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Suppes’ probabilistic theory of causality and causal inference in economics

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  • Julian Reiss

Abstract

This paper examines Patrick Suppes’ probabilistic theory of causality understood as a theory of causal inference, and draws some lessons for empirical economics and contemporary debates in the foundations of econometrics. It argues that a standard method of empirical economics, multiple regression, is inadequate for most but the simplest applications, that the Bayes’ nets approach, which can be understood as a generalisation of Suppes’ theory, constitutes a considerable improvement but is still subject to important limitations, and that the currently fashionable ‘design-based approach’ suffers from the same flaws Suppes anticipated a long time ago. It then sketches an alternative in response, one that differs drastically from the formalisms Suppes endorsed but is consistent with his pragmatic general take on science.

Suggested Citation

  • Julian Reiss, 2016. "Suppes’ probabilistic theory of causality and causal inference in economics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 23(3), pages 289-304, July.
  • Handle: RePEc:taf:jecmet:v:23:y:2016:i:3:p:289-304
    DOI: 10.1080/1350178X.2016.1189127
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    Cited by:

    1. Nasir, Muhammad Ali & Morgan, Jamie, 2023. "Paradox of stationarity? A policy target dilemma for policymakers," The Quarterly Review of Economics and Finance, Elsevier, vol. 87(C), pages 142-145.

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