Causal inference and austrian economics

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations


In this chapter, the author argues that Austrians are perhaps uniquely placed to be effective practitioners of causal inference techniques on observational data. This is because, while the methods are easy to implement, their validity and value lies in a detailed, “analytical/historical” narrative to accompany the findings. This is true for several reasons. (1) all the models have identifying assumptions (e.g., no spillovers and parallel trends) that are best addressed by an exposition of the institutional/economic/historical milieu in place before and after the treatment under study; (2) determination of external validity also requires detailed institutional and historical knowledge; and (3) researchers often want to know the mechanisms producing the reduced form result that comes out of most causal inference studies. Here again, institutional and historical learning is crucial. My conclusion is that Austrians should add the tools of causal inference with observational data to their arsenal of analysis. This would be good both for their publication prospects and for the profession at large.

Original languageEnglish
Title of host publicationAdvances in Austrian Economics
PublisherEmerald Group Holdings Ltd.
Number of pages10
StatePublished - 2022

Publication series

NameAdvances in Austrian Economics
ISSN (Print)1529-2134


  • Austrian Economics
  • Causal inference
  • Counterfactual reasoning
  • Difference in differences
  • Regression discontinuity
  • Synthetic control


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