Discovering causal pathways to successful protection outcomes
Stian Kjeksrud · 2023
Abstract This chapter explores combinations of conditions—so-called “causal recipes”—that may systematically explain variations in outcomes of UN military protection operations across time and UN missions, applying fuzzy set Qualitative Comparative Analysis (fsQCA) to 126 cases from the UNPOCO dataset. The cases are studied along four conditions frequently identified as causally relevant in existing literature: deterrent presence, willingness to accept risk, pre-emption, and matching. It finds that matching and pre-emption unite in the most promising recipe to explain positive outcomes across cases. Still, many cases remain unexplained, demanding other methods to search for other possible causal conditions, which is performed in later chapters.