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Causal models and evidential pluralism in econometrics

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  • Alessio Moneta
  • Federica Russo

Abstract

Social research, from economics to demography and epidemiology, makes extensive use of statistical models in order to establish causal relations. The question arises as to what guarantees the causal interpretation of such models. In this paper we focus on econometrics and advance the view that causal models are 'augmented' statistical models that incorporate important causal information which contributes to their causal interpretation. The primary objective of this paper is to argue that causal claims are established on the basis of a plurality of evidence. We discuss the consequences of 'evidential pluralism' in the context of econometric modelling.

Suggested Citation

  • Alessio Moneta & Federica Russo, 2014. "Causal models and evidential pluralism in econometrics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 21(1), pages 54-76, March.
    • Handle: RePEc:taf:jecmet:v:21:y:2014:i:1:p:54-76
    DOI: 10.1080/1350178X.2014.886473
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    Cited by:

    1. Brancaccio, Emiliano & Garbellini, Nadia & Giammetti, Raffaele, 2018. "Structural labour market reforms, GDP growth and the functional distribution of income," Structural Change and Economic Dynamics, Elsevier, vol. 44(C), pages 34-45.
    2. Michael Joffe, 2017. "Causal theories, models and evidence in economics—some reflections from the natural sciences," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1280983-128, January.
    3. Marchionni, Caterina & Reijula, Samuli, 2018. "What is mechanistic evidence, and why do we need it for evidence-based policy?," SocArXiv 4ufbm, Center for Open Science.
    4. Claudius Gräbner, 2017. "The Complementary Relationship Between Institutional and Complexity Economics: The Example of Deep Mechanismic Explanations," Journal of Economic Issues, Taylor & Francis Journals, vol. 51(2), pages 392-400, April.
    5. M. Mouchart & R. Orsi & G. Wunsch, 2020. "Causality in Econometric Modeling. From Theory to Structural Causal Modeling," Working Papers wp1143, Dipartimento Scienze Economiche, Universita' di Bologna.
    6. Leonardo Marinho, 2022. "Causal Impulse Responses for Time Series," Working Papers Series 570, Central Bank of Brazil, Research Department.

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