Causal Inference: The Mixtape

“Identifying causal effects involves assumptions, but it also requires a particular kind of belief about the work of scientists. Credible and valuable research requires that we believe that it is more important to do our work correctly than to try and achieve a certain outcome (e.g., confirmation bias, statistical significance, stars). The foundations of scientific knowledge are scientific methodologies. Science does not collect evidence in order to prove what we want to be true or what people want others to believe. That is a form of propaganda, not science. Rather, scientific methodologies are devices for forming a particular kind of belief. Scientific methodologies allow us to accept unexpected, and sometimes, undesirable answers. They are process oriented, not outcome oriented. And without these values, causal methodologies are also not credible.”

Causal Inference: The Mixtape by Scott Cunningham, associate professor of economics at Baylor University (oh and there’s an accompanying Spotify playlist)

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Hannah Blackburn

Hannah Blackburn is an associate at IDinsight in Nairobi, Kenya. IDinsight is a non-profit organization that uses a variety of data-driven research methods to help decision makers in the development field maximize their social impact.

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