Philosophical Attitudes Toward Causal Inference in Statistics and Responses from Econometrics

Investigate whether statisticians historically held explicit or implicit philosophical positions that resisted the possibility of causal inference; identify philosophical views developed by practitioners of causal inference in response; determine what would constitute an adequate philosophical response to statisticians’ resistance.

Background

The paper notes that causal inference was long viewed skeptically within mainstream statistics, while econometrics embraced the potential outcomes framework (Rubin 1974), culminating in recognition by the 2021 Nobel Prize in Economics. This raises questions about the philosophical stances that may have underpinned statistical skepticism and the counter-positions articulated by causal inference practitioners.

Addressing this would bridge historical practice with philosophical analysis, clarifying the conceptual foundations of causal inference across disciplines.

References

Open Question III (from Econometrics). While statisticians had been largely dismissive about causal inference throughout most of the history of statistics, the 2021 Nobel Prize in Economics recognized a theory of causal inference—the potential outcomes framework—which had its early development (Rubin 1974) much better received in econometrics rather than in statistics. Was there a philosophical view, held either explicitly or implicitly by some statisticians at the time, that resisted the very possibility of causal inference? Did practitioners of causal inference develop any philosophical views in response? Or what would constitute a good response?

— A Plea for History and Philosophy of Statistics and Machine Learning (2506.22236 - Lin, 27 Jun 2025) in Section 9 (Closing): Open Question III (from Econometrics)