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Getting Practical With Causal Mechanisms: The application of Process‐Tracing Under Real‐World Evaluation Constraints
Author(s) -
Raimondo Estelle
Publication year - 2020
Publication title -
new directions for evaluation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.374
H-Index - 40
eISSN - 1534-875X
pISSN - 1097-6736
DOI - 10.1002/ev.20430
Subject(s) - process tracing , process (computing) , tracing , field (mathematics) , computer science , psychological intervention , causal model , management science , causal inference , impact evaluation , conditional cash transfer , comprehension , process management , politics , psychology , political science , economics , business , econometrics , medicine , poverty , mathematics , pathology , psychiatry , pure mathematics , law , operating system , programming language
Over the past decade, the field of development evaluation has seen a renewed interest in methodological approaches that can answer compelling causal questions about what works, for whom, and why. Development evaluators have notably started to experiment with Bayesian Process Tracing to unpack, test, and enhance their comprehension of causal mechanisms triggered by development interventions. This chapter conveys one such experience of applying Bayesian Process Tracing to the study of citizen engagement interventions within a conditional cash transfer program under real‐world evaluation conditions. The chapter builds on this experience to discuss the benefits, challenges, and potential for the applicability of this approach under real‐world evaluation conditions of time, money, and political constraints.