On the value of the rational expectations revolution which has dominated mainstream macroeconomic modeling for the past 30 years:
... the typical graduate macroeconomics and monetary economics training received at Anglo-American universities during the past 30 years or so, may have set back by decades serious investigations of aggregate economic behaviour and economic policy-relevant understanding. It was a privately and socially costly waste of time and other resources.On the matter of mathematical assumptions turning up in dynamic programming problems, and their unjustified inclusion as assumptions about the behaviour of real people in real markets:
Most mainstream macroeconomic theoretical innovations since the 1970s (the New Classical rational expectations revolution associated with such names as Robert E. Lucas Jr., Edward Prescott, Thomas Sargent, Robert Barro etc, and the New Keynesian theorizing of Michael Woodford and many others) have turned out to be self-referential, inward-looking distractions at best. Research tended to be motivated by the internal logic, intellectual sunk capital and esthetic puzzles of established research programmes rather than by a powerful desire to understand how the economy works...
The common practice of solving a dynamic general equilibrium model of a(n) (often competitive) market economy by solving an associated programming problem, that is, an optimisation problem, is evidence of the fatal confusion in the minds of much of the economics profession between shadow prices and market prices and between transversality conditions that are an integral part of the solution to an optimisation problem and the long-term expectations that characterise the behaviour of decentralised asset markets. The efficient markets hypothesis assumes that there is a friendly auctioneer at the end of time – a God-like father figure – who makes sure that nothing untoward happens with long-term price expectations or (in a complete markets model) with the present discounted value of terminal asset stocks or financial wealth.On the systematic obliteration of non-linearities and positive feed backs in today's macro models, even in the face of obvious empirical evidence for their importance:
... The future surely belongs to behavioural approaches relying on empirical studies on how market participants learn, form views about the future and change these views in response to changes in their environment, peer group effects etc. Confusing the equilibrium of a decentralised market economy, competitive or otherwise, with the outcome of a mathematical programming exercise should no longer be acceptable.
Finally, on the usefulness of so-called Dynamic Stochastic General Equilibrium models, the current state of the art of the macroeconomics community:
If one were to hold one’s nose and agree to play with the New Classical or New Keynesian complete markets toolkit, it would soon become clear that any potentially policy-relevant model would be highly non-linear, and that the interaction of these non-linearities and uncertainty makes for deep conceptual and technical problems. Macroeconomists are brave, but not that brave. So they took these non-linear stochastic dynamic general equilibrium models into the basement and beat them with a rubber hose until they behaved. This was achieved by completely stripping the model of its non-linearities and by achieving the transsubstantiation of complex convolutions of random variables and non-linear mappings into well-behaved additive stochastic disturbances.
Those of us who have marvelled at the non-linear feedback loops between asset prices in illiquid markets and the funding illiquidity of financial institutions exposed to these asset prices through mark-to-market accounting, margin requirements, calls for additional collateral etc. will appreciate what is lost by this castration of the macroeconomic models. Threshold effects, critical mass, tipping points, non-linear accelerators – they are all out of the window. ...The practice of removing all non-linearities and most of the interesting aspects of uncertainty from the models that were then let loose on actual numerical policy analysis, was a major step backwards. I trust it has been relegated to the dustbin of history by now in those central banks that matter.
Charles Goodhart, who was fortunate enough not to encounter complete markets macroeconomics and monetary economics during his impressionable, formative years, but only after he had acquired some intellectual immunity, once said of the Dynamic Stochastic General Equilibrium approach which for a while was the staple of central banks’ internal modelling: “It excludes everything I am interested in”. He was right. It excludes everything relevant to the pursuit of financial stability.