Paper by Daniel Goldstein and Johannes Wiedemann: “To combat the novel coronavirus, there must be relatively uniform implementation of preventative measures, e.g., social distancing and stay-at-home orders, in order to minimize continued spread. We analyze cellphone mobility data to measure county-level compliance with these critical public health policies. Leveraging staggered roll-out, we estimate the causal effect of stay-at-home orders on mobility using a difference-in-differences strategy, which we find to have significantly curtailed movement.
However, examination of descriptive heterogeneous effects suggests the critical role that several sociopolitical attributes hold for producing asymmetrical compliance across society. We examine measures of partisanship, partisan identity being shared with government leaders, and trust in government (measured by the proxies of voter turnout and social capital). We find that Republican counties comply less, but comply relatively more when directives are given by co-partisan leaders, suggesting citizens are more trusting in the authority of co-partisans. Furthermore, our proxy measures suggest that trust in government increases overall compliance. However, when trust (as measured by social capital) is interacted with county-level partisanship, which we interpret as community-level trust, we find that trust amplifies compliance or noncompliance, depending upon the prevailing community sentiment.
We argue that these results align with a theory of public policy compliance in which individual behavior is informed by one’s level of trust in the experts who craft policy and one’s trust in those who implement it, i.e., politicians and bureaucrats. Moreover, this evaluation is amplified by local community sentiments. Our results are supportive of this theory and provide a measure of the real-world importance of trust in government to citizen welfare. Moreover, our results illustrate the role that political polarization plays in creating asymmetrical compliance with mitigation policies, an outcome that may prove severely detrimental to successful containment of the COVID-19 pandemic….(More)”.