REH – assuming we know what in fact we never know15 December, 2012 at 10:27 | Posted in Economics, Statistics & Econometrics, Theory of Science & Methodology | 2 Comments
With over a million copies of its papers downloaded per year, Real-World Economics Review is now probably the world’s most read economics journal. The latest issue – no. 62 – is out today. And yours truly has a paper in it - Rational expectations – a fallacious foundation for macroeconomics in a non-ergodic world:
The financial crisis of 2007-08 hit most laymen and economists with surprise. What was it that went wrong with mainstream neoclassical macroeconomic models, since they obviously did not foresee the collapse or even make it conceivable?
As I have tried to show in this essay, one important reason ultimately goes back to how these models handle data. In REH-based modern neoclassical macroeconomics – Dynamic Stochastic General Equilibrium (DSGE), New Synthesis, New Classical, “New Keynesian” – variables are treated as if drawn from a known “data-generating process” that unfolds over time and on which one therefore have access to heaps of historical time-series. If one does not assume the “data-generating process” to be known – if there is no “true” model – the whole edifice collapses.
Building on REH, modern macroeconomics obviously did not anticipate the enormity of the problems that unregulated “efficient” financial markets created. Why? Because it builds on the myth of us knowing the “data-generating process” and that we can describe the variables of our evolving economies as drawn from an urn containing stochastic probability functions with known means and variances …
In the end this is what it all boils down to. We all know that many activities, relations, processes and events are of the Keynesian uncertainty type. The data do not – as REH models assume – unequivocally single out one decision as the only “rational” one. Neither the economist, nor the deciding individual, can fully pre-specify how people will decide when facing uncertainties and ambiguities that are ontological facts of the way the world works.
Some macroeconomists, however, still want to be able to use their hammer. So they decide to pretend that the world looks like a nail, and pretend that uncertainty can be reduced to risk. So they construct their mathematical models on that assumption. The result: financial crises and economic havoc.
How much better – how much bigger chance that we do not lull us into the comforting thought that we know everything and that everything is measurable and we have everything under control – if instead we would just admit that we often “simply do not know,” and that we have to live with that uncertainty as well as it goes. Fooling people into believing that one can cope with an unknown economic future in a way similar to playing at the roulette wheels, is a sure recipe for only one thing – economic catastrophy. The unknown knowns – the things we fool ourselves to believe we know – often have more dangerous repercussions than the “Black Swans” of Knightian unknown unknowns, something quantitative risk management – based on the hypotheses of market efficiency and rational expectations – has given ample evidence of during the latest financial crisis.