Learning heuristics, issue salience and polarization in the policy process

Abstract

This article proposes a theory that links issue salience and actor polarisation to the uses of learning heuristics in the policy process. In harking back to research on public policy, behavioural economics, and crisis management, we argue that policy makers use two learning heuristics when they update their policy ideas: policy-oriented learning and power-oriented learning. The article develops theoretical expectations that link issue salience and polarisation of actor constellations to policy-oriented and power-oriented learning. To illustrate the theoretical expectations, the article discusses EU anti-crisis policies dealing with the 2007–2009 global financial and economic crisis and its aftermath, as well as the responses to the COVID-19 pandemic in Germany and the U.S. as pathway cases. Overall, this article contributes to the understanding of learning and the political uses of ideas in the policy process.