Estimating long-term treatment effects without long-term outcome data
David Rhys Bernard (Rethink Priorities), Jojo Lee and Victor Yaneng Wang (Global Priorities Institute, University of Oxford)
GPI Working Paper No. 13-2023
The surrogate index method allows policymakers to estimate long-run treatment effects before long-run outcomes are observable. We meta-analyse this approach over nine long-run RCTs in development economics, comparing surrogate estimates to estimates from actual long-run RCT outcomes. We introduce the M-lasso algorithm for constructing the surrogate approach’s first-stage predictive model and compare its performance with other surrogate estimation methods. Across methods, we find a negative bias in surrogate estimates. For the M-lasso method, in particular, we investigate reasons for this bias and quantify significant precision gains. This provides evidence that the surrogate index method incurs a bias-variance trade-off.
Other working papers
How much should governments pay to prevent catastrophes? Longtermism’s limited role – Carl Shulman (Advisor, Open Philanthropy) and Elliott Thornley (Global Priorities Institute, University of Oxford)
Longtermists have argued that humanity should significantly increase its efforts to prevent catastrophes like nuclear wars, pandemics, and AI disasters. But one prominent longtermist argument overshoots this conclusion: the argument also implies that humanity should reduce the risk of existential catastrophe even at extreme cost to the present generation. This overshoot means that democratic governments cannot use the longtermist argument to guide their catastrophe policy. …
Numbers Tell, Words Sell – Michael Thaler (University College London), Mattie Toma (University of Warwick) and Victor Yaneng Wang (Massachusetts Institute of Technology)
When communicating numeric estimates with policymakers, journalists, or the general public, experts must choose between using numbers or natural language. We run two experiments to study whether experts strategically use language to communicate numeric estimates in order to persuade receivers. In Study 1, senders communicate probabilities of abstract events to receivers on Prolific, and in Study 2 academic researchers communicate the effect sizes in research papers to government policymakers. When…
Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Paris School of Economics)
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. …