by Econometrics — analysis with incredible certitude There have been over four decades of econometric research on business cycles … But the significance of the formalization becomes more difficult to identify when it is assessed from the applied perspective … The wide conviction of the superiority of the methods of the science has converted the econometric community largely to a group of fundamentalist guards of mathematical rigour … So much so that the relevance of the research to business cycles is reduced to empirical illustrations. To that extent, probabilistic formalisation has trapped econometric business cycle research in the pursuit of means at the expense of ends. The limits of econometric forecasting have, as noted by Qin, been critically
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Lars Pålsson Syll considers the following as important: Statistics & Econometrics
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Econometrics — analysis with incredible certitude
There have been over four decades of econometric research on business cycles …
But the significance of the formalization becomes more difficult to identify when it is assessed from the applied perspective …
The wide conviction of the superiority of the methods of the science has converted the econometric community largely to a group of fundamentalist guards of mathematical rigour … So much so that the relevance of the research to business cycles is reduced to empirical illustrations. To that extent, probabilistic formalisation has trapped econometric business cycle research in the pursuit of means at the expense of ends.
The limits of econometric forecasting have, as noted by Qin, been critically pointed out many times before. Trygve Haavelmo assessed the role of econometrics — in an article from 1958 — and although mainly positive of the “repair work” and “clearing-up work” done, Haavelmo also found some grounds for despair:
There is the possibility that the more stringent methods we have been striving to develop have actually opened our eyes to recognize a plain fact: viz., that the “laws” of economics are not very accurate in the sense of a close fit, and that we have been living in a dream-world of large but somewhat superficial or spurious correlations.
Maintaining that economics is a science in the ‘true knowledge’ business, I remain a sceptic of the pretences and aspirations of econometrics. The marginal return on its ever higher technical sophistication in no way makes up for the lack of serious under-labouring of its deeper philosophical and methodological foundations that already Keynes complained about. The rather one-sided emphasis of usefulness and its concomitant instrumentalist justification cannot hide that the legions of probabilistic econometricians who give supportive evidence for their considering it ‘fruitful to believe’ in the possibility of treating unique economic data as the observable results of random drawings from an imaginary sampling of an imaginary population, are skating on thin ice.
A rigorous application of econometric methods in economics really presupposes that the phenomena of our real world economies are ruled by stable causal relations between variables. The endemic lack of predictive success of the econometric project indicates that this hope of finding fixed parameters is an incredible hope for which there, really, is no other ground than hope itself.