Causal Inference and Austrian Economics

Kevin Grier

A chapter in Contemporary Methods and Austrian Economics, 2022, vol. 26, pp 105-114 from Emerald Group Publishing Limited

Abstract: 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.

Keywords: Causal inference; Austrian Economics; counterfactual reasoning; synthetic control; regression discontinuity; difference in differences (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aaeczz:s1529-213420220000026007

DOI: 10.1108/S1529-213420220000026007

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