Empirical versus Theoretical Claims about Extreme Counterfactuals: A Response

Langche ZengDepartment of Political Science, University of California, San Diego, La Jolla, CA 92093 e-mail: lazeng{at}ucsd.edu In response to the data-based measures of model dependence proposedin King and Zeng (2006), Sambanis and Michaelides (2008) proposealternative measures that rely upon assumptions untestable inobservational data. If these assumptions are correct, then theirmeasures are appropriate and ours, based solely on the empiricaldata, may be too conservative. If instead, and as is usuallythe case, the researcher is not certain of the precise functionalform of the data generating process, the distribution from whichthe data are drawn, and the applicability of these modelingassumptions to new counterfactuals, then the data-based measuresproposed 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 modelingassumptions on counterfactual inferences. Author’s note: Easy-to-use software to implement the methodsdiscussed here, called "WhatIf: Software for Evaluating Counterfactuals,"is available at http://gking.harvard.edu/whatif. All informationnecessary to replicate the analyses herein can be found in King and Zeng (2008).Conflict of interest statement. None declared.