Sarah Robinson
Assistant Professor of Economics
Claremont McKenna College
I am an Assistant Professor of Economics at Claremont McKenna College. My research interests are in health economics and public economics.
sarah.robinson@claremontmckenna.edu
CV
@RobinsonSarah_
Peer-Reviewed Publications
“One Hundred Years of U.S. State Taxation” with Alisa Tazhitdinova, Journal of Public Economics, January 2025
⛁ Data
“Geographic Variation in Cesarean Sections in the United States: Trends, Correlates, and Other Interesting Facts” with Heather Royer and David Silver, Journal of Labor Economics, April 2024
☆ Featured in: NBER Bulletin on Health
“Corporate Political Spending and State Tax Policy: Evidence from Citizens United ” with Cailin Slattery and Alisa Tazhitdinova, Journal of Public Economics, May 2023
☆ Featured in: Wall Street Journal, Harvard Law School Forum on Corporate Governance, CATO Insitute
Working Papers
“Do Firms Avoid Health Insurance Mandates? Evidence from the Self-Funding of Employer Plans”
(Job Market Paper)
Fifty percent of the U.S. population gets health insurance through an employer, and roughly half of employers only offer one health plan. Therefore, the choices made by firms about what plan(s) to offer are critical to understanding the health insurance available to workers. This paper focuses on one dimension of the firm’s decision: whether to self-fund plans (meaning the firm bears the financial risk of claims itself). I study whether firms use self-funding to avoid complying with mandates to cover specific procedures or providers. Using administrative data on the health plans offered by firms and a difference-in-differences design, I find that new mandates increase rates of self-funding among smaller firms (100-249 employees) by 3.2 percentage points, an increase of 14.5%. The mandates do not appear to affect larger firms (250+ employees), who are more likely to already be self-funded in the pre-period. These results imply that new mandates can lead to long-lasting reductions in the proportion of firms that are bound by any state health insurance regulations, including all previously mandated benefits as well as premium taxes.
“Do Taxes Affect Pre-Tax Income Inequality? Evidence from 100 Years of U.S. State Policies” with Matías Strehl Pessina and Alisa Tazhitdinova
We study how U.S. state personal and corporate income taxes have affected pre-tax income inequality (income shares and top incomes) during the last century. The long panel nature of our data, from 1917 to 2018, allows us to study the effect of tax adoptions, tax cancellations, and tax changes, and to assess both immediate and long-term relationships. With event study and synthetic control designs, we generally find no statistically significant relationship between tax measures and inequality. Some of our point estimates, and also two-way fixed effects analysis, suggest that higher income taxes may reduce top incomes and income shares.
“Are U.S. State Tax Policies Increasingly Polarized?” with Alisa Tazhitdinova
We study the extent to which political polarization permeates U.S. state tax policies from 1910 to 2022. We document a dramatic increase in tax policy polarization in recent decades, particularly for personal income, corporate income, and cigarette taxes, but convergence in sales taxes. However, the current levels of polarization are not unique relative to the past. Furthermore, this polarization is only pronounced among states with large political majorities and stable political regimes. Yet state tax policies are not gridlocked: swing states change taxes as frequently as, and with similar magnitude to, deep red and blue states.
“What Drives Tax Policy? Political, Institutional and Economic Determinants of State Tax Policy” with Alisa Tazhitdinova
We collect detailed data on U.S. state personal income, corporate, sales, cigarette, gasoline, and alcohol taxes over the past 70 years to shed light on the determinants of state tax policies. We provide a comprehensive summary of how tax policy has changed over time, within and across states. We then use permutation analysis, variance decomposition, and machine learning techniques to show that the timing and magnitude of tax changes are not driven by economic needs, state politics, institutional rules, neighbor competition, or demographics. Altogether, these factors explain less than 20% of observed tax variation.
Work in Progress
“Employer Choice of Health Insurance Plans and Premium Sharing” (approved FSRDC project)
Resources
Teaching Materials for UCSB ECON PhD Math Camp
Other Resources
- UCSB ECON 210A PDF | LaTeX (PhD 1st Year Micro Fall – Consumption & Production)
- UCSB ECON 210B PDF | LaTeX (PhD 1st Year Micro Winter – Game Theory)
- UCSB ECON 134A Interest Rate Summary