Evidential variety as a source of credibility for causal inference: beyond sharp designs and structural models
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Journal of Economic Methodology 18 (3):233-253 (2011)
There is an ongoing debate in economics between the design-based approach and the structural approach. The main locus of contention regards how best to pursue the quest for credible causal inference. Each approach emphasizes one element ? sharp study designs versus structural models ? but these elements have well-known limitations. This paper investigates where a researcher might look for credibility when, for the causal question under study, these limitations are binding. It argues that seeking variety of evidence ? understood specifically as using multiple means of determination to robustly estimate the same causal effect ? constitutes such an alternative and that applied economists actually take advantage of it. Evidential variety is especially relevant for a class of macro-level causal questions for which the design-based and the structural approaches appear to have limited reach. The use of evidential variety is illustrated by drawing on the literature on the institutional determinants of the aggregate unemployment rate.
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References found in this work BETA
John Aldrich (2006). When Are Inferences Too Fragile to Be Believed? Journal of Economic Methodology 13 (2):161-177.
William Bechtel (2005). Explanation: A Mechanist Alternative. Studies in History and Philosophy of Biol and Biomed Sci 36 (2):421--441.
Luc Bovens & Stephan Hartmann (2003). Bayesian Epistemology. Oxford: Oxford University Press.
Sylvia Culp (1994). Defending Robustness: The Bacterial Mesosome as a Test Case. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:46 - 57.
Sylvia Culp (1995). Objectivity in Experimental Inquiry: Breaking Data-Technique Circles. Philosophy of Science 62 (3):438-458.
Citations of this work BETA
François Claveau (2012). The Russo–Williamson Theses in the Social Sciences: Causal Inference Drawing on Two Types of Evidence. Studies in History and Philosophy of Science Part C 43 (4):806-813.
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