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Stumbleupon Review of : http://www.versobooks.com/FTP/Jump%20You%20Fuckers%202%203.pdf

The Origins of the Crisis

So we can’t adequately explain what happened with either the long view of human nature or with a close‐up on the finance sector in recent years. Nor should we overstate the importance of a handful of now retired operators. The crisis we now face begins to form in outline in the early seventies. Two related developments introduced growing instability into financial markets and the wider economy – the growth of debt and the deregulation of finance.

After a long period of expansion between 1945 and 1970, in which real wages grew steadily throughout the developed world, workers’ compensation levelled off. Average earnings per hour in private non‐agricultural industries in the United States reached $8.99 in 1972 (calculated in 1982 dollars). By 2007 they had risen to $8.30. Sorry, no, they had fallen to $8.30 (again, calculated in 1982 dollars). More widely, in the rich, industrialised world, the percentage of GDP
captured by all workers in the form of wages fell from 75% in the mid‐seventies to 66% in the middle years of this decade.

Output per hour continued to rise – workers still produced more goods and delivered more services, helped in part by information technology. But they weren’t being paid more in real terms for the time and effort.

So who benefited from the weakening share of income secured by labour? Profits and rents have increased by a full third over the last generation, so the first group to benefit from the shift was the very, very rich. The result has been a new Gilded Age, reminiscent of the late nineteenth and early twentieth centuries, with all the exquisite good taste, state of the art sycophancy, and imperial violence that characterised the earlier era.

But the share of GDP paid to workers was also distributed far more unevenly. Managers who successfully drove down wages for the rest of the workforce themselves enjoyed massive increases in wealth. According to Paul Krugman, in 1970 American CEOs made $1.3 million a year ‐ 39 times as much as the average worker. By 1999 their pay had increased to $37.5 million ‐ a staggering 1000 times the average.

via, and.

Stumbleupon Review of : http://www.santafe.edu/research/publications/workingpapers/97-10-080.pdf

Path dependence refers to both those economic environments in which the history of shocks have long run consequences as well as those in which the shocks are merely persistent. The important feature in path dependent economies is that the certain shocks to the system will not work their way out of the system due to some intrinsic dynamic within the system. However, they may dissipate due to future shocks. This feature is particularly useful in thinking about models which can generate phenomena similar to the Great Depression in the United States, where the output declines of 1929-1932 do not seem to have been self-correcting, yet the New Deal and Second World War were able to shift the economy away from sustained low-production. Hence while, as an historical matter, the Depression was persistent rather than permanent, it nevertheless is defensible that the pre-World War II economy exhibited path dependence.

Stumbleupon Review of : http://www.voxeu.org/index.php?q=node/3210

What this shows, not for the first time, is that models of the economy that incorporate the EMH – and this includes the complete markets core of the New Classical and New Keynesian macroeconomics – are not models of decentralised market economies, but models of a centrally planned economy.

The friendly auctioneer at the end of time, who ensures that the right terminal boundary conditions are imposed to preclude, for instance, rational speculative bubbles, is none other than the omniscient, omnipotent and benevolent central planner. No wonder modern macroeconomics is in such bad shape. The EMH is surely the most notable empirical fatality of the financial crisis. By implication, the complete markets macroeconomics of Lucas, Woodford et. al. is the most prominent theoretical fatality. 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.

So, no Oikomenia, there is no pot of gold at the end of the rainbow, and no Auctioneer at the end of time.

Linearise and trivialise

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 transubstantiation 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. Those of us who worry about endogenous uncertainty arising from the interactions of boundedly rational market participants cannot but scratch our heads at the insistence of the mainline models that all uncertainty is exogenous and additive.

Technically, the non-linear stochastic dynamic models were linearised (often log-linearised) at a deterministic (non-stochastic) steady state. The analysis was further restricted by only considering forms of randomness that would become trivially small in the neighbourhood of the deterministic steady state. Linear models with additive random shocks we can handle – almost!