It is a well-known predicament of the social sciences that predictions can sometimes intervene on the very processes the predictions concern. The purpose of this paper is to address the question of how modelers or scientists should act in the presence of such performative effects with a specific focus on the example of climate economics. Specifically, we will argue that two strategies for managing performative effects recently defended in the literature (i.e., mitigating and appraisal) will not be adequate for all cases because we often lack the knowledge to execute them properly. We will focus on the use of so-called integrated assessment models (IAMs) in climate policy, where the policy process spans large time-horizons and heavily depends on a diverse set of social actors. For cases like this, we argue that we should do neither mitigating nor appraisal and propose that it can be adequate to act as if one does not anticipate any performative effects.
Beck et al. (Fri,) studied this question.