Date of Completion

Spring 5-1-2021

Thesis Advisor(s)

Dr. David Simon

Honors Major



Behavioral Economics | Health Economics | Political Economy


The COVID-19 pandemic has affected all aspects of life within the United States since early 2020. How people decided to behave during this time heavily influenced the trends that followed, triggering both health and behavioral economic concerns. Those trends seemed to vary based on the area and the beliefs of those constituents. This paper explores how partisan beliefs had an impact on the changes in case rates that occurred within the top 30 most populated towns in the state of Connecticut. In July 2020, former President Donald Trump sent out a tweet publicly endorsing face masks for the first time. This paper studies the effects and trends on case rates a month after that information shock across those top 30 towns. The initial assumption was that in democratic areas, an information shock coming from a republican source would either have a negative or no significant impact. However, the results show that the more democratic an area was, the tweet had a larger effect on decreasing rates. Although there are many other factors that can help explain this result, the research here suggests that information shocks can be very impactful in areas of high partisanship.