Showing papers by "Joshua D. Angrist published in 2012"

Estimation of Limited Dependent Variable Models With Dummy Endogenous Regressors

Abstract: Applied economists have long struggled with the question of how to accommodate binary endogenous regressors in models with binary and nonnegative outcomes. I argue here that much of the difculty with limited dependent variables comes from a focus on structural parameters, such as index coefcients, instead of causal effects. Once the object of estimation is taken to be the causal effect of treatment, several simple strategies are available. These include conventional two-stage least squares, multiplicative models for conditional means, linear approximation of nonlinear causal models, models for distribution effects, and quantile regression with an endogenous binary regressor. The estimation strategies discussed in the article are illustrated by using multiple births to estimate the effect of childbearing on employment status and hours of work.

The Elite Illusion: Achievement Effects at Boston and New York Exam Schools

Abstract: Parents gauge school quality in part by the level of student achievement and a school's racial mix. The importance of school characteristics in the housing market can be seen in the jump in house prices at school district boundaries where peer characteristics change. The question of whether schools with more attractive peers are really better in a value-added sense remains open, however. This paper uses a fuzzy regression-discontinuity design to evaluate the causal effects of peer characteristics. Our design exploits admissions cutoffs for Boston and New York City's heavily over-subscribed exam schools. Successful applicants near admissions cutoffs for the least selective of these schools move from schools with scores near the bottom of the state SAT score distribution to a school with scores near the median. Successful applicants near admissions cutoffs for the most selective of these schools move from above-average schools to schools with students drawn from the extreme upper tail. Exam school students can also expect to study with fewer nonwhite classmates than unsuccessful applicants. Our estimates suggest that the marked changes in peer characteristics at exam school admissions cutoffs have little causal effect on test scores or college quality.

Explaining Charter School Effectiveness.

Abstract: Lottery estimates suggest Massachusetts’ urban charter schools boost achievement well beyond that of traditional urban public schools students, while nonurban charters reduce achievement from a higher baseline. The fact that urban charters are most effective for poor nonwhites and low-baseline achievers contributes to, but does not fully explain, these differences. We therefore link school-level charter impacts to school inputs and practices. The relative efficacy of urban lottery sample charters is accounted for by these schools’ embrace of the No Excuses approach to urban education. In our Massachusetts sample, Non-No-Excuses urban charters are no more effective than nonurban charters. (JEL H75, I21, I28) A growing body of evidence suggests that urban charter schools have the potential to generate impressive achievement gains, especially for minority students living in high-poverty areas. In a series of studies using admissions lotteries to identify causal effects, we looked at the impact of charter attendance in Boston and at a Knowledge is Power Program (KIPP) school in Lynn, Massachusetts (Abdulkadiro ˘ g

Who benefits from kipp

Abstract: The nation’s largest charter management organization is the Knowledge is Power Program (KIPP). KIPP schools are emblematic of the No Excuses approach to public education, a highly standardized and widely replicated charter model that features a long school day, an extended school year, selective teacher hiring, strict behavior norms, and emphasizes traditional reading and math skills. No Excuses charter schools are sometimes said to target relatively motivated high achievers at the expense of students who are more difficult to teach, including limited English proficiency (LEP) and special education (SPED) students, as well as students with low baseline achievement levels. We use applicant lotteries to evaluate the impact of KIPP Academy Lynn, a KIPP school in Lynn, Massachusetts that typifies the KIPP approach. Our analysis focuses on special needs students that may be underserved. The results show average achievement gains of 0.36 standard deviations in math and 0.12 standard deviations in reading for each year spent at KIPP Lynn, with the largest gains coming from the LEP, SPED, and low-achievement groups. Average reading gains are driven almost entirely by SPED and LEP students, whose reading scores rise by roughly 0.35 standard deviations for each year spent at KIPP Lynn. C � 2012 by the Association for Public Policy Analysis and Management.

Schooling and labor market consequences of the 1970 state abortion reforms

Abstract: This study uses the 1970 state abortion reforms to estimate the effect of teen and out-of-wedlock childbearing on the schooling and labor market outcomes of mothers observed in 1980 and 1990 [U.S.] Census microdata. Reduced-form estimates suggest that state abortion reforms had a negative impact on teen marriage teen fertility and teen out-of-wedlock childbearing. The teen marriage effects are largest and most precisely estimated for white women while the teen fertility and out-of-wedlock childbearing effects are largest and most precisely estimated for black women. (EXCERPT)

Wanna Get Away? RD Identification Away from the Cutoff

Abstract: In the canonical regression discontinuity (RD) design for applicants who face an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The impact of treatment on inframarginal applicants is also of interest, but identification of such effects requires stronger assumptions than are required for identification at the cutoff. This paper discusses RD identification away from the cutoff. Our identification strategy exploits the availability of dependent variable predictors other than the running variable. Conditional on these predictors, the running variable is assumed to be ignorable. This identification strategy is illustrated with data on applicants to Boston exam schools. Functional-form-based extrapolation generates unsatisfying results in this context, either noisy or not very robust. By contrast, identification based on RD-specific conditional independence assumptions produces reasonably precise and surprisingly robust estimates of the effects of exam school attendance on inframarginal applicants. These estimates suggest that the causal effects of exam school attendance for 9th grade applicants with running variable values well away from admissions cutoffs differ little from those for applicants with values that put them on the margin of acceptance. An extension to fuzzy designs is shown to identify causal effects for compliers away from the cutoff.

Explaining Charter School Effectiveness

Abstract: Estimates using admissions lotteries suggest that urban charter schools boost student achievement, while charter schools in other settings do not. Using the largest available sample of lotteried applicants to charter schools, we explore student-level and school-level explanations for this difference in Massachusetts. In an econometric framework that isolates sources of charter effect heterogeneity, we show that urban charter schools boost achievement well beyond that of urban public school students, while non-urban charters reduce achievement from a higher baseline. Student demographics explain some of these gains since urban charters are most effective for non-whites and low-baseline achievers. At the same time, non-urban charter schools are uniformly ineffective. Our estimates also reveal important school-level heterogeneity within the urban charter sample. A non-lottery analysis suggests that urban charters with binding, well-documented admissions lotteries generate larger score gains than under-subscribed urban charter schools with poor lottery records. Finally, we link charter impacts to school characteristics such as peer composition, length of school day, and school philosophy. The relative effectiveness of urban lottery-sample charters is accounted for by these schools' embrace of the No Excuses approach to urban education.

The Elite Illusion: Achievement Effects at Boston and New York Exam Schools

Abstract: Talented students compete fiercely for seats at Boston and New York exam schools. These schools are characterized by high levels of peer achievement and a demanding curriculum tailored to each district's highest achievers. While exam school students do very well in school, the question of whether an exam school education adds value relative to a regular public education remains open. We estimate the causal effect of exam school attendance using a regression-discontinuity design, reporting both parametric and non- parametric estimates. The outcomes studied here include scores on state standardized achievement tests, PSAT and SAT participation and scores, and AP scores. Our estimates show little effect of exam school offers on most students' achievement. We use two-stage least squares to convert reduced form estimates of the effects of exam school offers into estimates of peer and tracking effects, arguing that these appear to be unimportant in this context. Finally, we explore the external validity of RD estimates, arguing that as best we can tell, there is little effect of an exam school education on achievement even for the highest-ability marginal applicants and for applicants to the right of admissions cutoffs. On the other hand, a Boston exam school education seems to have a modest effect on high school English scores for minority applicants. A small group of 9th grade applicants also appears to do better on SAT Reasoning. These localized gains notwithstanding, the intense competition for exam school seats does not appear to be justified by improved learning for a broad set of students.

Explaining Charter School Effectiveness

Abstract: Estimates using admissions lotteries suggest that urban charter schools boost student achievement, while charter schools in other settings do not. Using the largest available sample of lotteried applicants to charter schools, we explore student-level and school-level explanations for this difference in Massachusetts. In an econometric framework that isolates sources of charter effect heterogeneity, we show that urban charter schools boost achievement well beyond that of urban public school students, while non-urban charters reduce achievement from a higher baseline. Student demographics explain some of these gains since urban charters are most effective for non-whites and low-baseline achievers. At the same time, non-urban charter schools are uniformly ineffective. Our estimates also reveal important school-level heterogeneity within the urban charter sample. A non-lottery analysis suggests that urban charters with binding, well-documented admissions lotteries generate larger score gains than under-subscribed urban charter schools with poor lottery records. Finally, we link charter impacts to school characteristics such as peer composition, length of school day, and school philosophy. The relative effectiveness of urban lottery-sample charters is accounted for by these schools' embrace of the No Excuses approach to urban education.

Wanna Get Away? RD Identification Away from the Cutoff

Abstract: In the canonical regression discontinuity (RD) design for applicants who face an award or admissions cutoff, causal effects are nonparametrically identified for those near the cutoff. The impact of treatment on inframarginal applicants is also of interest, but identification of such effects requires stronger assumptions than are required for identification at the cutoff. This paper discusses RD identification away from the cutoff. Our identification strategy exploits the availability of dependent variable predictors other than the running variable. Conditional on these predictors, the running variable is assumed to be ignorable. This identification strategy is illustrated with data on applicants to Boston exam schools. Functional-form-based extrapolation generates unsatisfying results in this context, either noisy or not very robust. By contrast, identification based on RD-specific conditional independence assumptions produces reasonably precise and surprisingly robust estimates of the effects of exam school attendance on inframarginal applicants. These estimates suggest that the causal effects of exam school attendance for 9th grade applicants with running variable values well away from admissions cutoffs differ little from those for applicants with values that put them on the margin of acceptance. An extension to fuzzy designs is shown to identify causal effects for compliers away from the cutoff.