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Goodhart's law

Adage about statistical measures

Goodhart's law

Adage about statistical measures

Note

statistics and government policy

Goodhart's law is an adage that has been stated as, "When a measure becomes a target, it ceases to be a good measure". It is named after British economist Charles Goodhart, who is credited with expressing the core idea of the adage in a 1975 article on monetary policy in the United Kingdom:

It was used to criticize the British Thatcher government for trying to conduct monetary policy on the basis of targets for broad and narrow money, but the law reflects a much more general phenomenon.

Priority and background

Charles Goodhart, for whom the adage is named, delivering a speech in 2012

Numerous concepts are related to this idea, at least one of which predates Goodhart's statement. Notably, Campbell's law likely has precedence, as Jeff Rodamar has argued, since various formulations date to 1969. Other academics had similar insights at the time. Jerome Ravetz's 1971 book Scientific Knowledge and Its Social Problems also predates Goodhart, though it does not formulate the same law. Ravetz discusses how systems in general can be gamed, focusing on cases where the goals of a task are complex, sophisticated, or subtle. In such cases, the persons possessing the skills to execute the tasks properly seek their own goals to the detriment of the assigned tasks. When the goals are instantiated as metrics, this could be seen as equivalent to Goodhart and Campbell's claim.

Shortly after Goodhart's publication, others suggested closely related ideas, including the Lucas critique (1976). As applied in economics, the law is also implicit in the idea of rational expectations, a theory in economics that states that those who are aware of a system of rewards and punishments will optimize their actions within that system to achieve their desired results. For example, if an employee is rewarded by the number of cars sold each month, they will try to sell more cars, even at a loss.

While it originated in the context of market responses, the law has profound implications for the selection of high-level targets in organizations. Jon Danielsson states the law as

And suggested a corollary for use in financial risk modelling:

Mario Biagioli related the concept to consequences of using citation impact measures to estimate the importance of scientific publications:

Generalization

Later writers generalized Goodhart's point about monetary policy into a more general adage about measures and targets in accounting and evaluation systems. In a book chapter published in 1996, Keith Hoskin wrote:

In a 1997 paper on the misuse of accountability models in education, anthropologist Marilyn Strathern cited Hoskins expressing Goodhart's Law as "When a measure becomes a target, it ceases to be a good measure", and linked the sentiment to the history of accountability stretching back into Britain in the 1800s:

Examples

  • The San Francisco Declaration on Research Assessment denounces several problems in science and as Goodhart's law explains, one of them is that measurement has become a target. The correlation between h-index and scientific awards is decreasing since widespread usage of h-index.
  • The International Union for Conservation of Nature's (IUCN) measure of extinction can be used to remove environmental protections, which resulted in IUCN becoming more conservative in labeling something as extinct.
  • In healthcare, the misapplication of metrics can lead to adverse outcomes. For instance, hospitals striving to reduce length of stay (LOS) may inadvertently discharge patients prematurely, leading to increased emergency readmissions.
  • According to Tom and David Chivers in How to Read Numbers, the law applied to the British government response to the COVID-19 pandemic when it announced a target of 100,000 COVID-19 tests per day—initially a target for tests actually carried out and later for maximum capacity of test-taking. The number of useful diagnostic tests was far lower than the government-reported number when it announced it had met the target.

References

References

  1. Goodhart, Charles. (1975). "Problems of Monetary Management: The UK Experience". Reserve Bank of Australia.
  2. Goodhart, Charles. (1975). "Problems of Monetary Management: The UK Experience". Barnes and Noble Books.
  3. (1987). "The Rise And Fall of Monetarism". [[Penguin Books]].
  4. (2018). "Categorizing Variants of Goodhart's Law".
  5. Manheim, David. (29 September 2016). "Overpowered Metrics Eat Underspecified Goals".
  6. Rodamar, Jeffery. (28 November 2018). "There ought to be a law! Campbell versus Goodhart". Significance.
  7. Ravetz, Jerome R.. (1971). "Scientific knowledge and its social problems". Transaction Publishers.
  8. Daníelsson, Jón. (July 2002). "The Emperor has no Clothes: Limits to Risk Modelling". Journal of Banking & Finance.
  9. Biagioli, Mario. (12 July 2016). "Watch out for cheats in citation game". Nature.
  10. (30 December 2014). "Editorial statement: Lessons from Goodhart's law for the management of the journal". European Journal of Government and Economics.
  11. Hoskin, Keith. (1996). "The 'awful idea of accountability': inscribing people into the measurement of objects".
  12. Strathern, Marilyn. (1997). "'Improving ratings': audit in the British University system". [[Wiley (publisher).
  13. (2021). "The h-index is no longer an effective correlate of scientific reputation.". PLOS ONE.
  14. Mooers, Arne. (2022-05-23). "When is a species really extinct?".
  15. (March 2023). "'Lost' taxa and their conservation implications". Animal Conservation.
  16. Babar, Sultan M.. (2023-11-08). "The Cobra Effect in Healthcare: Goodhart's Law and the Pitfalls of Misguided Metrics".
  17. (2021). "[[How to Read Numbers]]". [[Weidenfeld & Nicolson]].
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