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

The scope of longtermism – David Thorstad (Global Priorities Institute, University of Oxford)

Longtermism holds roughly that in many decision situations, the best thing we can do is what is best for the long-term future. The scope question for longtermism asks: how large is the class of decision situations for which longtermism holds? Although longtermism was initially developed to describe the situation of…

A Fission Problem for Person-Affecting Views – Elliott Thornley (Global Priorities Institute, University of Oxford)

On person-affecting views in population ethics, the moral import of a person’s welfare depends on that person’s temporal or modal status. These views typically imply that – all else equal – we’re never required to create extra people, or to act in ways that increase the probability of extra people coming into existence. In this paper, I use Parfit-style fission cases to construct a dilemma for person-affecting views: either they forfeit their seeming-advantages and face fission analogues…

The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists – Elliott Thornley (Global Priorities Institute, University of Oxford)

I explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that…