Education Level

We study the effect of preferences for boys on the performance in mathematics of girls, using evidence from two different data sources. In our first set of results, we identify families with a preference for boys by using fertility stopping rules in a large population of households whose children attend public schools in Florida. Girls growing up in a boy-biased family score on average 3 percentage points lower on math exams when compared to girls raised in other types of families. In our second set of results we find similar strong effects when we study the correlations between girls’ performance in mathematics and maternal gender role attitudes, using evidence from the National Longitudinal Survey of Youth. We conclude that socialization at home can explain a non-trivial part of the observed gender disparities in mathematics performance and document that maternal gender attitudes correlate with those of their children.

Citation: Gaia Dossi, David Figlio, Paola Giuliano, Paola Sapienza (2019). Born in the Family: Preferences for Boys and the Gender Gap in Math . CALDER Working Paper No. 216-0219-1

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.

WP 214-0119-1 was originally released in January 2019. An updated version was released in April 2019.

Citation: Cory Koedel, Eric Parsons (2019). Using Free Meal and Direct Certification Data to Proxy for Student Disadvantage in the Era of the Community Eligibility Provision. CALDER Working Paper No. 214-0119-1

Novice teachers’ professional contexts may have important implications for their effectiveness, development, and retention. However, descriptions of these contexts suffer from data limitations, resulting in unidimensional or vague characterizations. Using 10 years of administrative data from the Los Angeles Unified School District, we describe patterns of new teacher sorting using 27 context measures organized along three distinct dimensions - intensity of instructional responsibilities, homophily, and colleague qualifications – and use school-level survey data to measure a fourth dimension (professional culture). Relative to more experienced teachers, novice teachers have placements that are more challenging along the first three dimensions, and composite measures are differentially predictive of teachers’ outcomes. This suggests that policymakers should consider placements to better retain and develop novice teachers.

Citation: Paul Bruno, Sarah Rabovsky, Katharine Strunk (2019). Taking their First Steps: The Distribution of New Teachers into School and Classroom Contexts and Implications for Teacher Effectiveness and Growth. CALDER Working Paper No. 212-0119-1

In many school districts the policies that regulate personnel are governed by collective bargaining agreements (CBAs) negotiated between teachers’ unions and school boards. While there is significant policy attention and, in some cases, legislative action that has affected the scope of these agreements, there is relatively little research that assesses how CBAs vary over time, or whether they change in response to states’ legislative reforms. In this paper we compare CBAs in three states at two points in time: before and after substantial reforms in Michigan and Washington impacting collective bargaining and in California where there were no major statutory changes affecting CBAs. We find that few district characteristics predict changes in CBA restrictiveness over time, other than institutional spillovers from local bargaining structures. However, we observe that reforms to the scope of bargaining in Michigan and Washington drastically reduced the restrictiveness of Michigan and Washington CBAs relative to California.

Citation: Katharine Strunk , Joshua Cowen, Dan Goldhaber , Bradley D. Marianno, Tara Kilbride, Roddy Theobald (2018). Collective Bargaining and State-Level Reforms: Assessing Changes to the Restrictiveness of Collective Bargaining Agreements across Three States. CALDER Working Paper No. 210-1218-1

We use a novel database of the preservice apprenticeships (“student teaching placements”) of teachers in Washington State to investigate the relationship between mentor effectiveness (as measured by value added) and the future effectiveness of their mentees. We find a strong, positive relationship between the effectiveness of a teacher’s mentor and their own effectiveness in math and a more modest relationship in English Language Arts. The relationship in math is strongest early in a teacher’s career, decays significantly over time, and would be positive and statistically significant even in the presence of nonrandom sorting on unobservables of the same magnitude as the sorting on observables. Put together, this suggests that at least some of this relationship reflects a causal relationship between mentor effectiveness and the future effectiveness of their mentees in math.

Citation: Dan Goldhaber, John Krieg, Roddy Theobald (2018). Effective Like Me? Does Having a More Productive Mentor Improve the Productivity of Mentees? . CALDER Working Paper No. 208-1118-1

We use comprehensive data on student teaching placements from 14 teacher education programs (TEPs) in Washington State to explore the sorting of teacher candidates to the teachers who supervise their student teaching (“cooperating teachers”) and the schools in which student teaching occurs. We find that, all else equal, teachers with more experience, higher degree levels, and higher value added in math are more likely to serve as cooperating teachers, as are schools with lower levels of historical teacher turnover but with more open positions the following year. We also find that teacher candidates are more likely to be placed with cooperating teachers of the same gender and race/ethnicity, and are more likely to work with cooperating teachers and in schools with administrators who graduated from the candidate’s TEP.

Citation: John Krieg , Dan Goldhaber, Roddy Theobald (2018). Teacher Candidate Apprenticeships: Assessing the Who and Where of Student Teaching. CALDER Working Paper No. 206-1118-1

Student teaching has long been considered the most important component of an effective teacher education program. Recently, new research is finding links between these experiences and teacher candidates’ future effectiveness, yet relatively little is known about the student teacher placement process and, in particular, the processes that lead to the matching of teacher candidates to the in-service teachers who supervise their student teaching (“cooperating teachers”). In this study, we examine the match process as well as the factors that influence these placement decisions. We also explore how, if at all, practices vary across teacher education programs (TEPs), districts, and schools. We find that, in broad terms, the process for matching student teachers to mentor teachers is similar across educational institutions, although TEPs and school systems sometimes face competing priorities when placing student teachers in classrooms. We also identify a problem of information asymmetry in the placement process, which leaves TEPs with questions about how cooperating teachers are selected and districts and schools with limited information with which to make thoughtful and intentional matches between candidates and cooperating teachers. Finally, we document the important role of social networks in placements and how they can advantage some TEPs, districts, and schools in this process.

Citation: Elise St. John, Dan Goldhaber, John Krieg, Roddy Theobald (2018). How the Match Gets Made: Exploring Student Teacher Placements Across Teacher Education Programs, Districts, and Schools. CALDER Working Paper No. 204-1018-1

We study the relative performance of two policy relevant value-added models – a one-step fixed effect model and a two-step aggregated residuals model – using a simulated dataset well grounded in the value-added literature. A key feature of our data generating process is that student achievement depends on a continuous measure of economic disadvantage. This is a realistic condition that has implications for model performance because researchers typically have access to only a noisy, binary measure of disadvantage. We find that one- and two-step value-added models perform similarly across a wide range of student and teacher sorting conditions, with the two-step model modestly outperforming the one-step model in conditions that best match observed sorting in real data. A reason for the generally superior performance of the two-step model is that it better handles the use of an error-prone, dichotomous proxy for student disadvantage.

WP 179 was revised in September 2018. It was originally released in June 2017

Citation: Eric Parsons, Cory Koedel, Li Tan (2018). Accounting for Student Disadvantage in Value-Added Models (Update). CALDER Working Paper No. 179

As states attempt to staff public school classrooms with qualified teachers, primary attention has focused on educator preparation and early career retention. Far less research has examined the staffing consequences of turnover induced by teacher pension plans. This paper makes use of a unique longitudinal data file with performance measures for all public school teachers in Tennessee. Descriptive analysis finds that higher quality teachers are less likely to retire for a given age and experience. To better understand the effects of pension plan incentives on workforce quality, we estimate a structural retirement model that explicitly allows for different work-retirement preferences for high and low quality teachers. We find that high quality teachers have a lower disutility for teaching as compared to retirement. Given that it costs less to keep high as compared to low quality teachers on the job, we use the structural estimates to simulate the effect of retention bonuses targeted to the former. One year retention bonuses produce an additional year of high quality teaching at a cost of roughly $40,000.

Citation: Shawn Ni, Michael Podgursky, Xiqian Wang (2018). Teacher Pension Plan Incentives, Retirement Decisions, and Workforce Quality. CALDER Working Paper No. 200-0718-1