Optimal contracting with altruistic agents: A structural model of Medicare payments for dialysis drugs

Arbeitspapier

We study physician agency and optimal payment policy in the context of an expensive medication used in dialysis care. Using Medicare claims data we estimate a structural model of treatment decisions, in which physicians differ in their altruism and marginal costs, and this heterogeneity is unobservable to the government. In a novel application of nonlinear pricing methods, we theoretically characterize the optimal unrestricted contract in this screening environment with multidimensional heterogeneity. We combine these results with the estimated model to construct the optimal contract and simulate counterfactual outcomes. The optimal contract is a exible fee-for-service contract, which pays for reported treatments but uses variable marginal payments instead of constant reimbursement rates, resulting in substantial health improvements and reductions in costs. Our structural approach also yields important qualitative findings, such as rejecting the optimality of any linear contract, and may be employed more broadly to analyze a variety of applications.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CHCP Working Paper ; No. 2020-3

Classification and Topics

• Classification: Wirtschaft ; Economics of Contract: Theory ; Transactional Relationships; Contracts and Reputation; Networks ; Analysis of Health Care Markets ; Health Insurance, Public and Private ; Economics of Regulation ; National Government Expenditures and Health ; Health: Government Policy; Regulation; Public Health
• Subject: Optimal contracts ; asymmetric information ; screening models ; health care ; paymentpolicy

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gaynor, Martin ; Mehta, Nirav ; Richards-Shubik, Seth
• Event: Veröffentlichung
• (who): The University of Western Ontario, Centre for Human Capital and Productivity (CHCP)
• (where): London (Ontario)
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/240392
• Last update: 10.03.2025, 11:44 AM CET