The Power of Exclusion: Pharmacy Networks and Bargaining in Medicare Part D
Creators: name: Town, Robert
name: Swanson, Ashley
name: Starc, Amanda
name: Fleitas, Sebastian
name: Gowrisankaran, Gautam
Publisher: name: Stanford Digital Repository
Year: 2025
Subjects: Nash-in- Nash with threat of replacement (NNTR)
Medicine Part D
Pharmacy Chains

description: In many markets, prices are determined via bilateral negotiations between firms with market power. In such negotiations, parties often seek to improve their bargaining leverage. A downstream firm may threaten to exclude an upstream firm from its network. An upstream or downstream firm may merge with a competitor or a negotiating partner. In this paper, we study preferred retail pharmacy networks in the Medicare Part D prescription drug insurance program for the elderly to measure the impact of market structure and exclusion on equilibrium networks, prices, and consumer welfare. We estimate a game of network formation, price negotiation, and premium setting. We use a Nash-in-Nash with threat of replacement (NNTR) bargaining model for negotiated prices (Ho and Lee, 2019). In the NNTR model, insurers and pharmacy chains negotiate over prices and preferred network inclusion, and insurers can threaten to eliminate pharmacy chains from the preferred network entirely or replace them with any other, non-preferred pharmacy chain. Insurers set consumer premiums simultaneously. Next, Medicare beneficiaries enroll in a plan. Finally, enrollees experience prescription drug needs and fill them at pharmacies, and pay lower out-of-pocket prices at preferred pharmacies. We model retail pharmacy demand as a function of distance and expected consumer out-of-pocket costs, given enrollee characteristics (Starc and Swanson, 2021). We then estimate plan demand as a function of premiums and the ex ante expected value of the plan’s network implied by the pharmacy demand model, given consumer characteristics. Finally, using the estimated pharmacy and plan demand models, we recover bargaining weights implied by the NNTR network formation and pricing game. We estimate the bargaining weights by matching predicted NNTR prices to prices observed in the data in a GMM framework, conditioning on the observed network structure. The bargaining weights are identified by the presence of substitutes to insurers and pharmacy chains, including the presence of pharmacy chains that do not have preferred status with a given insurer and hence, which can be used as replacement threat points. Our estimates show that, allowing for exclusion, in the estimation meaningfully impacts the bargaining parameter estimates. Our preliminary estimates indicate that pharmacy chains have an average of 10-20% of the bargaining weight relative to insurers. This indicates that pharmacy chains capture only a relatively small fraction of the available surplus on average. We also demonstrate that the NNTR approach is better able to match the patterns in our data than the more common Nash-in-Nash bargaining model, in which insurers can threaten pharmacies with exclusion but not replacement. For most cases, the Nash-in-Nash approach misleadingly implies average bargaining weights for pharmacies that are very close to zero. Having estimated bargaining weights in the NNTR game, we then perform a series of counterfactual exercises, exploring the impact of horizontal mergers between pharmacy chains upstream, and between insurers downstream. Finally, we examine pro- and anti-competitive effects of vertical integration in this market, focusing on the impact of a recent acquisition between CVS and Aetna.