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In contrast to conventional model selection criteria, the Focused Information Criterion (FIC) allows for purpose-specific choice of models. This accommodates the idea that one kind of model might be highly appropriate for inferences on a particular parameter, but not for another. Ever since its development, the FIC has been increasingly applied in the realm of statistics, but this concept appears to be virtually unknown in the economic literature. Using a classical example and data for 35 U.S. industry sectors (1960-2005), this paper provides for an illustration of the FIC and a demonstration of its usefulness in empirical applications.

Being Focused: When the Purpose of Inference Matters for Model Selection