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
Crying wolf: Warning about societal risks can be reputationally risky – Lucius Caviola (Global Priorities Institute, University of Oxford) et al.
Society relies on expert warnings about large-scale risks like pandemics and natural disasters. Across ten studies (N = 5,342), we demonstrate people’s reluctance to warn about unlikely but large-scale risks because they are concerned about being blamed for being wrong. In particular, warners anticipate that if the risk doesn’t occur, they will be perceived as overly alarmist and responsible for wasting societal resources. This phenomenon appears in the context of natural, technological, and financial risks…
AI takeover and human disempowerment – Adam Bales (Global Priorities Institute, University of Oxford)
Some take seriously the possibility of AI takeover, where AI systems seize power in a way that leads to human disempowerment. Assessing the likelihood of takeover requires answering empirical questions about the future of AI technologies and the context in which AI will operate. In many cases, philosophers are poorly placed to answer these questions. However, some prior questions are more amenable to philosophical techniques. What does it mean to speak of AI empowerment and human disempowerment? …
Cassandra’s Curse: A second tragedy of the commons – Philippe Colo (ETH Zurich)
This paper studies why scientific forecasts regarding exceptional or rare events generally fail to trigger adequate public response. I consider a game of contribution to a public bad. Prior to the game, I assume contributors receive non-verifiable expert advice regarding uncertain damages. In addition, I assume that the expert cares only about social welfare. Under mild assumptions, I show that no information transmission can happen at equilibrium when the number of contributors…