In the past 20 years, researchers have begun to embrace the idea that identification is not an all-or-nothing matter and that a set of plausible assumptions that does not deliver point identification can still contain useful information about parameters of interest.This partial identification view has been motivated by the fact that point identification is not the objective by itself and in essence takes us back to Koopmans & Reiersol’s (1950) dictum whereby the specification of a model ought to be based on [A] the underlying economics, [B] prior knowledge (such as the linearity of variable cost that people have established for this industry), or [C] other assumptions with universal or [C*] almost universal acceptance, but [D] should not be geared primarily toward point identifying the parameters. “Scientific honesty demands that the specification of a model be based [B] on prior knowledge of the phenomenon studied and [E] possibly on criteria of simplicity, but not [D] on the desire for identifiability of characteristics that the researcher happens to be interested in” (Koopmans & Reiersol 1950, pp. 169–70). Once the structure is specified, the model can either have no information about the parameter of interest, restrict the parameter of interest to a nontrivial set, or point identify the parameter of interest. This is exactly the domain of identification analysis, with partial identification taking the view that identification is not only about verifying whether the third case holds, but also determining the extent of information contained in the second and linking this to the type of assumptions that the researcher proposes in the model.--Elie Tamer (2010). [Emphasis and Letters added to facilitate discussion. --ES]*
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