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.
EFFECTIVE NUMBER OF CLUSTERS AND INFERENCE WITH INSTRUMENTAL VARIABLES
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.
Other Projects and Affiliations
Information about COVID-19 and its observed effects on foot traffic in Santa Barbara County.
The Economic Forecast Project provides reliable economic, demographic, health, and environmental data and analysis to our community of citizens, government, business, non-profit, and other users.
A short tutorial on how to work with ERA Reanalysis Data in Netcdf format in R and creating an interactive leaflet map of weather data.
A short tutorial mapping NFL stadiums and finding the closest stadium to every United States county.
The Community Indicators Project measures the social, environmental, and economic factors that affect the quality of life in Santa Barbara county.
A short tutorial on how to import your Strava activities into R and create a heatmap.