Empirical Economics? An Econometric Dilemma with Only a Methodological Solution
Conventional econometric practice begins with a general model or family of models. Various model specifications are explored, and the one that best fits the data is chosen. If, however, researchers regard the chosen model as merely a convenient summary of the data, what can be learned about economic theory or our explanation of economic phenomena? Nothing, unless theory is held in genuine risk of rejection or revision by observation. Rarely does applied econometrics begin with a theory (and when it does, it is utility theory). More rare still are those studies where a specific utility function is used to derive the researcher's econometric model. Because econometric models are not regarded as the theory under examination, researchers usually do not bother to accumulate evidence, for or against, a specific econometric representation. Rather, the development and application of new statistical techniques propel model evaluation and evolution. Econometric inference is only as trustworthy as the underlying statistical assumptions. The necessary assumptions concern specific distributional properties of the errors in the associated econometric model.1 Such errors receive little attention from economic theorists and are added grudgingly at the end of econometric models. Nonetheless, it is the proper specification of these error distributions, along with the exact structure of the interdependence, that sanctions our empirical economic inferences. The necessity of correctly specifying the underlying statistical model is always at issue in actual econometric applications. Questions of proper