Political and Socioeconomic Influences on Social Distancing Behaviour in the United States

The Social Distancing Index (SDI) measures social distancing behaviour every day across all fifty American states. This study leverages SDI data to model social distancing behaviour with time-series COVID-19 data, as well as an array of political and economic variables. The central aim of this study is to examine three hypotheses: (i) COVID-19 outbreaks within a state will induce social distancing by fear of the virus, (ii) states with more low-income workers will engage in less social distancing due to the nature of essential work, and (iii) political beliefs will influence social distancing behaviour, through the public debate over social distancing policy and a partisan logic defining state stay-at-home orders. We use Vector Autoregressive (VAR) and Beta Regression models to determine the most influential variables in this study. VAR models for time-series relationships between cases and social distancing behaviour in California and Texas, and corresponding Granger-Cause Test results, are investigated through case studies. Significant Beta model variables influencing social distancing behaviour are closely examined through visual data analysis and qualitatively contextualized to describe relationships present in the data. Our results indicate statistically significant relationships between the severity of state outbreaks, age and income distribution, change in governor approval ratings, and social distancing behaviour. There are also clear relationships between the partisan make-up of a state and social distancing behaviour. The results found in this study contribute to growing evidence regarding the impact political polarization has on various aspects of American social life, while giving insight to behavioural dynamics that play a critical role in mitigating the spread of COVID-19.