Jiaxin Wu
Jiaxin Wu is PhD candidate at the Stockholm School of Economics and affiliated with the Swedish House of Finance (SHoF).
Corporate Governance
Millennials and Gen Z Are Willing to Accept Lower Wages to Work in More Sustainable Firms
Firms in more environmentally friendly sectors are better able to attract and retain talent and at lower wages. Millennials and Gen Z,...
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Antitrust and Competition
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...
Commentary
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...
Antitrust and Competition
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.
Economic History Series
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...
Antitrust and Competition
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...
Antitrust and Competition
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...
Corporate Governance
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....
