Dissertation Defense: “Essays in Health and Public Economics” Sarah Robinson
Biography
Sarah Robinson is a PhD Candidate in Economics at the University of California, Santa Barbara. Her primary interests are in Health Economics and Public Economics. Sarah uses empirical methods to estimate the causal effects of policy on individuals and firms. In addition, she investigates the mechanisms that drive differences in health insurance coverage, health outcomes, and public policy. Currently, she is particularly interested in how firms make decisions about the health insurance they offer to workers.
Sarah's work has been supported by the National Institute on Aging as a Pre-Doctoral Fellowship at the National Bureau of Economic Research. She received a BA in Philosophy, Politics, and Economics from Claremont McKenna College in 2013 and subsequently worked in the Strategy & Operations practice at Deloitte Consulting LLP.
Abstract
This dissertation contains three chapters on health and public economics. Chapter 1 explores whether firms avoid health insurance mandates by self-funding their health plans. 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.
Chapter 2 investigates the drivers of tax policy. 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.
Chapter 3 studies geographic variation in the use of C-sections. We use U.S. natality data from 1989 to 2017 to investigate county-level geographic disparities in the use of C-section among first-birth singleton mothers. We document the existence and persistence of geographic variation in C-section across low- and high- C-section risk mothers and the sensitivity of C-section use and infant and maternal health outcomes to C-section risk across counties. Our key finding is that counties with high C-section rates perform more C-sections across the entirety of the risk distribution. Yet these higher rates of C-section are correlated with nearly equivalent or better outcomes than counties with less-intensive C-section rates.
