Estimating long-term treatment effects without long-term outcome data
David Rhys Bernard (Paris School of Economics)
GPI Working Paper No. 11-2020
This paper has been awarded the paper prize of the 2019 Early Career Conference Programme.
Estimating long-term impacts of actions is important in many areas but the key difficulty is that long-term outcomes are only observed with a long delay. One alternative approach is to measure the effect on an intermediate outcome or a statistical surrogate and then use this to estimate the long-term effect. Athey et al. (2019) generalise the surrogacy method to work with multiple surrogates, rather than just one, increasing its credibility in social science contexts. I empirically test the multiple surrogates approach for long-term effect estimation in real-world conditions using long-run RCTs from development economics. In the context of conditional cash transfers for education in Colombia, I find that the method works well for predicting treatment effects over a 5-year time span but poorly over 10 years due to a reduced set of variables available when attempting to predict effects further into the future. The method is sensitive to observing appropriate surrogates.
Other working papers
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Various philosophers accept moral views that are impartial, additive, and risk-neutral with respect to betterness. But, if that risk neutrality is spelt out according to expected value theory alone, such views face a dire reductio ad absurdum. If the expected sum of value in humanity’s future is undefined—if, e.g., the probability distribution over possible values of the future resembles the Pasadena game, or a Cauchy distribution—then those views say that no real-world option is ever better than any other. And, as I argue…
Against Anti-Fanaticism – Christian Tarsney (Population Wellbeing Initiative, University of Texas at Austin)
Should you be willing to forego any sure good for a tiny probability of a vastly greater good? Fanatics say you should, anti-fanatics say you should not. Anti-fanaticism has great intuitive appeal. But, I argue, these intuitions are untenable, because satisfying them in their full generality is incompatible with three very plausible principles: acyclicity, a minimal dominance principle, and the principle that any outcome can be made better or worse. This argument against anti-fanaticism can be…
AI alignment vs AI ethical treatment: Ten challenges – Adam Bradley (Lingnan University) and Bradford Saad (Global Priorities Institute, University of Oxford)
A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching…