Prediction: The long and short of it
Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)
GPI Working Paper No. 7-2020, published in American Economic Journal: Microeconomics
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. So what is the relative importance of short- and long-run predictability? We study this question in a model of rational dynamic adjustment to a changing environment. Even if adjustment costs, discount factors, and long-run uncertainty are large, short-run predictability can be much more important than long-run predictability.
Other working papers
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. …
Against Willing Servitude: Autonomy in the Ethics of Advanced Artificial Intelligence – Adam Bales (Global Priorities Institute, University of Oxford)
Some people believe that advanced artificial intelligence systems (AIs) might, in the future, come to have moral status. Further, humans might be tempted to design such AIs that they serve us, carrying out tasks that make our lives better. This raises the question of whether designing AIs with moral status to be willing servants would problematically violate their autonomy. In this paper, I argue that it would in fact do so.
Aggregating Small Risks of Serious Harms – Tomi Francis (Global Priorities Institute, University of Oxford)
According to Partial Aggregation, a serious harm can be outweighed by a large number of somewhat less serious harms, but can outweigh any number of trivial harms. In this paper, I address the question of how we should extend Partial Aggregation to cases of risk, and especially to cases involving small risks of serious harms. I argue that, contrary to the most popular versions of the ex ante and ex post views, we should sometimes prevent a small risk that a large number of people will suffer serious harms rather than prevent…