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dc.contributor.author	King, Gary
dc.contributor.author	Zeng, Langche
dc.date.accessioned	2010-06-14T18:36:08Z
dc.date.issued	2006
dc.identifier.citation	King, Gary, and Langche Zeng. 2006. The dangers of extreme counterfactuals. Political Analysis 14(2): 131-159.	en_US
dc.identifier.issn	1047-1987	en_US
dc.identifier.uri	http://nrs.harvard.edu/urn-3:HUL.InstRepos:4215040
dc.description.abstract	We address the problem that occurs when inferences about counterfactuals -- predictions, "what if" questions, and causal effects -- are attempted far from the available data. The danger of these extreme counterfactuals is that substantive conclusions drawn from statistical models that fit the data well turn out to be based largely on speculation hidden in convenient modeling assumptions that few would be willing to defend. Yet existing statistical strategies provide few reliable means of identifying extreme counterfactuals. We offer a proof that inferences farther from the data are more model-dependent, and then develop easy-to-apply methods to evaluate how model-dependent our answers would be to specified counterfactuals. These methods require neither sensitivity testing over specified classes of models nor evaluating any specific modeling assumptions. If an analysis fails the simple tests we offer, then we know that substantive results are sensitive to at least some modeling choices that are not based on empirical evidence.	en_US
dc.description.sponsorship	Government	en_US
dc.language.iso	en_US	en_US
dc.publisher	Oxford University Press	en_US
dc.relation.isversionof	doi:10.1093/pan/mpj004	en_US
dash.license	LAA
dc.title	The Dangers of Extreme Counterfactuals	en_US
dc.type	Journal Article	en_US
dc.description.version	Version of Record	en_US
dc.relation.journal	Political Analysis -Ann Arbor then Oxford-	en_US
dash.depositing.author	King, Gary
dc.date.available	2010-06-14T18:36:08Z

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  Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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