11:20 - 13:00
P12
Room:
Room: South Room 220
Panel Session 12
Indraneel Sircar - The Great Lockdown and Economic Voting: Estimating the Impact of the SARS-CoV-2 Recession on the 2020 US Presidential Election
Seonghui Lee - Surfing the COVID Waves? A Comparative Study on the Determinants of Election Postponement
Constanza Sanhueza Petrarca - Government Opposition and Non-compliance with the Covid-19 Prevention Measures: Evidence from 11 European Countries
Max Schaub - Health crises and the cultural roots of antisemitism
Kirby Goidel, Julia Scoobe - Primary Care Physicians, State Governments, and COVID-19 Responsibility and Response
The Great Lockdown and Economic Voting: Estimating the Impact of the SARS-CoV-2 Recession on the 2020 US Presidential Election
P12-1
Presented by: Indraneel Sircar
Indraneel Sircar
University College London
The 2020 US presidential election was won by Democrat challenger Joseph Biden over Republican incumbent Donald Trump and was contested during the global novel coronavirus (SARS-CoV-2) pandemic. The pandemic and policy responses to curb SARS-CoV-2 cases in the US sharply increased unemployment. We investigate whether there was economic voting in the 2020 election, that is, whether increased unemployment rate during the pandemic negatively affected Trump’s vote. We examine the eight closely contested ‘battleground states’ where Biden won: Arizona, Georgia, Michigan, Minnesota, Wisconsin, Pennsylvania, Nevada, and New Hampshire. Using triple-differences (DDD) models by state (that is, examining changes in a candidate's county-level vote-share depending on the change in unemployment and historical Republican-Democrat partisanship), we find that there was a significant effect of unemployment change in a number of battleground states. We then use these models to predict what would have happened if the increase in unemployment rate in spring 2020 had been half of the actual value. Although Biden would have still secured enough electoral votes to win the presidency according to the predictions, the result would have been far closer.