The price effects of cross‐market mergers: theory and evidence from the hospital industry

• Author: Kate Ho,Robin S. Lee,Leemore Dafny
• Published date: 01 June 2019
• Date: 01 June 2019
• DOI: http://doi.org/10.1111/1756-2171.12270

RAND Journal of Economics

Vol.50, No. 2, Summer 2019

pp. 286–325

The price effects of cross-market mergers:

theory and evidence from the hospital

industry

Leemore Dafny∗

Kate Ho∗∗

and

Robin S. Lee∗

We consider the effect of mergers between firms whose products are not viewed as direct sub-

stitutes for the same good or service, but are bundled by a common intermediary. Focusing on

hospital mergers acrossdistinct geographic markets, we show that such combinations can reduce

competition among merging hospitals for inclusionin insurers’ networks, leading to higher prices

(or lower-quality care). Using data on hospital mergers from 1996–2012, we find support that

this mechanism operates within state boundaries: cross-market, within-state hospital mergers

yield price increases of 7%–9 % for acquiring hospitals, whereasout-of-state acquisitions do not

yield significant increases.

1. Introduction

Merger analysis is a staple of antitrust enforcement. When a merger eliminates current or

potential competition for a relevant product or service, enforcers may sue to block or unwind the

transaction. According to the most recent release of the “Horizontal Merger Guidelines,” which

articulate the principles followed by the federal antitrust enforcement agencies, merger analysis

is a “fact-specific process,” one in which the particulars of the relevant market(s) and merging

parties are integral to enforcement decisions. One such particular is the presence (or absence)

of intermediaries in the chain of production or distribution. In this study, we evaluate mergers

of upstream suppliers to intermediaries that bundle products or services for sale to customers,

who in turn may aggregate the preferences of multiple individuals. We argue that the presence of

intermediaries selling to such customers can affect both the likelihood and margin of harm from

∗Harvard University and NBER; ldafny@hbs.edu, robinlee@fas.harvard.edu.

∗∗Princeton University, NBER, and CEPR; kate.ho@princeton.edu.

Wethank the Editor, three anonymous referees, David Balan, Cory Capps, David Dranove, Gautam Gowrisankaran,Aviv

Nevo,Bob Town, Nathan Wilson, and numerous conference and seminar participants for useful comments and discussion;

and Matthew Schmitt and Victoria Marone for exceptional research assistance. All errors are our own.

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DAFNY, HO AND LEE / 287

a merger of suppliers, and that harm to consumers may result, even if the products being supplied

are not direct “head-to-head” rivals at the point of sale. Examples of such settings include: cable

TV, where different content producers offer channels that are not direct substitutes but negotiate

prices with distributors that market a bundle of channels to multiperson households; and retail

product markets, where products may be targeted to different consumers but are stocked by

retailers offering one-stop shopping.

Health insurance is another relevant example. Private (commercial) insurers bargain with

providers(e.g., physicians or hospitals) over reimbursement rates (prices); the insurers then bundle

these services, adding in administrative and oversightfeatures—as well as risk-bearing in the case

of “full insurance” products—and sell insurance plans to employersand households. Hospitals are

critical upstream suppliers to health plans, accounting for nearly one third of healthcare spending

in the United States today.1Inrecent years, the Federal Trade Commission (FTC) has successfully

challenged several proposed mergers of hospitals that are direct substitutes at the point of care

(i.e., in the same geographic and product market), informed by an economic literature showing

that these “within-market” mergers tend to result in price increases for privately insured patients

without significant quality improvements.2

In contrast, there has been very little regulatory activity regarding hospital mergers across

distinct markets. This gap is notable in light of the significant pace of such “cross-market” mergers

in recent years.3More than half of the 528 general acute-care hospital mergers between 2000 and

2012 involved hospitals or systems without facilities in the same CBSA,4and a recent study by

Lewis and Pflum (2016) shows substantial increases in prices for independent hospitals acquired

by out-of-market systems (located 45+minutes away), as well as price increases by nearbyrivals.

As we describe below, current methods of assessing the anticompetitive threat from hospital

mergers assume there can be no increase in bargaining leverage unless the merging parties are

vying to provide the same set of services to the same set of patients. These methods implicitly

assume that insurance markets do not impact upstream market power; more formally, the models

typically assume insurers face demand that is separable across product and service markets (as

in Capps, Dranove, and Satterthwaite, 2003).

We argue that an extension to the current methodology is warranted in light of the role and

realities of intermediary markets. Insurers negotiate with and pay hospitals for their services,

and demand for insurance may not, in fact, be separable across service markets. We show that

the presence of “common customers” (e.g., employers or households) who purchase insurance

products and value the services offered by both merging parties can give rise to greater post-

merger bargainingl everagefor the merging hospitals, even when those hospitals operate in distinct

patient markets. These common customers are likely to be large employersthat demand insurance

products covering hospital services in multiple distinct geographic markets, that is, areas where

their employeeslive and work. Because insurers serve employers in multiple geographic regions, a

merged cross-market hospital system that coversthose regions can demand higher reimbursement

rates from insurers.5

1CMS National Health Expenditure Accounts, available at www.cms.gov/research-statistics-data-and-

systems/statistics-trends-and-reports/nationalhealthexpenddata/nhe-fact-sheet.html.

2See Dranove and White (1994); Town and Vistnes (2001); Capps, Dranove,and Satterthwaite (2003); Gaynor and

Vogt(2003); Dafny (2009); Haas-Wilson and Garmon (2011); Farrell et al. (2011); Gaynor and Town (2012); Gaynor,

Ho, and Town(2015), among others.

3Examples include the $3.9 billion acquisition of Health Management (71 hospitals) byCommunity Health Systems

(135 hospitals) in 2014, and the 2013 merger of Dallas-based Baylor Health Care System and Temple-based Scott &

White Health; post-merger, the combined entity comprised 43 hospitals and more than 6000 affiliated physicians.

4Data from Irving Levin on 528 general acute-care hospital mergers between 2000–2012 indicate that 256 (48.5%)

involved hospitals located within the same CBSA; 193 (36.6%) werein the same state but not the same CBSA; whereas

79 (15%) were out-of-state. A CBSA is defined as a metropolitan statistical area in larger cities, and a “micropolitan”

area in smaller towns. For further details, see www.census.gov/programs-surveys/metro-micro/about.html.

5Common customers for insurance products can also be households that demand services of hospitals in the same

geographic area but different product markets, for example, pediatric and cardiac specialty hospitals.

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288 / THE RAND JOURNAL OF ECONOMICS

Consider for illustrative purposes a simple setting where a state-wide employer chooses

insurance products to offer to employees who are evenly distributed across the state. Assume

there are 10 local markets, each of which contains three evenly sized, competing hospitals.

Insurers engage in pair-wise bargainingwith hospitals over prices. Under current antitrust practice,

authorities would be likely to object to mergers of hospitals within a local market on the grounds

that they would “substantially lessen competition or tend to create a monopoly,” per Section

7 of the Clayton Act.6They would be unlikely, however, to object to cross-market mergers—

even repeated mergers that created three large hospital systems, each owning a hospital in every

market. However, the cross-market presence of the large employer implies a potentially large

effect of these mergers on negotiated hospital prices. Although the employer would be unlikely

to drop an insurance plan that removed just one of the 30 hospitals from its network(because this

would affect few of its employees), it would be much more likely to drop a plan that removed a

large hospital system representing a third of all hospitals. Thus, competition among insurers for

inclusion in employers’ plan menus provides the large hospital system with greater bargaining

leverage than individual hospitals to negotiatehigher prices, even if no two hospitals in the system

operate in overlapping service markets.

The first part of this article uses a theoretical model of bargaining between upstream suppliers

and downstream intermediaries to formalize the intuition outlined above. Building on the model

in Ho and Lee (2017), we show that a sufficient condition for a market power effect of an

upstream merger between hospitals is that the insurer’s objective function, typically represented

by its profits, is submodular in the set of upstream hospitals—that is, the value of a hospital

to an insurer is decreasing in the size of the insurer’s hospital network. This condition can be

satisfied under standard formulations for consumer demand and insurer profits if the hospitals

are valued by a common customer, (e.g., employer or household) even if they operate in different

service markets. Our model formalizes some of the arguments in Vistnes and Sarafidis (2013),

which includes numerical examples illustrating how price effects may arise when employers

recruit employees from different geographic areas. We also provide conditions under which a

merger between hospitals negotiating with a common insurer,even absent common customers, is

sufficient to generate a price effect.7

The second part of the article explores the predictions of our model using panel data

on hospital prices and system acquisitions, supplemented with data on local insurance market

shares. We examine two distinct samples of acute-care hospital mergers over the period 1996–

2012, and compare the price trajectories of three groups of hospitals: (i) hospitals acquiring a

new system member in the same state but not the same narrow geographic market (“adjacent

treatment hospitals”); (ii) hospitals acquiring a new system member out-of-state (“nonadjacent

treatment hospitals”); and (iii) hospitals that are not members of “target” (i.e., acquired) or

acquiring systems. To minimize concerns about the exogeneity of which hospitals are parties

to transactions, we focus on hospitals that are likely to be “bystanders” rather than the drivers

of transactions. Our first sample of transactions comprises mergers investigated by the FTC

due to potential horizontal overlap among the merging parties. We argue that hospitals that are

members of the merging systems but located outside the areas of concern likely fall into the

bystander category. Our second sample makes use of a broader set of mergers, that is, we begin

with the set of all mergers involving at least one hospital system over the period 2002–2012. We

limit the treatment group in two ways: first, we exclude hospitals that are the “crown jewels” of

each deal (so the remaining hospitals are likely to be bystanders to the transaction); second, we

exclude hospitals that gain a system member within 30 minutes (or are located within 30 minutes

of another hospital that experiences the same over a five year period spanning the transaction

6Throughout this manuscript, we refer to “price effects,” but our theoretical and conceptual observations apply

equally to other potential merger effects, such as effects on quality or innovation.

7Depending on the precise mechanism, these effects may not arise from a diminution of competition among the

merging entitites.

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