Causal Inference in Nonprofit Management and Public Administration
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Abstract
The “causal revolution” in the broader social sciences has led to a new field of observational causal inference. However, these advancements have been less used among nonprofit scholars and practitioners. In this article, we provide a methodological guide for applying causal inference tools within nonprofit studies. We walk through practical examples of model-based and design-based approaches from epidemiology and econometrics to observational causal inference, including causal models, inverse probability weighting, difference-in-differences, regression discontinuity, and instrumental variables. We include empirical illustrations of these approaches by replicating existing nonprofit research and program evaluations. We conclude with a call for more careful and explicit attempts at making causal claims in nonprofit studies.