One thing to note about the bounds of the FP cost-effectiveness estimate is that they aren’t equivalent to a 95% confidence interval. Instead they’ve been calculated by multiplying through the most extreme plausible values for each variable on our cost-effectiveness calculation. This means they correspond to an absolute, unimaginably bad worst case scenario and an absolute, unfathomably good best case scenario. We understand that this is far from ideal: first, cost-effectiveness estimates that span 6+ orders of magnitude aren’t that helpful for cause prioritization; second, they probably overrepresent our actual uncertainty.
On TaRL specifically, the effects seem really good—whether or not we can get governments to implement TaRL effectively seems to be where most of the uncertainty lies.
@smclare Thanks for giving some background on the Founders Pledge cost-effectiveness scenarios. For TaRL, I’m surprised that you say that the optimistic scenario is the unfathomably best case scenario. Even in that scenario, impacts are assumed to last 20 years, and the impact of test scores improvements on earnings does not use the most optimistic cases mentioned in the Founders Pledge education report. It seems fathomable impacts could last a whole career (say 40 years). As you can see from my cost-effectiveness estimates for TaRL, my unfathomably best case scenario is significantly more optimistic than the one from Founders Pledge (I included in the cost-effectiveness spreadsheet a worksheet using the worksheet from Founders Pledge as a starting point, but with my own scenarios in there). And in both cases, we only include the impact on income. It seems quite plausible that education would have impacts beyond that which aren’t taken into account.
One thing to note about the bounds of the FP cost-effectiveness estimate is that they aren’t equivalent to a 95% confidence interval. Instead they’ve been calculated by multiplying through the most extreme plausible values for each variable on our cost-effectiveness calculation. This means they correspond to an absolute, unimaginably bad worst case scenario and an absolute, unfathomably good best case scenario. We understand that this is far from ideal: first, cost-effectiveness estimates that span 6+ orders of magnitude aren’t that helpful for cause prioritization; second, they probably overrepresent our actual uncertainty.
On TaRL specifically, the effects seem really good—whether or not we can get governments to implement TaRL effectively seems to be where most of the uncertainty lies.
@smclare Thanks for giving some background on the Founders Pledge cost-effectiveness scenarios. For TaRL, I’m surprised that you say that the optimistic scenario is the unfathomably best case scenario. Even in that scenario, impacts are assumed to last 20 years, and the impact of test scores improvements on earnings does not use the most optimistic cases mentioned in the Founders Pledge education report. It seems fathomable impacts could last a whole career (say 40 years). As you can see from my cost-effectiveness estimates for TaRL, my unfathomably best case scenario is significantly more optimistic than the one from Founders Pledge (I included in the cost-effectiveness spreadsheet a worksheet using the worksheet from Founders Pledge as a starting point, but with my own scenarios in there). And in both cases, we only include the impact on income. It seems quite plausible that education would have impacts beyond that which aren’t taken into account.