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Anecdotal evidence points to the importance of school principals, but the limited existing research has neither provided consistent results nor indicated any set of essential characteristics of effective principals. This paper exploits extensive student-level panel data across six states to investigate both variations in principal performance and the relationship between effectiveness and key certification factors. While principal effectiveness varies widely across states, there is little indication that regulation of the background and training of principals yields consistently effective performance. Having prior teaching or management experience is not related to our estimates of principal value-added.

We examine the potential to expand and diversify the production of university STEM degrees by shifting the margin of initial enrollment between community colleges and 4-year universities. Our analysis is based on statewide administrative microdata from the Missouri Department of Higher Education and Workforce Development covering enrollees in all public postsecondary institutions statewide. We find that the potential for shifting the enrollment margin to expand degree production in STEM fields is modest, even at an upper bound, because most community college students are not academically prepared for bachelor's degree programs in STEM fields. We also find that shifting the enrollment margin is unlikely to improve racial/ethnic diversity among university STEM degree recipients. This is because community college students at the enrollment margin are less diverse than their peers who enter universities directly.

The recent turn toward core practices and practice-based teacher education has been accompanied by a growing literature on the definitions, pedagogies to teach, and assessments of core practices. Despite these developments, the field lacks core practices performance assessments designed to be used across course sections, courses, and subjects. This paper provides an existence proof of this type of assessment and investigates the affordances and constraints of the approach. The study describes three types of mixed-reality simulation-based performance tasks of three core practices. More than 400 novices in 64 teacher preparation programs in the United States reported that they were able to use the simulation environment and believed the tasks measure important teaching skills. Scores on the tasks were positively related to novices' prior academic and teacher education experiences. Implications for the formative use of such simulations are discussed.

Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new measure of student risk for use in education policies, which we call Predicted Academic Performance (PAP). PAP is a flexible, data-rich indicator that identifies students at risk of poor academic outcomes. It blends concepts from emerging "early warning" systems with principles of incentive design to balance the competing priorities of accurate risk measurement and suitability for policy use. PAP is more effective than common alternatives at identifying students who are at risk of poor academic outcomes and can be used to target resources toward these students--and students who belong to several other associated risk categories--more efficiently.

We estimate the education and earnings returns to enrolling in technical two-year degree programs at community colleges in Missouri. A unique feature of the Missouri context is the presence of a highly-regarded, nationally-ranked technical college: State Technical College of Missouri (State Tech). Compared to enrolling in a non-technical community college program, we find that enrolling in a technical program at State Tech greatly increases students' likelihoods of graduation and earnings. In contrast, there is no evidence that technical education programs at other Missouri community colleges increase graduation rates, and our estimates of the earnings impacts of these other programs are much smaller than for State Tech. Our findings exemplify the importance of institutional differences in driving the efficacy of technical education and suggest great potential for high-quality programs to improve student outcomes.

We develop a new framework for identifying at-risk students in public schools. Our framework has two fundamental advantages over "status quo" systems: (1) it is based on a clear definition of what it means for a student to be at risk and (2) it leverages states' rich administrative data systems to produce more informative risk measures. Our framework is more effective than common alternatives at identifying students who are at risk of low academic performance and we use policy simulations to show that it can be used to target resources toward these students more efficiently. It also offers several other benefits relative to "status quo" systems. We provide an alternative approach to risk measurement that states can use to inform funding, accountability, and other policies, rather than continuing to rely on broad categories tied to the nebulous concept of "disadvantage."

We use statewide administrative data from Missouri to document the prevalence of Industry Recognized Credential (IRC) programs in public high schools and understand the characteristics of students who complete IRCs. We show that 9 percent of Missouri students complete an IRC during their senior year of high school. IRC completers have lower achievement and are more likely to be disadvantaged along several measurable dimensions relative to their peers who complete analog college-ready programs, on average. Noting these average relationships, there is substantial heterogeneity among individual IRCs in terms of the types of students served: some IRCs attract students with high test scores who mostly go on to attend college, whereas others serve low-scoring students who mostly forego college. There is strong gender segregation across individual IRCs that aligns with gender segregation across occupations in the labor market.

There is empirical evidence of substantial heterogeneity in economic mobility across geographic areas and the efficacy of schools has been suggested as an explanatory factor. Using administrative microdata from seven states covering nearly 3 million students, we explore the potential role of schools in promoting economic mobility by estimating cross-district variation in "academic mobility"--a term we use to describe the extent to which students' ranks in the distribution of academic performance change during their schooling careers. We show that there exists considerable heterogeneity in academic mobility across school districts. However, after aggregating our district-level measures of academic mobility to the commuting-zone level and merging them with geographically matched external estimates of economic mobility, we find little scope for geographic differences in academic mobility to meaningfully account for differences in economic mobility.

Free and reduced-price meal eligibility (FRM) is commonly used in education research and policy applications as an indicator of student poverty. However, using multiple data sources external to the school system, we show that FRM status is a poor proxy for poverty, with eligibility rates far exceeding what would be expected based on stated income thresholds for program participation. This is true even without accounting for community eligibility for free meals, although community eligibility has exacerbated the problem in recent years. Over the course of showing the limitations of using FRM data to measure poverty, we provide promising validity evidence for a new, publicly-available measure of school poverty based on local-area family incomes.

The Individuals with Disabilities Education Act (IDEA) provides services to students who have disabilities. These IDEA-funded services are afforded to students between the ages of 3 and 21 who attend not only public schools (including charter schools), but also private schools. IDEA contains comprehensive guidelines on 3 processes which, by design, are meant to ensure that IDEA-funded services are granted without prejudice to any private school student who may by law be eligible to receive them. These processes IDEA refers to as "child find," "consultation," and "proportionate share." For a variety of reasons, the execution of these processes has been decidedly flawed. As a result, tens of thousands of private school students with disabilities have been denied the services to which IDEA, as a federal law, entitles them. Relying on raw data from certain public-school districts and state departments of education regarding their respective execution of the "child-find" process, the authors assess the extent to which, nationwide, private school students' (and their teachers') fair and full access to IDEA-funded services has been systemically denied. Based on this assessment, the authors offer recommendations on how, in the short-term, the current IDEA statute and regulations might be better enforced and IDEA's regulations might be improved. In view of IDEA's anticipated re-authorization, the authors also offer recommendations on how Congressionally approved statutory changes to the current law would ensure that, in the future, private school students will finally be able to freely and fully participate in IDEA.

The Community Eligibility Provision (CEP) is a policy change to the federally-administered National School Lunch Program that allows schools serving low-income populations to classify all students as eligible for free meals, regardless of individual circumstances. This has implications for the use of free and reduced-price meal (FRM) data to proxy for student disadvantage in education research and policy applications, which is a common practice. We document empirically how the CEP has affected the value of FRM eligibility as a proxy for student disadvantage. At the individual student level, we show that there is essentially no effect of the CEP. However, the CEP does meaningfully change the information conveyed by the share of FRM-eligible students in a school. It is this latter measure that is most relevant for policy uses of FRM data. [Portions of this paper were previously circulated under the title "Using Free Meal and Direct Certification Data to Proxy for Student Disadvantage in the Era of the Community Eligibility Provision" (ED595218). The authors have since split the original paper into two parts. This is the first part.]

We evaluate the feasibility of estimating test-score growth with a gap year in testing data, informing the scenario when state testing resumes after the 2020 COVID-19-induced test stoppage. Our research design is to simulate a gap year in testing using pre-COVID-19 data--when a true test gap did not occur--which facilitates comparisons of district- and school-level growth measures that are estimated with and without a gap year. We find that growth estimates based on the full data and gap-year data are generally similar, and our results highlight an advantage of using comprehensive growth models with rich controls for student and schooling circumstances. With the caveat that there is looming uncertainty about which students will be tested in public schools when testing resumes, and how they will be tested, our findings establish the potential for estimating useful growth measures with a gap year in testing.

We use rich administrative microdata from Missouri to examine the potential to expand and diversify the production of STEM [science, technology, engineering, and mathematics] degrees at universities by tapping into the population of community college students. We find that the scope for expansion is modest, even at an upper bound, because most community college students have academic qualifications that make them unlikely to succeed in a STEM field at a university. We also find there is almost no scope for community college students to improve the racial/ethnic diversity of four-year STEM degree recipients. We conclude that it will be challenging to expand and diversify STEM degree production at universities with interventions targeted toward community college students.

We study the effects of exposure to non-resident students on the outcomes of undergraduate in-state students during a period of high non-resident enrollment growth at the University of Missouri-Columbia. Our models leverage within-major, cross-time variation in nonresident exposure for identification. We find no evidence that increased exposure to domestic non-residents affects in-state student outcomes and our null results are precisely estimated. We find evidence of modest negative impacts on in-state students when their exposure to foreign students increases using our preferred specification. However, the identifying variation in exposure to foreign students in our data is limited and this result is not robust in all of our models.

Sixty-seven school finance reforms (SFRs) in 26 states have taken place since 1990; however, there is little empirical evidence on the heterogeneity of SFR effects. We provide a comprehensive description of how individual reforms affected resource allocation to low- and high-income districts within states, including both financial and non-financial outcomes. After summarizing the heterogeneity of individual SFR impacts, we then examine its correlates, identifying both policy and legislative/political factors. Taken together, this research aims to provide a rich description of variation in states' responses to SFRs, as well as explanation of this heterogeneity as it relates to contextual factors.

Free and reduced-price meal (FRM) data are used ubiquitously to proxy for student disadvantage in education research and policy applications. The Community Eligibility Provision (CEP)--a recently-implemented policy change to the federally-administered National School Lunch Program--allows schools serving low-income populations to identify all students as FRM-eligible regardless of individual circumstances. We study the CEP's effect on FRM eligibility as a proxy for student disadvantage, and relatedly, we examine the viability of direct certification (DC) status as an alternative disadvantage measure. Our findings on whether the CEP degrades the informational content of FRM data are mixed. At the individual level there is essentially no effect, but the CEP does meaningfully change the information conveyed by the FRM-eligible share of students in a school. Our comparison of FRM and DC data in the post-CEP era shows that these measures are similarly informative as proxies for disadvantage, despite the CEP-induced information loss in FRM data. Using both measures together can improve the identification of disadvantaged students, but only marginally.

We use statewide administrative data from Missouri to examine the explanatory power of high schools over student sorting to colleges and majors at 4-year public universities. We develop a "preparation and persistence index" (PPI) for each university-by-major cell in the Missouri system that captures dimensions of selectivity and rigor and allows for a detailed investigation of sorting. Our analysis shows that students' high schools predict the quality of the initial university, as measured by PPI, conditional on their own academic preparation, and that students from lower SES high schools systematically enroll at lower-PPI universities. However, high schools offer little explanatory power over major placements within universities.

We study the effects of access to high school math and science courses on postsecondary STEM enrollment and degree attainment using administrative microdata from Missouri. Our data panel includes over 140,000 students from 14 cohorts entering the 4-year public university system. The effects of high school course access are identified by exploiting plausibly exogenous variation in course offerings within high schools over time. We find that differential access to high school courses does not affect postsecondary STEM enrollment or degree attainment. Our null results are estimated precisely enough to rule out moderate impacts.

A vast research literature is devoted to analyzing causes of and potential remedies for early-career teacher attrition. However, much less attention has been paid to late-career attrition among experienced teachers, which is driven primarily by retirement plan incentives. Although there is some variation across states, it is generally the case that late-career teachers retire at much younger ages than their professional counterparts. Moreover, given the well-documented returns to teaching experience, late-career exits are on average more costly to students in K-12 schools than early-career exits. This study uses structural estimates from a dynamic retirement model to simulate the effect of targeted retention bonuses for senior teachers rated as effective or teaching in high-need fields. While the cost per incremental year of instruction is expensive in the short run, it declines over time. Moreover, because labor supply decisions are forward-looking, a temporary bonus has much smaller effects than a permanent one. These findings highlight the value of stability in policies aimed at extending teachers' careers. Overall our results suggest that carefully-targeted retention bonuses can be useful tool in raising the quality of the teaching workforce and closing achievement gaps.

We use statewide administrative data from Missouri to examine the role of high schools in explaining students' initial college and major placements at 4-year public universities. To facilitate our investigation of postsecondary sorting, we develop a "preparation and persistence index" (PPI) for each university-by-major cell in the Missouri system to measure the quality of that cell. The PPI depends on the pre-college academic qualifications of degree completers. Our analysis of high schools shows that the high school attended predicts the quality of the initial university, as measured by PPI, conditional on a student's own academic preparation. Consistent with previous research, we further show that students from lower-SES high schools systematically enroll at lower-quality universities relative to their similarly-qualified peers from higher-SES high schools. However, high schools offer little explanatory power over major placements within universities. Correspondingly, there are not meaningful differences in the quality of these placements by high-school SES. Supplementary tables are appended.

In 2012, five foundations launched the Credit When Its Due (CWID) initiative that was "designed to encourage partnerships of community colleges and universities to significantly expand programs that award associate degrees to transfer students when the student completes the requirements for the associate degree while pursuing a bachelor's degree" (Lumina Foundation, 2012, n.p.), also known as "reverse transfer." Initially, 12 states (Arkansas, Colorado, Florida, Hawaii, Maryland, Michigan, Minnesota, Missouri, New York, North Carolina, Ohio, and Oregon) were funded to develop and implement these reverse transfer programs and policies, and the Office of Community College Research and Leadership (OCCRL) at the University of Illinois at Urbana-Champaign was chosen as the research partner. In late 2013, three states (Georgia, Tennessee, and Texas) were added to bring the total number of states to 15. At least six additional states have legislation, pending legislation, or statewide initiatives related to reverse transfer. This thought paper describes changes that are occurring at the state, system, and institution levels with implementation of reverse transfer in the 12 original states. Using qualitative and quantitative data collected from the CWID Implementation Study, the authors describe efforts related to the optimization of reverse transfer in these 12 states. The authors define optimization as policy and program change at any level--state, system, or institution--that yields the largest number of students who are eligible for and able to benefit from reverse transfer. The initial results suggest that some states are piloting reverse transfer with a limited set of public community college and university partnerships, and others are striving for system-level reforms that eventually may impact all forms of transfer. Understanding what optimization means and how it works is possible because of this variation in implementation approaches among states, and this thought paper explores how states are implementing and optimizing reverse transfer.

Most public school teachers in the United States are enrolled in defined benefit (DB) pension plans. Using administrative micro data from four states, combined with national pension funding data, we show these plans have accumulated substantial unfunded liabilities -- effectively debt -- owing to previous plan operations. On average across 49 state plans, an amount that exceeds 10 percent of current teachers' earnings is being set aside to pay for previously-accrued pension liabilities. To the extent that the costs of the unfunded liabilities drag on teacher compensation, they may exacerbate problems of teacher recruitment and retention. We briefly discuss three policy changes that could end or reduce the accumulation of unfunded liabilities in educator pension plans: (1) transition teachers to defined-contribution retirement plans; (2) transition teachers to cash-balance retirement plans; and (3) tighten the link between funding and benefit formulas within the current defined-benefit structure.

Rising costs of public employee pension plans are a source of fiscal stress in many cities and states and have led to calls for reform. To assess the economic consequences of plan changes it is important to have reliable statistical models of employee retirement behavior. The authors estimate a structural model of teacher retirement using administrative panel data. A Stock-Wise option value model provides a good fit to the data and predicts well out-of-sample on the effects of pension enhancements during the 1990s. The structural model is used to simulate the effect of alternatives to the current defined benefit plan.

We use data from workers in the largest public-sector occupation in the United States -- teaching -- to examine the effect of pension enhancements on employee retention. Specifically, we study a 1999 enhancement to the benefit formula for public school teachers in St. Louis that resulted in an immediate and dramatic increase in their incentives to remain in covered employment. To identify the effect of the enhancement on teacher retention, we leverage the fact that the strength of the incentive increase varied across the workforce depending on how far teachers were from retirement eligibility when it was enacted. Although we document substantial differences across teachers in how their retention incentives were affected by the enhancement, our results indicate that these differences did not translate into meaningful changes in behavior. The following are appended: (1) Pension-Wealth Calculation Details; (2) Supplementary Tables; and (3) Using a Cost-Benefit Framework to Gain Insight about Novice Teachers.