Martin Gaynor

Martin Gaynor is the E.J. Barone University Professor of Economics and Public Policy at Carnegie Mellon University and former Director of the Bureau of Economics at the US Federal Trade Commission. Professor Gaynor's research focuses on competition and incentives in health care, and on antitrust policy.

More Than 20 Years of Consolidation Have Led to a Dysfunctional Health Care Market

The US health care system is based on markets, which do not function as well as they could, or should. Prices are...

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George Stigler on Henry Simons, “Crown Prince” of the Chicago School

To mark 75 years since the passing of Henry Simons, professor of Economics and Law at the University of Chicago, ProMarket is...

Electoral College Reform: New Problems or Real Solutions?

Each electoral system creates specific incentives to (mis)allocate government resources. Would putting the National Popular Vote (NPV) in lieu of the Electoral...

When Do Users Benefit From Platform Mergers?

A new paper shows that platform mergers can harness network effects at the cost of reducing the platform differentiation that users value. 

Harold Demsetz and Israel Kirzner Understood That Competition Regulates Markets

Economists Harold Demsetz and Israel Kirzner challenged the prevailing orthodoxy in microeconomic analysis and public policy beginning with their respective work in...

The Covid-19 Pandemic Should Not Delay Actions to Prevent Anticompetitive Consolidation in US Health Care Markets

Harvard Business School professor Leemore Dafny lays out potential reforms to assist agencies in halting anticompetitive acquisitions and practices, and to preserve...

Who Benefits From Competitive State-Level Legislatures?

A new paper finds that when interparty competition in state legislatures is high, well-connected and influential incumbent firms are best able to...

No More “Mystery Meat”: Why We Need Better Corporate Governance Data

Three decades of finance, economics, and legal studies in corporate governance have been built substantially on data sets with nearly unknown provenance....