Dilan Alpergin

Dilan Alpergin

PhD in Economics

Working Papers

Family Spillovers In Healthcare Consumption: Evidence From a Southern Healthcare Payor

Abstract: This paper studies how family spillovers affect healthcare consumption through behavioral changes where risks and consequences of health events are shared and transmitted in the family. By exploiting an unpredictable shock, a heart attack, to a family member, I draw a causal link to their dependents’ average medical expenditures. The spouse’s heart attack is used as a source of exogenous variation in healthcare consumption of non-injured family members since this event is relatively unpredictable and random for non-injured family members. Under this setting, I aim to compare the healthcare consumption in the pre- and post-shock periods to estimate family spillovers. For this purpose, I use claims data provided by a southern healthcare payor in the U.S. providing detailed information on the healthcare consumption of family members and various member-level characteristics, such as demographic and socioeconomic characteristics, chronic conditions, and income. I employ an OLS regression to compare the average health consumption before and after the spouse’s heart attack. The results show that the family spillover effect has a statistically significant and positive impact on non-injured family members’ healthcare consumption. In particular, I find that non-injured family members increased their average medical expenses by $571 in the post-period of their spouses’ heart attack relative to prior to the health shock. Moreover, I explore the effect of the health shock on different subgroups. The following subgroups show a statistically significant increase in average medical expenses after experiencing a health shock: individuals without chronic conditions, individuals who identify as White, females, and those with lower levels of education.

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Risk Perception of COVID-19 and Consumption Changes in California [JOB MARKET PAPER]

Abstract: This paper studies the causal relationship between consumers' risk perception of COVID-19 and changes in consumption expenditures in the U.S. at the early stages of the pandemic. Although providing empirical evidence of the causal relationship between risk perception and spending is challenging due to possible endogeneity problems, I address this problem using a two-stage instrumental variable (IV) approach. Specifically, I use the weekly growth rate of COVID-19 cases in New York as a source of exogenous variation in consumer risk perception of COVID-19 in California. Two datasets are used for this purpose: (i) The University of Southern California (USC) Center for Economic and Social Research's Understanding Coronavirus in America Survey and (ii) The Opportunity Insights Economic Tracker. I focus on the period from April 1, 2020 to January 2, 2021, before the COVID-19 vaccine was publicly available in California. The results show that the growth rate of confirmed cases in New York is a strong instrument that has a positive and statistically significant effect on California residents' risk perception of death, infection, money loss, and job loss due to COVID-19. Moreover, I find a statistically significant causal relationship between risk perception and consumption expenditures. This effect is negative for major consumption categories, such as accommodation and food services, health care and social assistance, and sporting goods and hobbies. On the other hand, the effect is positive for grocery and food stores and arts, entertainment, and recreation.

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Optimal Health Expenditures under Uncertainty in Patient Numbers

Abstract: Healthcare providers face unexpected changes in patient numbers as diseases and injuries are unpredictable. This paper studies socially optimal health expenditures and treatments by drawing attention to this quantity uncertainty in healthcare markets. This paper is the first to approach this problem from the norms of welfare economics. I first introduce a model that characterizes the socially optimal setting, then provide a model for healthcare providers and compare the outcomes from the two models. The results show that healthcare providers' investments in treatment resources differ from socially optimal levels. Based on this finding, I argue that healthcare providers fail to bring socially optimal treatment to society when there are unexpected surges in hospital patient flows.

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