A Morgensternian critique of econometrics is different from other critiques that focus on econometrics as practiced by prominent economists. Edward Leamer (1983), in an influential article, stated that econometric analysis is not taken seriously due to the amount of “data mining” and “number crunching.” Econometricians make implicit assumptions about the distribution of errors, the functional form, and the variables in the model. According to Leamer statistical interference is based on opinions and whims. In a similar way, Deirdre McCloskey and Steven Ziliak (2008) criticize the procedure of econometricians and the abuse of significance testing. Too often statistical significance is confused with real world significance. Morgenstern’s critique is, however, on a different level. The critique of econometric practices and techniques does not deal with the accuracy of the underlying data but takes it as given. Morgenstern more fundamentally questions the accuracy of economic data and, consequently, the very basis for econometrics.
It is indeed surprising to note how much the problem of accuracy in economic data has been neglected. This is not the case in the physical sciences (Preston and Dietz 1991). Within the physical sciences the error of observation is always explicitly mentioned, yet in economics there is simply no error estimate. This means that economists do not know the accuracy of the economic data presented to them. This is even more troubling when one considers that in social or economic data there are more possible sources of error than in the physical sciences. Economists, therefore, face the question of why the problem of accuracy of economic data is rarely mentioned or passed over in silence in economics, while in the physical sciences this problem is widely acknowledged.
—Philipp Bagus, “Morgenstern’s Forgotten Contribution: A Stab to the Heart of Modern Economics,” American Journal of Economics and Sociology 70, no. 2 (April 2011): 542.
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