
Campbell's sharper social-science version: the more a quantitative indicator is used for decision-making, the more it will be corrupted and the more it will distort the process it monitors. Where Goodhart notes the measure breaks, Campbell notes the underlying activity bends to fit it. In markets it explains why disclosure regimes reliably produce managed numbers.
Why large state plans fail when they override local, practical knowledge.
Recommended by: Balaji S. Srinivasan, Nat Eliason
How to test whether reported earnings reflect reality, from tax books to receivables.
Recommended by: Rational Capital Investment Fund and 1 other
The tricks companies use to inflate earnings, cash flow and key metrics, by case.
“Some of my favorites include Howard M. Schilit and Jeremy Perler, Financial Shenanigans” — Michael Mauboussin
Source: Thirty Years: Reflections on the Ten Attributes of Great Investors (Credit Suisse)
Recommended by: Michael Mauboussin, Anu Hariharan
Cathy O'Neil catalogues algorithmic systems deployed in hiring, lending, policing, and education that reinforce rather than correct existing inequities. The book's value is empirical: these are real systems with documented effects, not speculative risks.
Recommended by: Tom Peters
How fixation on measured performance damages the work it is meant to improve.
William Ackmanrecommends 1 book here
Balaji S. Srinivasanrecommends 1 book here