Given the increasing popularity of Qualitative Comparative Analysis (QCA) for the study of public policy and policy processes, this article offers a review of two key issues: multiple configurational causality and temporality. On the one hand, the study of multiple configurational causal relations allows researchers to deal with the extremely complex set of elements that interact in policy processes. However, this task poses the challenge of balancing deductive and inductive logics in a research design. On the other hand, policy process theories often involve temporal arguments, but QCA does not easily deal with dynamic elements. This article discusses these challenges and proposes several ways to address them. It thereby illustrates the advantages and limitations of QCA for students of policy processes.

Collaboration between actors in political decision-making processes is crucial from both an actor and a process perspective. Previous studies have highlighted the role of preference similarity, power, and opportunity structures as drivers of collaboration. However, these studies have focused on single policy sectors and have therefore overlooked possible differences in effects across sectors, as well as interactions between sectors. This article innovates by taking a cross-sector perspective. Applying exponential random graph models to collaboration networks covering 11 decision-making processes, we show that relational opportunity structures have a fairly consistent influence on collaboration, whereas the effects of social and institutional opportunity structures vary across processes. The effect of institutional opportunity structures is contingent on the importance of institutional arenas. Our hypothesis on cross-sector influences receives partial support. Opportunity structures and interactions betwee...