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

AI alignment vs AI ethical treatment: Ten challenges – Adam Bradley (Lingnan University) and Bradford Saad (Global Priorities Institute, University of Oxford)

A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching…

Existential risk and growth – Leopold Aschenbrenner (Columbia University)

Human activity can create or mitigate risks of catastrophes, such as nuclear war, climate change, pandemics, or artificial intelligence run amok. These could even imperil the survival of human civilization. What is the relationship between economic growth and such existential risks? In a model of directed technical change, with moderate parameters, existential risk follows a Kuznets-style inverted U-shape. …