Speaker

Austan Goolsbee

Austan Goolsbee

Economist and central banker; since January 2023 the tenth president and CEO of the Federal Reserve Bank of Chicago, and a voting or rotating member of the Federal Open Market Committee that sets US monetary policy.

Goolsbee spent most of his career at the University of Chicago’s Booth School of Business, where he was the Robert P. Gwinn Professor of Economics — an empirical microeconomist known for work on taxation, technology, and productivity, including a much-cited study (with Chad Syverson) documenting flat-to-negative productivity growth in the US construction industry over decades. He served in the Obama administration, chairing the Council of Economic Advisers in 2010–2011 after advising the 2008 campaign. He describes his method as that of a ‘data dog’ rather than an inflation hawk or dove: resolving questions by getting into the data and reasoning about causality, and resisting pre-commitment to any monetary-policy rule that is not robust to changing shocks.

Core positions

  • A ‘data dog’, not a hawk or dove. The most useful thing academic economics gives a central banker is the discipline of getting into the data and thinking about identification and causality — ‘a time for walking and a time for sniffing’.
  • Refuses to make policy off an accounting identity. MV = PY has no economic content; rules premised on past demand shocks fail when supply shocks dominate, as the 2023 ‘golden path’ (disinflation without recession) showed.
  • Post-pandemic inflation was not purely demand. Inflation soaring with unemployment above 6 per cent, its simultaneity across low-stimulus domestically-driven economies, and its fall as supply chains healed all point to a real supply component.
  • Shadow banking and stablecoins are the core financial-stability risk. Money-like deposits without insurance or asset restrictions end in runs — ‘500 years of financial history’ say so; the Fed should stay the ‘fuddy-duddy’ and keep risk off the payment system.
  • Defends the decentralised Fed and doubts AI magic. The twelve regional Reserve Banks guard against monetary-policy monoculture; and because a model is ‘only as good as the training sample’, AI (like a rule-bound central bank) hallucinates when the present is novel.

In the wiki