Profits, Pandemics, and Lockdown Effectiveness: Theory and Evidence from Nursing Home Networks

How do the effects of government policy response to health crises differ for for-profit and not-for-profit organizations? We theoretically address this question through the lens of a two-sector continuous-time individual-based mean-field theoretical model incorporating a social network and show that a unique equilibrium exists under classical conditions. We test our model using unique data on nursing home networks in the United States. We calibrate the model and jointly quantify state-level lockdown effectiveness and preference for enforcing stringent containment strategies during the COVID-19 pandemic. We validate our estimated policy measures using external data. Simulations and regression-based analyses show that not-for-profit nursing homes are much more likely to be sent into lockdown, which results in for-profit nursing homes occupying more central positions in social networks. In addition, lockdown effectiveness interacts significantly with the ownership status of a nursing home to determine COVID-19 death among residents. In particular, the difference in COVID-19 deaths between for-profit and not-for-profit nursing homes rises with lockdown effectiveness; a one standard deviation increase in the effectiveness of lockdown intensifies the death gap by around 23 percent relative to the mean. Our analysis implies that the structure of markets and their heterogeneity in experiencing uncertain shocks can help policymakers design optimal targeted interventions for future pandemics.