Empirical versus Theoretical Claims about Extreme Counterfactuals: A Response

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Empirical versus Theoretical Claims about Extreme Counterfactuals: A Response

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Title: Empirical versus Theoretical Claims about Extreme Counterfactuals: A Response
Author: King, Gary ORCID  0000-0002-5327-7631 ; Zeng, Langche

Note: Order does not necessarily reflect citation order of authors.

Citation: King, Gary, and Langche Zeng. 2009. Empirical versus theoretical claims about extreme counterfactuals: A response. Political Analysis 17(1): 107-112.
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Research Data: http://hdl.handle.net/1902.1/11903
Abstract: In response to the data-based measures of model dependence proposed in King and Zeng (2006), Sambanis and Michaelides (2008) propose alternative measures that rely upon assumptions untestable in observational data. If these assumptions are correct, then their measures are appropriate and ours, based solely on the empirical data, may be too conservative. If instead, and as is usually the case, the researcher is not certain of the precise functional form of the data generating process, the distribution from which the data are drawn, and the applicability of these modeling assumptions to new counterfactuals, then the data-based measures proposed in King and Zeng (2006) are much preferred. After all, the point of model dependence checks is to verify empirically, rather than to stipulate by assumption, the effects of modeling assumptions on counterfactual inferences.
Published Version: doi:10.1093/pan/mpn010
Other Sources: http://j.mp/1AzKERk
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4215043
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