How to Get Away with Merger: Stealth Consolidation and Its Real Effects on US Healthcare
Most US mergers are not reported to the government on the basis of their size, which can effectively exempt them from antitrust scrutiny, thereby leading to anticompetitive behavior. This paper studies premerger notification exemptions in the US dialysis industry. Over two decades, dialysis providers attempted over 4,000 facility acquisitions, half of which were not reported to the nation’s competition authorities. I estimate the effect of premerger notification exemptions on antitrust enforcement rates, and then I estimate the impact of the resulting market structure changes on patient health outcomes. First, I find that exemptions severely limit enforcement. Most striking, proposed facility acquisitions that would result in monopoly are blocked more than 80% of the time when apart of reportable mergers but less than 2% of the time when apart of exempt ones. Second, I find that the resulting market structure changes reduce the quality of care, evidenced by higher hospitalization rates and lower survival rates.
I thank Jimmy Roberts for suggesting the setting, Paul Eliason for helping navigate the data, and Fiona Scott Morton (NBER discussant), Judy Chevalier (ASSA discussant), John Asker, Dave Balan, Dennis Carlton, Thom Covert, Austan Goolsbee, Neale Mahoney, Ariel Pakes, Chad Syverson, Haris Tabakovic, and seminar participants at Harvard University, the Federal Trade Commission, Duke University, KU Leuven, Northwestern University, Columbia University, Chicago Booth, the NBER Winter IO Meeting, the ASSA Annual Meeting, Microsoft Research, Charles River Associates, the Hal White Antitrust Conference, the ASHEcon Annual Conference, and the Midwest IO Conference for thoughtful comments. Credit for the title belongs with Mike Sinkinson. (Note that the title was suggested and adopted before the paper contemplated mortality and is not intended to make light of that outcome.) Excellent research assistance was provided by James Kiselik, Paulo Henrique Ramos, Divya Vallabhanen, and Jason Yang. Financial support from the Becker Friedman Institute’s Health Economics Initiative is gratefully acknowledged. The data reported here have been supplied by the United States Renal Data System (USRDS). The interpretation and reporting of these data are the responsibility of the author and in no way should be seen as an official policy or interpretation of the US government. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.