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Causal inference and American political development: common challenges and opportunities

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  • Eric Schickler

    (University of California)

Abstract

The causal inference (CI) movement has forced political scientists to think far more seriously about what can be learned from a particular research design and to be more attentive to making design choices that allow for credible causal inferences. At the same time, the rise of CI has given rise to the concern that political scientists have been better at making particular contributions isolating the effect of a single independent variable than at developing and testing theories that help us understand how these diverse findings fit together. For all of American political development’s (APD’s) distance from the causal inference revolution, a parallel can be drawn between the state of APD today and some of the concerns expressed about the broader state of political science in the wake of the rise of CI. This essay considers ways in which APD and CI can each be enriched through greater mutual engagement, suggesting that one should not dichotomize research into mutually exclusive categories of “well-identified research that makes credible causal claims” and “purely descriptive” APD studies.

Suggested Citation

  • Eric Schickler, 2020. "Causal inference and American political development: common challenges and opportunities," Public Choice, Springer, vol. 185(3), pages 501-511, December.
  • Handle: RePEc:kap:pubcho:v:185:y:2020:i:3:d:10.1007_s11127-019-00690-8
    DOI: 10.1007/s11127-019-00690-8
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