The Inferential Opportunity of Specificity: How Institutional and Historical Detail Can Enable Causal Explanations and Inference

Corrine McConnaughy ()
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Corrine McConnaughy: Princeton University

A chapter in Causal Inference and American Political Development, 2024, pp 41-60 from Springer

Abstract: Abstract This chapter takes up the context-specificity of the research field of American Political Development (APD), especially fertile ground, for empirical assessment of causal explanations of politics using observational data. Despite an ongoing—though diminishing—quantitative-qualitative divide in political science scholarship, notable agreement has emerged across that divide on the imperative for “rich theories” with multiple implications in the assessment of causal arguments when experimentation is impossible. Drawing on the underlying logic of that agreement, I consider how and why APD can both benefit from and add value to the use of design-based quantitative approaches developed within the potential-outcomes framework for causal inference. Among the central considerations are the limits on direct assessment of historical macro-level causal hypotheses and the imperative for multilevel and context-specific theorizing to enable informative empirical analyses. Also considered is the value of rigorous qualitative work to justify assumptions and measurement strategies in quantitative causal inference analyses. Illustrations of the advocated multiple-implication, multiple-method approaches are drawn from my previous work on the development of woman suffrage in the United States. That integrative approach suggests the benefit of continued development of broader toolkits for explanation of complex, contingent, and endogenous political processes.

Keywords: Causal inference; Potential outcomes; Process tracing; Political dynamics; Suffrage; Voting rights (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:stpchp:978-3-031-74913-1_3

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DOI: 10.1007/978-3-031-74913-1_3

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