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

On two arguments for Fanaticism – Jeffrey Sanford Russell (University of Southern California)

Should we make significant sacrifices to ever-so-slightly lower the chance of extremely bad outcomes, or to ever-so-slightly raise the chance of extremely good outcomes? Fanaticism says yes: for every bad outcome, there is a tiny chance of of extreme disaster that is even worse, and for every good outcome, there is a tiny chance of an enormous good that is even better.

Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)

Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …

Existential Risk and Growth – Leopold Aschenbrenner and Philip Trammell (Global Priorities Institute and Department of Economics, University of Oxford)

Technology increases consumption but can create or mitigate existential risk to human civilization. Though accelerating technological development may increase the hazard rate (the risk of existential catastrophe per period) in the short run, two considerations suggest that acceleration typically decreases the risk that such a catastrophe ever occurs. First, acceleration decreases the time spent at each technology level. Second, given a policy option to sacrifice consumption for safety, acceleration motivates greater sacrifices…