Breaking the link between poverty and low student achievement: An evaluation of Title I

This study provides an evaluation of the impact of Title I funding of compensatory education programs on school finance and student performance in New York City public schools during the 1993, 1997 and 2001 school years. Estimates based on a regression-discontinuity approach indicate that the program was unsuccessful in improving student outcomes in high-poverty schools in New York City during this period, and may in fact have had adverse effects during the earlier years in our sample. Less evidence of a negative effect is found for the 2001 school year. These findings are related to the way in which the federal funds were spent.     

Accounting for heterogeneous returns in sequential schooling decisions

This paper presents a method for estimating returns to multiple schooling levels taking into account that returns may be heterogeneous among agents and that educational decisions are made sequentially. A sequential decision model explicitly considers that the level of education is the result of previous schooling choices and so, the variation of supply-side instruments over time will emerge as a source of identification of the desired parameters. A test for heterogeneity in returns from sequential schooling decisions is developed and expressions for Marginal Treatment Effects are obtained in this context. Returns are estimated and tested from cross-sectional data from a Spanish household survey that contains rich family background information and useful instruments. This methodology is used to analyze possible effects of the 1970 reform of the Spanish education system.     

Diversity,Choice and the Quasi‐market: An Empirical Analysis of Secondary Education Policy in England*

This article investigates the extent to which exam performance at the end of compulsory education has been affected by three major education reforms: the introduction of a quasi‐market following the Education Reform Act (1988); the specialist schools initiative introduced in 1994; and the Excellence in Cities programme introduced in 1999. Using a panel of schools for all state‐funded secondary schools in England (1992–2006), we find that only about one‐third of the improvement in school exam scores is directly attributable to the combined effect of these three major education reforms. The distributional consequences of the policy, however, are estimated to have been favourable, with the greatest gains being achieved by schools with the highest proportion of pupils from poor families.     

Estimating the Impact of the Specialist Schools Programme on Secondary School Examination Results in England*

This paper investigates the impact of the specialist schools programme in England on examination performance at age 16. Two approaches are used. The first uses pupil‐level data from the 2003 National Pupil Database. The second uses panel data methods and is based on time‐series data for secondary schools during 1992–2003. The paper also investigates the distributional consequences of the specialist schools programme. Specialist schools perform marginally better than their non‐specialist counterparts (especially in science, business studies and technology) but by much less than is indicated by previous studies. The programme does not appear to have had adverse distributional consequences.     

An Analysis of the Value Added by Secondary Schools in England: Is the Value Added Indicator of Any Value?*

This paper argues that the value added score published for all publicly funded secondary schools in England is an unreliable indicator of school performance. A substantial proportion of the between‐school variation in the value added score is accounted for by factors outside the school's control. These factors include several pupil‐related variables such as the proportion of pupils on free school meals, the authorized absence rate of pupils and the proportion of pupils from ethnic minority backgrounds. The value added score is also related to several school characteristics such as the school's admission policy and its subject specialism. The main policy recommendation of this paper is that the value added score should not be used as a performance indicator, but should be used to gain a better understanding of why the value added score varies between schools.     

Charter school closure and student achievement: Evidence from Ohio

The closure of low-performing schools is an essential feature of the charter school model. Our regression discontinuity analysis uses an exogenous source of variation in school closure—an Ohio law that requires charter schools to close if they fail to meet a specific performance standard—to estimate the causal effect of closure on student achievement. The results indicate that closing low-performing charter schools eventually yields achievement gains of around 0.2–0.3 standard deviations in reading and math for students attending these schools at the time they were identified for closure. The study also employs mandatory closure as an instrument for estimating the impact of exiting low-quality charter schools, thus providing plausible lower-bound estimates of charter school effectiveness. These results complement the more common lottery-based estimates of charter school effects, which likely serve as upper-bound estimates due to their focus on oversubscribed schools often located in cities with high-performing charter sectors. We discuss the implications for research and policy.     

Extending the regression-discontinuity approach to multiple assignment variables

The recent scholarly attention to the regression-discontinuity design has focused exclusively on the application of a single assignment variable. In many settings, however, exogenously imposed cutoffs on several assignment variables define a set of different treatments. In this paper, we show how to generalize the standard regression-discontinuity approach to include multiple assignment variables simultaneously. We demonstrate that fitting this general, flexible regression-discontinuity model enables us to estimate several treatment effects of interest.     

The influence of school size,principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle schools

The aim of the paper is to identify which among the aspects that relate to the composition of the student body, school (district) size, management practices and the school principals' own characteristics are associated with the performance of Italian students at grade 8, measured through standardised test scores in reading and mathematics. The analysis makes use of a student-level efficiency model, and several school level variables are included as explanators for efficiency scores. The results show that, especially for reading, the most influential variables relate to the composition of the student body, while the students' performance in mathematics is partly correlated with the management practices adopted by the school principal/head teacher. Schools and schooling can only explain a minor part of the variance in achievement scores, however, and the characteristics of the students themselves play the most significant role.     

Private school vouchers and student achievement: A fixed effects quantile regression evaluation

Fundamental to the recent debate over school choice is the issue of whether voucher programs actually improve students' academic achievement. Using newly developed quantile regression approaches, this paper investigates the distribution of achievement gains in the first school voucher program implemented in the US. We find that while high-performing students selected for the Milwaukee Parental Choice program had a positive, convexly increasing gain in mathematics, low-performing students had a nearly linear loss. However, the program seems to prevent low-performing students from having an even bigger loss experienced by students in the public schools.     

The impact of the National School Lunch Program on child health: A nonparametric bounds analysis

Children in households reporting the receipt of free or reduced-price school meals through the National School Lunch Program (NSLP) are more likely to have negative health outcomes than observationally similar nonparticipants. Assessing causal effects of the program is made difficult, however, by missing counterfactuals and systematic underreporting of program participation. Combining survey data with auxiliary administrative information on the size of the NSLP caseload, we extend nonparametric partial identification methods that account for endogenous selection and nonrandom classification error in a single framework. Similar to a regression discontinuity design, we introduce a new way to conceptualize the monotone instrumental variable (MIV) assumption using eligibility criteria as monotone instruments. Under relatively weak assumptions, we find evidence that the receipt of free and reduced-price lunches improves the health outcomes of children.     

The role of aggregation in estimating the effects of private school competition on student achievement

This paper investigates possible reasons for the disparity in results in the private school competition literature. In particular, the focus is on the data set, the grade range, and level of aggregation of the competition variable, and on the choice of OLS or IV estimation strategies. The results show that the size and significance of the competition variable depends on each of these attributes, although the grade range of the competition variable has a slightly smaller impact than the others. Private school competition does not have a consistently positive, significant effect on student achievement.     

Quality competition with motivated providers and sluggish demand

We study incentives for quality provision in markets where providers are motivated (semi-altruistic); prices are regulated and firms are funded by a combination of block grants and unit prices; competition is based on quality, and demand adjusts sluggishly. Health or education are sectors in which the mentioned features are the rule. We show that the presence of motivated providers makes dynamic competition tougher, resulting in higher steady-state levels of quality in the closed-loop solution than in the benchmark open-loop solution, if the price is sufficiently high. However, this result is reversed if the price is sufficiently low (and below unit costs). Sufficiently low prices also imply that a reduction in demand sluggishness will lead to lower steady-state quality. Prices below unit costs will nevertheless be welfare optimal if the providers are sufficiently motivated.     

Quadratic Engel Curves with Measurement Error: Evidence from a Budget Survey*

This paper examines the importance of accounting for measurement error in total expenditure in the estimation of Engel curves, based on the 1994 Ethiopian Urban Household Survey. Using Lewbel's [Review of Economics and Statistics (1996 ), Vol. 78, pp. 718–725] estimator for demand models with correlated measurement errors in the dependent and independent variables, we find robust evidence of a quadratic relationship between food share and total expenditure in the capital city, and significant biases in various estimators that do not correct for correlated measurement errors.     

Political Influence and the Banking Sector: Evidence from Korea*

This paper uses panel data to compare the performance of Korean banks with and without effective government control of the appointment of chief operating officers. A privatization programme succeeded in spreading ownership of banks widely among the public, but government retention of an ownership stake in an institution meant de facto control by government. Despite charging lower loan rates, banks controlled by government experience higher bad loans ratios. This is in line with expectations of regulatory forbearance and government protection for recipients of political loans. Banks controlled by government are less efficient than privately controlled banks and bad loan variables are higher at banks with lower efficiency scores.     

学生成绩管理系统的设计与实现

学生成绩管理可以提高学校的信息化管理水平,促进学生成绩管理更科学,节约管理人员时间。文章对学生成绩管理系统进行了需求分析,并设计与实现了一个学生成绩管理系统,以提高教学管理效率。     

Teacher qualifications and student achievement in urban elementary schools

Teacher quality is a key element of student academic success, but few specific teacher characteristics influence classroom outcomes. This research examines whether teacher licensure test scores and other teacher attributes affect elementary student achievement. The results are based on longitudinal student-level data from Los Angeles. California requires three types of teacher licensure tests as part of the teacher certification process; a general knowledge test, a subject area test (single subject for secondary teachers and multiple subject for elementary teachers), and a reading pedagogy test for elementary school teachers. The student achievement analysis uses a value-added approach that adjusts for both student and teacher fixed effects. The results show large differences in teacher quality across the school district, but measured teacher characteristics explain little of the difference. Teacher licensure test scores are unrelated to teacher success in the classroom. Similarly, student achievement is unaffected by whether classroom teachers have advanced degrees. Student achievement increases with teacher experience, but the linkage is weak and largely reflects poor outcomes for teachers during their first year or two in the classroom.     

Closing schools in a shrinking district: Do student outcomes depend on which schools are closed?

In the last decade, many cities around the country have needed to close schools due to declining enrollments and low achievement. School closings raise concerns about the possible negative impacts on student achievement, neighborhoods, families, and teaching staff. This study examines an anonymous urban district that, faced with declining enrollment, chose to make student achievement a major criterion in determining which schools would be closed. The district targeted low-performing schools in its closure plan, and sought to move their students to higher-performing schools. We estimate the impact of school closures on student test scores and attendance rates by comparing the growth of these measures among students differentially affected by the closures. We use residential assignment to school as an instrument to address non-random sorting of students into new schools. We also statistically control for the contemporaneous effects of other reforms within the district. Results show that students displaced by school closures can experience adverse effects on test scores and attendance, but these effects can be minimized when students move to schools that are higher-performing (in value-added terms). Moreover, the negative effect on attendance disappears after the first year in the new school. Meanwhile, we find no adverse effects on students in the schools that are receiving the transferring students.     

Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances

This study develops a methodology of inference for a widely used Cliff–Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while allowing for unknown heteroskedasticity in the innovations. We first generalize the GMM estimator suggested in  and  for the spatial autoregressive parameter in the disturbance process. We also define IV estimators for the regression parameters of the model and give results concerning the joint asymptotic distribution of those estimators and the GMM estimator. Much of the theory is kept general to cover a wide range of settings.     

Nonparametric estimation and inference on conditional quantile processes

This paper presents estimation methods and asymptotic theory for the analysis of a nonparametrically specified conditional quantile process. Two estimators based on local linear regressions are proposed. The first estimator applies simple inequality constraints while the second uses rearrangement to maintain quantile monotonicity. The bandwidth parameter is allowed to vary across quantiles to adapt to data sparsity. For inference, the paper first establishes a uniform Bahadur representation and then shows that the two estimators converge weakly to the same limiting Gaussian process. As an empirical illustration, the paper considers a dataset from Project STAR and delivers two new findings.     

A central limit theorem for endogenous locations and complex spatial interactions

We provide a new central limit theorem (CLT) for spatial processes under weak conditions that are plausible for many economic applications in which location is endogenous. In particular, our CLT is designed for problems that have some, but not necessarily all, of the following features: (i) Agents choose the locations of observations to maximize profits, welfare, or some other objective. (ii) The objects that are chosen (e.g., stores or brands) interact with one another. For example, they can be substitutes or complements. (iii) Interaction can be complex. In particular, interaction between i and j need not depend only on the distance between the locations of i and j, but can also depend on distance to or location of other observations k, or possibly on the number of other such observations.