The Conservation Multiplier
Bård Harstad (University of Oslo)
GPI Working Paper No. 13 - 2022, published in Journal of Political Economy
Every government that controls an exhaustible resource must decide whether to exploit it or to conserve and thereby let the subsequent government decide whether to exploit or conserve. This paper develops a positive theory of this situation and shows when a small change in parameter values has a multiplier effect on exploitation. The multiplier strengthens the influence of a lobby paying for exploitation, and of a donor compensating for conservation. A successful donor pays every period for each unit; a successful lobby pays once. This asymmetry causes inefficient exploitation. A normative analysis uncovers when compensations are optimally offered to the party in power, to the general public, or to the lobby.
Other working papers
Future Suffering and the Non-Identity Problem – Theron Pummer (University of St Andrews)
I present and explore a new version of the Person-Affecting View, according to which reasons to do an act depend wholly on what would be said for or against this act from the points of view of particular individuals. According to my view, (i) there is a morally requiring reason not to bring about lives insofar as they contain suffering (negative welfare), (ii) there is no morally requiring reason to bring about lives insofar as they contain happiness (positive welfare), but (iii) there is a permitting reason to bring about lives insofar as they…
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. …
Imperfect Recall and AI Delegation – Eric Olav Chen (Global Priorities Institute, University of Oxford), Alexis Ghersengorin (Global Priorities Institute, University of Oxford) and Sami Petersen (Department of Economics, University of Oxford)
A principal wants to deploy an artificial intelligence (AI) system to perform some task. But the AI may be misaligned and aim to pursue a conflicting objective. The principal cannot restrict its options or deliver punishments. Instead, the principal is endowed with the ability to impose imperfect recall on the agent. The principal can then simulate the task and obscure whether it is real or part of a test. This allows the principal to screen misaligned AIs during testing and discipline their behaviour in deployment. By increasing the…