Politicians under Radical Uncertainty: How Uncertain Phenomena Influence Political Elites' Behavior

Political elites-political representatives who can take binding decisions, e.g. ministers, parliamentarians, local politicians-face numerous radically uncertain phenomena, from Covid-19 to the long-term effects of Brexit. Radical uncertainty is characterized by manifold unknowns, ambiguity and vagueness, and it differs fundamentally from resolvable uncertainty, those situations in which it is possible to assign probabilities to outcomes, like the electoral consequences of welfare retrenchment. RADIUNCE will explore how these phenomena influence political elites' behavior. Do they "avoid" uncertainty, as some did with the coronavirus; use rules of thumb, "heuristics", e.g. comparing Covid-19 to the flu; or display other behavioral responses? Answering this is urgent: different responses have different outcomes that may impact how representative democracies function and how effective they are at solving problems. For example, avoiding a virus may cost lives, while using heuristics may result in faulty courses of action. RADIUNCE's aim is to develop a theoretical model of how political elites respond to both radically and resolvably uncertain phenomena. We will focus on four countries with different institutional opportunities and constraints for responding to uncertainty: Germany, the Netherlands, the United Kingdom and the United States, 1996-2021. The model will be multidisciplinary, integrating insights from political science, behavioral economics, decision theory, psychology and public administration. We will collect new, unique comparative data from politicians through an innovative combination of automated text analysis and survey experiments. Taking a multimethods approach, we will integrate quantitative data with qualitative methods (process tracing, Qualitative Comparative Analysis, interviews). The new model will explain how political elites respond to the challenges and opportunities in our face-pace world from digitalization to Covid-19 to migration.