Difference between revisions of "Goodhart’s Law"
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== Examples == | == Examples == | ||
* The case against [[Leverage Ratio | leverage ratios]] is that they may encourage banks to increase their risk per unit of assets, reducing their usefulness as an indicator of bank failure<ref>The dog and the frisbee, Andrew G Haldane, Vasileios Madouros, Economist, Bank of England, 2012</ref> | * The case against [[Leverage Ratio | leverage ratios]] is that they may encourage banks to increase their risk per unit of assets, reducing their usefulness as an indicator of bank failure<ref>The dog and the frisbee, Andrew G Haldane, Vasileios Madouros, Economist, Bank of England, 2012</ref> | ||
| + | * Indicators may lose their predictive power when relied on for regulatory purposes [[BCBS 258]] | ||
== See Also == | == See Also == | ||
Revision as of 10:52, 4 March 2024
Definition
Goodhart’s Law states that any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes. Alternative expression: When a measure becomes a target, it ceases to be a good measure.
Implications
The fitness of risk models for control purposes may be compromised, i.e., no risk model can take account ex-ante of the ways in which it might be gamed by involved parties.
Similarly, if an economic indicator or index becomes a target for conducting social or economic policy, it will lose the information qualities that qualify it to play such a role in the first place.
Examples
- The case against leverage ratios is that they may encourage banks to increase their risk per unit of assets, reducing their usefulness as an indicator of bank failure[1]
- Indicators may lose their predictive power when relied on for regulatory purposes BCBS 258
See Also
References
- ↑ The dog and the frisbee, Andrew G Haldane, Vasileios Madouros, Economist, Bank of England, 2012
