IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v56y2022i4d10.1007_s11135-021-01190-y.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-021-01190-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-021-01190-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    2. Eva Thomann & Martino Maggetti, 2020. "Designing Research With Qualitative Comparative Analysis (QCA): Approaches, Challenges, and Tools," Sociological Methods & Research, , vol. 49(2), pages 356-386, May.
    3. Michael Baumgartner & Alrik Thiem, 2020. "Often Trusted but Never (Properly) Tested: Evaluating Qualitative Comparative Analysis," Sociological Methods & Research, , vol. 49(2), pages 279-311, May.
    4. Ragin, Charles C., 2000. "Fuzzy-Set Social Science," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226702773, September.
    5. Rodrigo Barrenechea & James Mahoney, 2019. "A Set-Theoretic Approach to Bayesian Process Tracing," Sociological Methods & Research, , vol. 48(3), pages 451-484, August.
    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.
    8. Thiem, Alrik, 2016. "Standards of Good Practice and the Methodology of Necessary Conditions in Qualitative Comparative Analysis," Political Analysis, Cambridge University Press, vol. 24(4), pages 478-484.
    9. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
    10. repec:ucp:bkecon:9780226702766 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martyna Daria Swiatczak, 2022. "Different algorithms, different models," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 1913-1937, August.
    2. Tim Haesebrouck & Eva Thomann, 2022. "Introduction: Causation, inferences, and solution types in configurational comparative methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 1867-1888, August.
    3. Filippopoulos, Nikolaos & Fotopoulos, Georgios, 2022. "Innovation in economically developed and lagging European regions: A configurational analysis," Research Policy, Elsevier, vol. 51(2).
    4. Michael Baumgartner, 2022. "Qualitative Comparative Analysis and robust sufficiency," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 1939-1963, August.
    5. Judith Glaesser, 2023. "Limited diversity and QCA solution types: assumptions and their consequences," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3485-3497, August.
    6. Borozan, Dj, 2022. "Detecting a structure in the European energy transition policy instrument mix: What mix successfully drives the energy transition?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    7. Paul Lichterman & Isaac Ariail Reed, 2015. "Theory and Contrastive Explanation in Ethnography," Sociological Methods & Research, , vol. 44(4), pages 585-635, November.
    8. Adel Daoud, 2020. "The wealth of nations and the health of populations: A quasi-experimental design of the impact of sovereign debt crises on child mortality," Papers 2012.14941, arXiv.org.
    9. Nicholas Weller & Jeb Barnes, 2016. "Pathway Analysis and the Search for Causal Mechanisms," Sociological Methods & Research, , vol. 45(3), pages 424-457, August.
    10. James Mahoney & Andrew Owen, 2022. "Importing set-theoretic tools into quantitative research: the case of necessary and sufficient conditions," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2001-2022, August.
    11. James J. Heckman & Rodrigo Pinto, 2022. "Causality and Econometrics," NBER Working Papers 29787, National Bureau of Economic Research, Inc.
    12. Manabu Kuroki, 2016. "The Identification of Direct and Indirect Effects in Studies with an Unmeasured Intermediate Variable," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 228-245, March.
    13. Lisa Capretti, 2023. "Technology adoption constraints and Laser Land Levelling: evidence from Karnataka, India," Working Papers 1/23, Sapienza University of Rome, DISS.
    14. Ali Tafti & Galit Shmueli, 2020. "Beyond Overall Treatment Effects: Leveraging Covariates in Randomized Experiments Guided by Causal Structure," Information Systems Research, INFORMS, vol. 31(4), pages 1183-1199, December.
    15. Alrik Thiem, 2022. "Beyond the Facts: Limited Empirical Diversity and Causal Inference in Qualitative Comparative Analysis," Sociological Methods & Research, , vol. 51(2), pages 527-540, May.
    16. Russo, Ivan & Confente, Ilenia, 2019. "From dataset to qualitative comparative analysis (QCA)—Challenges and tricky points: A research note on contrarian case analysis and data calibration," Australasian marketing journal, Elsevier, vol. 27(2), pages 129-135.
    17. Douglas, Evan J. & Shepherd, Dean A. & Prentice, Catherine, 2020. "Using fuzzy-set qualitative comparative analysis for a finer-grained understanding of entrepreneurship," Journal of Business Venturing, Elsevier, vol. 35(1).
    18. Eva Thomann & Martino Maggetti, 2020. "Designing Research With Qualitative Comparative Analysis (QCA): Approaches, Challenges, and Tools," Sociological Methods & Research, , vol. 49(2), pages 356-386, May.
    19. James J. Heckman & Rodrigo Pinto, 2023. "Econometric Causality: The Central Role of Thought Experiments," NBER Working Papers 31945, National Bureau of Economic Research, Inc.
    20. Tim Haesebrouck, 2019. "An alternative update of the two-step QCA procedure," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(6), pages 2765-2780, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:56:y:2022:i:4:d:10.1007_s11135-021-01190-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.