Ben Bernanke’s econometric shadow boxing with reality

4 November, 2015 at 10:55 | Posted in Statistics & Econometrics | 1 Comment

I consider the work of Bernanke (1986) on the relationship between money and output because I agree with Robert King’s observation that it is an “admirable piece of normal science” even if I do not share his view that the paper is “a tribute to macroeconomics”. Bernanke’s thoughtfulness, care and attention to detail is apparent. His scientific objectivity in considering his own theory and that of others is exemplary … I single Bernanke’s work out because it is an example of excellent research within the tradition it represents.

shadowboxBernanke’s paper does not really reach a substantive conclusion that could possibly change the views of any serious observer of the economy … The only firm conclusion reached is that structural interpretations of VARs are very sensitive to the model one assumes and that future research using VARs should take this into account. It is hard to see how such findings can stimulate new theoretical developments or bring about improvements in our ability to predict, control or explain economic events …

Investigators like Bernanke, who believe that they can learn something new about causal relationships without introducing information beyond that contained in time series whose properties have already been studied thousands of times, are shadow boxing with reality. As the foregoing observations suggest, their identifying assumptions are obviously implausible once stated in English. Formalism and the attendant matrix algebra serves primarily to obscure the futility of the exercise in which they are engaged.

Lawrence Summers


1 Comment

  1. Absolutely. To understand causality you need to do the historical work – which means ploughing through a lot of (largely qualitative) primary historical documentation. Time series regressions are no where near enough to give us the crucial information and when implausible assumptions are also introduced we are wasting our time.

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