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A regularity theory of causality for the social sciences

Author

Listed:
  • James Mahoney

    (Northwestern University)

  • Laura Acosta

    (Northwestern University)

Abstract

This article discusses a regularity theory of causality (RTC) for the social sciences. With RTC, causality is a relationship between X and Y characterized by three features: (1) temporal order; (2) spatiotemporal connection; and (3) constant conjunction. The article discusses each of these three features, situating them within work in the social sciences. The article explores how scholars in the fields of comparative-historical analysis (CHA) and qualitative comparative analysis (QCA) implicitly understand causality in terms of these three features. Special attention is focused on the concern of CHA with methods for establishing the spatiotemporal connection between cause and outcome. Likewise, special attention is focused on the concern of QCA with establishing constant conjunction in the form of non-spurious regularities. The article compares RTC with two other theories of causality: causal power theories, which focus on the activation of entities with generative capacities, and counterfactual theories, which view individual causes as difference-makers for outcomes. The article concludes with a call for scholars in the social sciences who implicitly use RTC to begin to do so explicitly and more self-consciously.

Suggested Citation

  • James Mahoney & Laura Acosta, 2022. "A regularity theory of causality for the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 1889-1911, August.
    • Handle: RePEc:spr:qualqt:v:56:y:2022:i:4:d:10.1007_s11135-021-01190-y
    DOI: 10.1007/s11135-021-01190-y
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    References listed on IDEAS

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    1. Imai, Kosuke & Keele, Luke & Tingley, Dustin & Yamamoto, Teppei, 2011. "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies," American Political Science Review, Cambridge University Press, vol. 105(4), pages 765-789, November.
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    6. Glynn, Adam N. & Quinn, Kevin M., 2011. "Why Process Matters for Causal Inference," Political Analysis, Cambridge University Press, vol. 19(3), pages 273-286, July.
    7. Schneider, Carsten Q., 2018. "Realists and Idealists in QCA," Political Analysis, Cambridge University Press, vol. 26(2), pages 246-254, April.
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    Cited by:

    1. Dul, Jan, 2024. "A different causal perspective with Necessary Condition Analysis," Journal of Business Research, Elsevier, vol. 177(C).

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