Failed Economic Theory

Here’s an article by Ben Bittrolff, the Financial Ninji, discussing the economic model upon which our economic policy is based.  The theory, neo-classical economic theory, is based on premises which are simply wrong. 

Policy Based on Failed Economic Theory: Just Stupid

Courtesy of Ben Bittrolff [ The Financial Ninja ]

I can’t stress how important it is to understand that economists are relying on hugely flawed theories and models when looking at the economy. Economic policy is being made off the neo-classical theory of economics. This is just a fancy way of describing current mainstream economic theory. This neo-classical theory of economics forms the basis for all the crap your politicians and their advisors keep trying. The greatest failed experiment of this theory is the practical implementation Keynesian and Neo-Keynesian economic policy. Today, right now you are witnessing the implementation of Keynesian theory to its absolute maximum limits with a policy of ZIRP and quantitative easing.

1) People have rational preferences among outcomes that can be identified and associated with a value.
2) Individuals maximize utility and firms maximize profits.
3) People act independently on the basis of full and relevant information.

The fact that we keep going thru economic and financial manias, bubbles and busts does not seem to deter the economic eggheads that continue to employ these theories literally like zealot Bible thumpers.

You’d figure that the Tulip Mania, South Sea Bubble, Dot Com Bubble, and the current Real Estate Bubble (to name a few) would be more than enough evidence to absolutely destroy all three of these premises.

This Economy Does Not Compute:

Excerpt:  A FEW weeks ago, it seemed the financial crisis wouldn’t spin completely out of control. The government knew what it was doing — at least the economic experts were saying so — and the Treasury had taken a stand against saving failing firms, letting Lehman Brothers file for bankruptcy. But since then we’ve had the rescue of the insurance giant A.I.G., the arranged sale of failing banks and we’ll soon see, in one form or another, the biggest taxpayer bailout of Wall Street in history. It seems clear that no one really knows what is coming next. Why?

Well, part of the reason is that economists still try to understand markets by using ideas from traditional economics, especially so-called equilibrium theory. This theory views markets as reflecting a balance of forces, and says that market values change only in response to new information — the sudden revelation of problems about a company, for example, or a real change in the housing supply. Markets are otherwise supposed to have no real internal dynamics of their own. Too bad for the theory, things don’t seem to work that way.

Nearly two decades ago, a classic economic study found that of the 50 largest single-day price movements since World War II, most happened on days when there was no significant news, and that news in general seemed to account for only about a third of the overall variance in stock returns. A recent study by some physicists found much the same thing — financial news lacked any clear link with the larger movements of stock values.

Certainly, markets have internal dynamics. They’re self-propelling systems driven in large part by what investors believe other investors believe; participants trade on rumors and gossip, on fears and expectations, and traders speak for good reason of the market’s optimism or pessimism. It’s these internal dynamics that make it possible for billions to evaporate from portfolios in a few short months just because people suddenly begin remembering that housing values do not always go up.

Really understanding what’s going on means going beyond equilibrium thinking and getting some insight into the underlying ecology of beliefs and expectations, perceptions and misperceptions, that drive market swings.

Surprisingly, very few economists have actually tried to do this, although that’s now changing — if slowly — through the efforts of pioneers who are building computer models able to mimic market dynamics by simulating their workings from the bottom up.

The idea is to populate virtual markets with artificially intelligent agents who trade and interact and compete with one another much like real people. These “agent based” models do not simply proclaim the truth of market equilibrium, as the standard theory complacently does, but let market behavior emerge naturally from the actions of the interacting participants, which may include individuals, banks, hedge funds and other players, even regulators. What comes out may be a quiet equilibrium, or it may be something else.

For example, an agent model being developed by the Yale economist John Geanakoplos, along with two physicists, Doyne Farmer and Stephan Thurner, looks at how the level of credit in a market can influence its overall stability.

Obviously, credit can be a good thing as it aids all kinds of creative economic activity, from building houses to starting businesses. But too much easy credit can be dangerous.

In the model, market participants, especially hedge funds, do what they do in real life — seeking profits by aiming for ever higher leverage, borrowing money to amplify the potential gains from their investments. More leverage tends to tie market actors into tight chains of financial interdependence, and the simulations show how this effect can push the market toward instability by making it more likely that trouble in one place — the failure of one investor to cover a position — will spread more easily elsewhere.

That’s not really surprising, of course. But the model also shows something that is not at all obvious. The instability doesn’t grow in the market gradually, but arrives suddenly. Beyond a certain threshold the virtual market abruptly loses its stability in a “phase transition” akin to the way ice abruptly melts into liquid water. Beyond this point, collective financial meltdown becomes effectively certain. This is the kind of possibility that equilibrium thinking cannot even entertain.

It’s important to stress that this work remains speculative. Yet it is not meant to be realistic in full detail, only to illustrate in a simple setting the kinds of things that may indeed affect real markets. It suggests that the narrative stories we tell in the aftermath of every crisis, about how it started and spread, and about who’s to blame, may lead us to miss the deeper cause entirely.

Financial crises may emerge naturally from the very makeup of markets, as competition between investment enterprises sets up a race for higher leverage, driving markets toward a precipice that we cannot recognize even as we approach it. The model offers a potential explanation of why we have another crisis narrative every few years, with only the names and details changed. And why we’re not likely to avoid future crises with a little fiddling of the regulations, but only by exerting broader control over the leverage that we allow to develop…

…Sadly, the academic economics profession remains reluctant to embrace this new computational approach (and stubbornly wedded to the traditional equilibrium picture). This seems decidedly peculiar given that every other branch of science from physics to molecular biology has embraced computational modeling as an invaluable tool for gaining insight into complex systems of many interacting parts, where the links between causes and effect can be tortuously convoluted.

Something of the attitude of economic traditionalists spilled out a number of years ago at a conference where economists and physicists met to discuss new approaches to economics. As one physicist who was there tells me, a prominent economist objected that the use of computational models amounted to “cheating” or “peeping behind the curtain,” and that respectable economics, by contrast, had to be pursued through the proof of infallible mathematical theorems.

If we’re really going to avoid crises, we’re going to need something more imaginative, starting with a more open-minded attitude to how science can help us understand how markets really work. Done properly, computer simulation represents a kind of “telescope for the mind,” multiplying human powers of analysis and insight just as a telescope does our powers of vision. With simulations, we can discover relationships that the unaided human mind, or even the human mind aided with the best mathematical analysis, would never grasp.

Better market models alone will not prevent crises, but they may give regulators better ways for assessing market dynamics, and more important, techniques for detecting early signs of trouble. Economic tradition, of all things, shouldn’t be allowed to inhibit economic progress. [Emphasis by Ninja]

Reference:  NY Times article, This Economy Does Not Compute, by Mark Buchanan, a theoretical physicist, author, most recently, of “The Social Atom: Why the Rich Get Richer, Cheaters Get Caught and Your Neighbor Usually Looks Like You.”