🤖 AI Summary
This study addresses the absence of a systematic framework in empirical economics for translating analytical findings into normative policy recommendations. Integrating statistical decision theory with the literature on policy choice, the authors develop a unified analytical framework and introduce two types of navigational maps to guide research design. They also implement an R package that automatically generates standardized, publication-ready visualizations of policy impacts. Demonstrated through applications in development economics, this approach substantially enhances the transparency, cross-study comparability, and empirical grounding of policy advice, thereby offering the first end-to-end methodological pipeline that bridges theoretical analysis and practical policy evaluation.
📝 Abstract
Applied research in economics is intrinsically motivated by broad normative objectives. However, it is not obvious how a researcher should direct their efforts to produce evidence toward such objectives. This paper reviews recent theoretical developments on research design for policy choice and provides new tools applied researchers can use to guide their design choices and communicate their policy recommendations. First, I focus on theoretical contributions in econometrics and provide a general framework that nests all the contexts and results reviewed using a coherent notation and narrative. Then, I present two diagrams applied researchers can use to navigate the theoretical literature starting from concrete scenarios to make thoughtful design choices. Finally, I introduce a new R package that produces one table and two figures applied researchers can plug in their `policy implications' section to provide evidence on the performance of different policy recommendations coming out of their study. The use of such tools is illustrated with an example in development economics.