Gary King and Langche Zeng. 2008. "Empirical versus
Theoretical Claims about Extreme Counterfactuals: A Response,"
Political Analysis, Vol. 17 (2009): Pp. 107-112.
DOI:10.1093/pan/mpn010,
http://gking.harvard.edu/files/abs/cfr-abs.shtml (Article: PDF | Oxford University Press: Abstract,
Full Text,
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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.
See also related research on Causal
inference.