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For scientific use, stochastic frontier estimates of hospital efficiency must be robust to plausible departures from the assumptions made by the investigator. Comparisons of alternative study designs, each well within the 'accepted' range according to current practice, generate similar mean inefficiencies but substantially different hospital rankings. The three alternative study contrasts feature (1) pooling vs partitioned estimates, (2) a cost function dual to a homothetic production process vs the translog, and (3) two conceptually valid but empirically different cost-of-capital measures. The results suggest caution regarding the use of frontier methods to rank individual hospitals, a use that seems to be required for reimbursement incentives, but they are robust when generating comparisons of hospital group mean inefficiencies, such as testing models that compare non-profits and for-profits by economic inefficiency. Demonstrations find little or no efficiency differences between these paired groups: non-profit vs for-profit; teaching vs non-teaching; urban vs rural; high percent of Medicare reliant vs low percent; and chain vs independent hospitals.

This paper presents an economic model to connect with the substantial empirical literature on social capital and health that exists largely outside of economics. Representative papers from that literature are reviewed and these show that disagreements exist on the nature and definition of social capital. The paper presents a new line of reasoning to support the view of social capital as a network of interpersonal bonds to include the bonds of family and close friends, not just the community at large. It then adapts and extends the work of Becker and Murphy on social economics to explain the demand for health goods as well as health bads in the presence of increased social capital. It further develops choice under risk to explain the demand for goods that entail a risk of death, such as cigarettes, illegal drugs, or excessive drinking. Empirical examples, including new statistical analyses are presented to illustrate the derivations.