Cassandra Merritt

I am a Ph.D. candidate with the Department of Economics at University of California, Davis. As a labor economist with a focus in the economics of education, my primary interests are oriented around the efficacy of schools and educational interventions in preparing students for further levels of schooling and for the changing landscape of work and labor markets. My recent projects investigate the impact of innovations in secondary math education and college advising, largely in tandem with my work as team member of the California Education Lab; I also have joint work investigating the determinants of new and disappearing job titles across US commuting zones. Prior to UC Davis, I served as a field economist for the Bureau of Labor Statistics. I previously earned a master’s degree in economics from the University of Edinburgh and a bachelor’s degree in mathematical business economics from Hofstra University. I expect to enter the 2024-25 economics job market and graduate from UC Davis by June 2025.

Works in Progress

Sorting Out the Effect of Course Choice: A Math Course Expansion in California Public High Schools

Abstract: The roll-out of new mathematics courses across California high schools provides an opportunity to answer a fundamental question about the consequences of choice in education.  The schools that expand their math course programming might endogenously select into such a policy change, but the timing of adoption of a particular set of differentiated alternative 12th grade math courses among schools is plausibly exogenous. Hence, exploiting the within-school variation in outcomes over time allows for causal analysis that can unpack the effects of broadening course programming. Preliminary results point to a general increase in 12th grade math enrollment outcomes, however, these effects do not appear to translate to increased postsecondary enrollment among the general student body. 

The Impact of Data Integrated Guidance Between California Public High Schools and Colleges

Abstract: The road to college has many hurdles, and the journey is an unravelling mystery for each traveller -- the right information could be crucial for post-secondary matriculation. The California College Guidance Initiative (CCGI) started rolling out data-driven guidance tools across many California school districts and charter networks from 2013 to present, and now serves as the basis for the state's Cradle-to-Career Data System initiative. A key feature of CCGI tools is integration between local school IT systems, the UC Office of the President's approved A-G course database, and California universities' application systems. California universities' admission requirements include completion of a validated A-G curriculum -- a complexity CCGI serves to alleviate. Using California Department of Education student-level K-12 data, the intent-to-treat effect of CCGI's information treatment is measured via an "event study"-esque specification. Results show weak statistically significant evidence of a 5 percentage point increase in A-G curriculum completion if the tools are available over a student's full high school tenure.

Measuring and Predicting "New Work" in the United States:  The Role of Local Factors and Global Trends (Co-Authored with Gueyon Kim & Giovanni Peri)

Abstract:  "New work”, namely the introduction of types of jobs that did not exist earlier, is an essential part of innovation and employment growth for advanced economies. Using text analysis, we develop an algorithm that identifies new job titles in the US economy based on their vector distance from the closest existing job title in the previous census. We use this method to generate a measure of "new work” from 1980 to 2010 in each of 354 occupations and we construct its distribution across 722 commuting zones. We first show how this measure of "new work" is associated to task and skill characteristics of workers in the occupations and to employment growth, skill bias and innovation in the commuting zones. Then we analyze whether local population density, human capital and manufacturing intensity in the 1980, and/or local exposure to structural "shocks" in the 1980-2010, relating to trade competition, technological change, immigration and age changes predict the creation of "new work." Our main findings show that the share of college educated and the density of population in 1980 are the strongest predictors of "new work'' in the 1980-2010 period. The aging of population and exposure to computer adoption were also associated with "new work,'' while robot adoption was negatively associated to it. The exposure to immigration and trade had a more nuanced and differentiated correlation to "new work."


Reed, S., Hurtt, A., Kurlaender, M., Luu, J., & Merritt, C. (2023, July). Inequality in academic preparation for college [Report]. Policy Analysis for California Education. 

Reed, S., Bracco, K. R., Kurlaender, M., & Merritt, C. (2023, February). Innovating high school math courses through K–12 and higher education partnerships [Report]. Policy Analysis for California Education. 

Reed, S., Merritt, C., & Kurlaender, M. (2022, December). 12th-grade math: An updated look at high school math course-taking in California [Infographic]. Policy Analysis for California Education. 

Resting Papers

Investigating the Impact of Advanced Math Courses on High School and College Outcomes in California (ancestor to "Sorting Out the Effect of Course Choice")

Abstract: Coursework in high school has the potential to determine student trajectories well beyond. Math courses have been shown to affect college attendance (Dougherty, Goodman, Hill, Litke, and Page, 2017; Kim, Kim, DesJardins, and McCall, 2015; Long, Conger, and Iatarola, 2012), degree completion (Adelman, 1999, 2006; Smith, Hurwitz, and Avery, 2017), and career earnings (Rose and Betts, 2004). These benefits may have motivated inefficient sorting of students into a single traditional math pathway, resulting in: (i) disparate outcomes between student subgroups as under-prepared students are forced into ill-fitting classes, often amplifying inequities; and (ii) stagnant math readiness among the overall student population. This paper investigates the effects of introducing alternative pathways, which break away from the traditional hierarchical curriculum, embodied by Advanced Innovation Math (AIM) courses designed by six intersegmental partnerships in California (Reed, Brocco, Kurlaender, and Merritt, 2023). Inexact matching estimators are applied to an analysis dataset, derived from restricted-use student records from the California Department of Education (CDE) matched to the National Student Clearinghouse (NSC) post-secondary enrollment data, to investigate the effect of AIM courses on high school and college outcomes. AIM courses increase the likelihood that students will complete course requirements for California State University or University of California eligibility by 3–10 percentage points, and, in some cases, improves high school math grades. Enrollment in an AIM course can also increases the likelihood of attending college