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a plausible explanation for the existing case based on a well-validated and explicit theory. This step is important, obviously, because the counterfactual varies what are thought to be the critical variables that presumably accounted for the historical outcome. If the investigator has an erroneous or questionable explanation for the historical case, then the counterfactual analysis is likely to be flawed.337 Similarly, if the generalization underlying the historical explanation is a probabilistic one, certain factors varied in the counterfactual exercise may have made the event less probable, but it might have occurred anyway in the absence of those factors.

Second, the relationship among variables hypothesized by the invented case must also be supported by a well-validated theory, as in the historical case. In other words, the explanation for the counterfactual case must be plausible.

Third, when many variables are part of a historical explanation (as is often the case), it is difficult to formulate a counterfactual that includes variation of all the causal variables.

Fourth, a historical explanation does not necessarily imply a counterfactual argument that the event would not have happened if the causal variable had been different. There could be causal substitution—i.e., some other set of causes might have substituted for the variable in question and caused the same outcome.

Fifth, the independent variable in the existing case that is varied in order to produce an invented one must be autonomous; that is, it must be separable from other independent variables that have operated to produce the outcome in the first case. When several independent variables are interconnected so that conjunctural causation exists, as is often the case for problems that engage the interest of social scientists, it becomes difficult to invent a usable new case via counterfactual analysis by altering only one variable, and the complexity of the interconnected variables may be difficult to identify with any reliability.

Sixth, if the explanation for the historical case consists of a series of events in sequence over time—i.e., chains of causation involving path dependency—rather than a single, simple circumscribed event, then constructing an acceptable counterfactual becomes much more difficult. For this would require either a complex counterfactual that involves a long chain of causation involving many variables and conditions, or a more limited counterfactual that focuses on a change in only one of the many events in the chain of causation. Conversely, a counterfactual case is easier to construct if one or only a few decisive points in the historical case determined the outcome. Short-term causation is generally easier to address with a counterfactual than causation that involves a longer-term process.

Summarizing the preceding discussion of the special difficulties encountered with the controlled comparison method, it is not surprising that investigators should differ in their judgment of its utility for theory development. Not all investigators believe that the problems are so intractable as to warrant abandoning controlled comparison studies altogether. Nonetheless, practically all efforts to make use of the controlled comparison method fail to achieve its strict requirements. This limitation is often recognized by investigators employing the method, but they proceed nonetheless to do the best they can with an admittedly imperfect controlled comparison. They do so because they believe that there is no acceptable alternative and no way of compensating for the limitations of controlled comparison.

We conclude, however, that it is desirable to develop alternatives to controlled comparison. The major alternative we propose is “within-case” causal analysis to be discussed briefly in this chapter and more fully in Chapter 10.

An Alternative Proposed by King, Keohane, and Verba

In Designing Social Inquiry (DSI), Gary King, Robert Keohane, and Sidney Verba express grave reservations, as we do, regarding the feasibility of meeting the