Causality is good for practice: policy design and reverse engineering

Abstract

AbstractRelevance to practice is an open issue for scholars in public policy and public administration. One major problem is the need to produce knowledge that can guide practitioners designing and implementing public interventions in specific contexts. This article claims that investigating the causal mechanisms of policy programs—i.e., modeling why and how they produce outcomes—can contribute to such knowledge. In this regard, mechanisms offer essential information to guide practitioners when replicating, adjusting, and designing interventions. Unfortunately, not all models of mechanisms can inform practice. The article proposes a strategy for design research and practice inspired by reverse engineering: selecting successful programs, causal modeling, assessing the target context, and designing. Scholars should model mechanisms by identifying the program and non-program elements that contribute to the outcome of interest and abstracting their causal powers. Practitioners can use these models, diagnose their target context, and adjust designs to deal with context-specific problems. The proposed research agenda may enhance orientation to practice and offer a middle ground between the search for abstract, general relationships, and single-case analyses.