Research

Abstract: Many hourly paid and low wage earners choose to waive enrollment in commercial health insurance coverage. This can be problematic because low wage earners tend to work in conditions that are more prone to injury and illness. Nevertheless, potential motivations not to enroll may be the high cost of premiums, excellent health, and health literacy. However, little evidence documents employee enrollment dynamics focused specifically on those who waived and then enroll in commercial coverage, especially among low wage earners. We estimate the change in health care utilization among those who enroll in health insurance following a year of waiving employer health insurance. Our samples consist of 10,292 employees at a large nationwide restaurant chain employed between 2019 and 2020. In 2020, 17% (1,753 employees) of those enrolled waived coverage in 2019. We study the impact of the enrollment variation across time combined with employee job-categories tied to wage – salaried employees who are generally higher income, hourly employees making below $15 an hour, and hourly employees making above $15 an hour. Among those employees enrolled in both years, hourly employees (both below and above $15 an hour) utilize less outpatient care than salaried employees. Salaried employees enrolled in 2020 were about 7 percentage points less likely to utilize outpatient care and utilized about 2 fewer outpatient visits in 2020 compared to salaried employees enrolled in both 2019 and 2020. Compared to salaried employees who enrolled in coverage in 2020, employees making less than $15 an hour who enrolled in 2020 were about 5 percentage points more likely to utilize outpatient care and utilized 2 more outpatient visits in 2020. Hourly employees making more than $15 an hour who enrolled in 2020 did not utilize outpatient care significantly different than salaried employees who enrolled in 2020. For all employees who enrolled in 2020, we did not observe increased emergency department use or hospitalizations. However, both low and high hourly paid employees had higher primary care physician visits than salaried employees who enrolled in 2020, while salaried employees who waived coverage in 2019 had fewer primary care physician visits than salaried employees enrolled in both years. To explore whether the identified differences in health care utilization could be explained by a lag in utilization once enrolled due to learning, we also look at the difference in utilization between the newly hired and the newly insured. Both groups are insured through this employer in 2020 and not insured through this employer in 2019. When compared to newly hired employees, hourly employees (below and above $15 an hour) are more likely to utilize outpatient care. Those newly insured making below $15 an hour are about 12.5 percentage points more likely to utilize outpatient care and those above $15 an hour are about 9 percentage points more likely to utilize outpatient care. There is no statistically significant difference between newly hired and newly insured salaried employees, suggesting that waiving health insurance coverage may lead to pent-up demand among hourly employees but not among salaried employees.

Abstract: I estimate the impact of air pollution events caused by wildfire smoke on respiratory and circulatory health outcomes. Utilizing a combination of California health data and NOAA wildfire smoke data I can estimate the impact of exposure to wildfire smoke on health outcomes for all individuals in California. Using inpatient data I am able to construct a measure of exposure to wildfire smoke prior to the hospital visit, this allows for the identification of the impact of wildfire smoke exposure on different health outcomes. I find that an additional day of smoke exposure in a month leads to on average 11.38 additional hospital admissions for respiratory diagnoses and an additional 3 hospital admissions for circulatory diagnoses. This translates to an annual cost of wildfire smoke exposure in California due to respiratory and circulatory hospital admissions of $192,316,498.

Abstract: How does the sharing economy affect traditional lodging markets? The advent of platforms such as Airbnb in 2008 has introduced a new channel of market interaction between those with space and those who seek it. This allows for transactions of lodging services that might otherwise be underutilized. This paper develops a framework to help think about how peer-to-peer transactions interact with traditional rental mar- kets, and what this means for property managers and tenants. Specifically, we examine how the introduction of sharing platforms (e.g. Airbnb) affect the listing decisions of managers of vacant properties and the lodging choices of dwelling seekers. The model features landlords who choose where to list vacant properties and renters who search for lodging. Renters can be either short or long-term, referencing how long they wish to occupy the property. Sharing platforms give landlords the option of accessing these short-term renters who would otherwise occupy hotels, affecting traditional, long-term renters. We find that Airbnbs decrease hotel prices by about $24 per night (about a 10% reduction) while they increase average rents by $39 per room, per month (about a 2.5% increase).

Abstract: We study the behavior of cluster-robust test statistics in models with instrumental variables when cluster heterogeneity is present. Inference in a large number of papers using two-stage least squares regressions published in American Economics Association journals are driven by the presence of one or two influential clusters. We link a measure of cluster heterogeneity, the feasible effective number of clusters, to measures of influence. Using simulations, we demonstrate that high levels of cluster heterogeneity lead to coverage of less than 95% for 95% confidence intervals when using instrumental variables with panel data or with data that can be grouped into clusters. Using data from papers with two-stage least squares regressions published in American Economic Association journals, we show that the feasible effective number of clusters can be used as a pre-test to the sensitivity of two-stage least squares inference to influential clusters.

Abstract: I study the impact of changing weather patterns on the incidence of malaria and the effectiveness of malaria initiatives in Sub-Saharan Africa between the years 2000 and 2015. Combining malaria incidence with climate reanalysis I estimate the impact of malarious weather on malaria prevalence and analyze the changing efficacy of malaria prevention and treatment.