Beyond Statistics: The Economic Content of Risk Scores

Liran Einav, Amy Finkelstein, Raymond Kluender, Paul Schrimpf

NBER Working Paper No. 21304
Issued in June 2015, Revised in July 2015
NBER Program(s):Economics of Aging, Health Care, Health Economics, Industrial Organization, Public Economics

In recent years, the increased use of “big data” and statistical techniques to score potential transactions has transformed the operation of insurance and credit markets. In this paper, we observe that these widely-used scores are statistical objects that constitute a one-dimensional summary of a potentially much richer heterogeneity, some of which may be endogenous to the specific context in which they are applied. We demonstrate this point empirically using rich data from the Medicare Part D prescription drug insurance program. We show that the “risk scores,” which are designed to predict an individualʼs drug spending and are used by Medicare to customize reimbursement rates to private insurers, do not distinguish between two different sources of spending: underlying health, and responsiveness of drug spending to the insurance contract. Naturally, however, these two determinants of spending have very different implications when trying to predict counterfactual spending under alternative contracts. As a result, we illustrate that once we enrich the theoretical framework to allow individuals to have heterogeneous behavioral responses to the contract, strategic incentives for cream skimming still exist, even in the presence of “perfect” risk scoring under a given contract.

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Document Object Identifier (DOI): 10.3386/w21304

Published: Liran Einav & Amy Finkelstein & Raymond Kluender & Paul Schrimpf, 2016. "Beyond Statistics: The Economic Content of Risk Scores," American Economic Journal: Applied Economics, vol 8(2), pages 195-224.

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