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In this paper, I estimate country-level efficiency using a newer order-mestimator where I condition efficiency estimates on secondary environmental variables. This allows me to identify which variables influence the effectiveness of a healthcare delivery system. I find that not controlling for secondary environmental variables leads to the average OECD country being 11% inefficient; after controlling for demographics and economic (social protection) environmental variables, inefficiency reduces to 7% (5%). This provides evidence that a substantial part of the inefficiencies of a healthcare system is related to demographics, socioeconomics, and the structure of the healthcare delivery system. Using the second-stage results, I find lower healthcare spending, both as a percent of GDP and total out-of-pocket, as well as more of the population covered by public health insurance, is related to better efficiency. Lower fertility rates, lower immigration rates, higher incomes, and lower pharmaceutical doses are also consistent with better healthcare efficiency. Lastly, a healthcare system that provides a basic benefits package but allows for purchase of private health insurance, with moderate gatekeeping and flexibility to increase the budget for healthcare through public and private financing, are the most efficient healthcare systems.

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This paper examines the efficiency of four major COVID-19 social distancing policies: (i) shelter-in-place orders (SIPO), (ii) non-essential business closures, (iii) mandatory quarantine for travelers, and (iv) bans on large gatherings. Results suggest that the average US state is highly inefficient in producing the fraction of the population that does not have COVID-19 without social distancing policies put in place. We find that having any of the four major social distancing policies increases conditional efficiency by 9.7 (9.5) percentage points in the first 100 days (full sample). This corresponds to 57 (172) fewer total COVID-19 cases per 100,000 population in the first 100 days (full sample). We also find that population density accounts for a majority of unconditional state inefficiency. Evidence suggests considerable heterogeneity in conditional efficiency improvement, indicating that no uniform national social distancing policy would have been more effective; more effective strategies would have been to target more densely populated areas. Conditional efficiency regressions suggest that bans on large gatherings were the most effective policies, with SIPOs and non-essential business closures having smaller impacts. States that implemented social distancing policies except mandatory quarantine for traveler policies were highly effective for the first 100 days, but had less effectiveness over the full sample. There is also preliminary evidence that premature revocations of social distancing policies reduced conditional efficiency, leading to COVID-19 case spikes.