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Under the Affordable Care Act (ACA), insurers cannot engage in medicalunderwriting and thus face perverse incentives to engage in risk selection anddiscourage low-value patients from enrolling in their plans. One ACA programintended to reduce the effects of risk selection is risk adjustment. Under arisk adjustment program, insurers with less healthy enrollees receive risktransfer payments from insurers with healthier enrollees. Our goal is tounderstand the elements driving risk transfers. First, the distribution of risktransfers should be based on random health shocks, which are unpredictableevents that negatively affect health status. Second, risk transfers could beinfluenced by factors unique to each insurer, such as certain plans attractingcertain patients, the extent to which carriers engage in risk selection, andthe degree of upcoding. We create a publicly available dataset using Centersfor Medicare and Medicaid Services data that includes insurer risk transferpayments, costs, and premiums for the 2014-2017 benefit years. Using thisdataset, we find that the empirical distribution of risk transfer payments isnot consistent with the lack of risk selection as measured by the ACA risktransfer formula. Over all states included in our dataset, at least 60% of thevolume of transfers cannot be accounted for by a purely normal model. Becausewe find that it is very unlikely that risk transfer payments are caused solelyby random shocks that reflect health events of the population, our work raisesimportant questions about the causes of heterogeneity in risk transfers.

Empirical Characteristics of Affordable Care Act Risk Transfer Payments