that changes in proficiency requirements induce teachers to shift more attention to students who are near the current proficiency standard.

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

Abstract: We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

Robust Inference with Multi-way Clustering

Abstract: In this article we propose a variance estimator for the OLS estimator as well as for nonlinear estimators such as logit, probit, and GMM. This variance estimator enables cluster-robust inference when there is two-way or multiway clustering that is nonnested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g., Liang and Zeger 1986; Arellano 1987) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer cluster-robust standard errors when there is one-way clustering. The method is demonstrated by a Monte Carlo analysis for a two-way random effects model; a Monte Carlo analysis of a placebo law that extends the state–year effects example of Bertrand, Duflo, and Mullainathan (2004) to two dimensions; and by application to studies in the empirical literature where two-way clustering is present.

Unobservable Selection and Coefficient Stability: Theory and Evidence

Abstract: A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on observables is informative about selection on unobservables. Although this link is known in theory in existing literature, very few empirical articles approach this formally. I develop an extension of the theory that connects bias explicitly to coefficient stability. I show that it is necessary to take into account coefficient and R-squared movements. I develop a formal bounding argument. I show two validation exercises and discuss application to the economics literature. Supplementary materials for this article are available online.

Complement and microglia mediate early synapse loss in Alzheimer mouse models

Abstract: Synapse loss in Alzheimer’s disease (AD) correlates with cognitive decline. Involvement of microglia and complement in AD has been attributed to neuroinflammation, prominent late in disease. Here we show in mouse models that complement and microglia mediate synaptic loss early in AD. C1q, the initiating protein of the classical complement cascade, is increased and associated with synapses before overt plaque deposition. Inhibition of C1q, C3, or the microglial complement receptor CR3 reduces the number of phagocytic microglia, as well as the extent of early synapse loss. C1q is necessary for the toxic effects of soluble β-amyloid (Aβ) oligomers on synapses and hippocampal long-term potentiation. Finally, microglia in adult brains engulf synaptic material in a CR3-dependent process when exposed to soluble Aβ oligomers. Together, these findings suggest that the complement-dependent pathway and microglia that prune excess synapses in development are inappropriately activated and mediate synapse loss in AD.

Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States*

Abstract: We use administrative records on the incomes of more than 40 million children and their parents to describe three features of intergenerational mobility in the United States. First, we characterize the joint distribution of parent and child income at the national level. The conditional expectation of child income given parent income is linear in percentile ranks. On average, a 10 percentile increase in parent income is associated with a 3.4 percentile increase in a child’s income. Second, intergenerational mobility varies substantially across areas within the U.S. For example, the probability that a child reaches the top quintile of the national income distribution starting from a family in the bottom quintile is 4.4% in Charlotte but 12.9% in San Jose. Third, we explore the factors correlated with upward mobility. High mobility areas have (1) less residential segregation, (2) less income inequality, (3) better primary schools, (4) greater social capital, and (5) greater family stability. While our descriptive analysis does not identify the causal mechanisms that determine upward mobility, the publicly available statistics on intergenerational mobility developed here can facilitate research on such mechanisms. The opinions expressed in this paper are those of the authors alone and do not necessarily reect