WhatIf: WhatIf: Software for Evaluating Counterfactuals
Inferences about counterfactuals are essential for
prediction, answering what if questions, and estimating causal
effects. However, when the counterfactuals posed are too far
from the data at hand, conclusions drawn from well-specified
statistical analyses become based largely on speculation hidden
in convenient modeling assumptions that few would be willing to
defend. Unfortunately, standard statistical approaches assume
the veracity of the model rather than revealing the degree of
model-dependence, which makes this problem hard to detect.
WhatIf offers easy-to-apply methods to evaluate counterfactuals
that do not require sensitivity testing over specified classes
of models. If an analysis fails the tests offered here, then
we know that substantive inferences will be sensitive to at
least some modeling choices that are not based on empirical
evidence, no matter what method of inference one chooses to
use. WhatIf implements the methods for evaluating
counterfactuals discussed in Gary King and Langche Zeng, 2006,
"The Dangers of Extreme Counterfactuals," Political Analysis 14
(2); and Gary King and Langche Zeng, 2007, "When Can History Be
Our Guide? The Pitfalls of Counterfactual Inference,"
International Studies Quarterly 51 (March).