Why Opposite Errors Do Not Cancel Out Across Cases
Averaging independent estimates of the same object can increase precision because errors may offset one another. But overpricing one policy and underpricing another are two separate mistakes; a correct system-wide average does not undo either consequence.
- Averaging helps when several people judge the same object.
- Opposite errors across different cases remain separate harms.
- Zero average bias can coexist with very poor performance.
- Institutional performance cannot be judged from the average alone.
“if you overprice one policy and you underprice the another policy that doesn't cancel out, you've made two mistakes”
“you can have a zero bias and the very poor performance”