Today's best prediction is that things are gonna stay mostly the same...

...and don't you let anyone tell you otherwise...

Amplify’d from www.boston.com

We reserve a special place in society for those who promise genuine insights into the future — who can predict what will happen in business, in sports, in politics, technology, and so on. The media landscape is rich with these experts; Wall Street pays millions of dollars every year to analysts to put a precise dollar figure on next year’s company earnings. Those who manage to get a few big calls right are rewarded handsomely, either in terms of lucrative gigs or the adoration of a species that so needs to believe that the future is in fact predictable.

But are such people really better at predicting the future than anyone else?

To find the answer, Denrell and Fang took predictions from July 2002 to July 2005, and calculated which economists had the best record of correctly predicting “extreme” outcomes, defined for the study as either 20 percent higher or 20 percent lower than the average prediction. They compared those to figures on the economists’ overall accuracy. What they found was striking. Economists who had a better record at calling extreme events had a worse record in general. “The analyst with the largest number as well as the highest proportion of accurate and extreme forecasts,” they wrote, “had, by far, the worst forecasting record.”

Their work is the latest in a long line of research dismantling the notion that predictions are really worth anything. The most notable work in the field is “Expert Political Judgment” by Philip Tetlock of the University of Pennsylvania. Tetlock analyzed more than 80,000 political predictions ventured by supposed experts over two decades to see how well they fared as a group. The answer: badly. The experts did about as well as chance. And the more in-demand the expert, the bolder, and thus the less accurate, the predictions. Research by a handful of others, Denrell included, suggests the same goes for economic forecasters. An accurate prediction — of an extreme event or even a series of nonextreme ones — can beget overconfidence, which can lead to making bolder and bolder bets, and thus, more and more errors.

There’s no great, complex explanation for why people who get one big thing right get most everything else wrong, argues Denrell. It’s simple: Those who correctly predict extreme events tend to have a greater tendency to make extreme predictions; and those who make extreme predictions tend to spend most of the time being wrong — on account of most of their predictions being, well, pretty extreme. There are few occurrences so out of the ordinary that someone, somewhere won’t have seen them coming, even if that person has seldom been right about anything else. Read more at www.boston.com

 

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Macroeconomics yet again: The disinterest in reality

DeLong from last year with two questions: Why do good macroeconomists seemingly find "patently unrealistic" theories acceptable? And why don't they feel they need to make their theories consistent with the evidence described and collected by economic historians?



Again, I feel the answer has to involve the strategies and attitudes towards empirical facts, knowledge and data that economists too frequently allow. The types of arguments and challenges economists face in seminars and from referees and editors make it necessary to be consistent with current theoretical fads and remove the need to take into account certain types of evidence and arguments. Provided you know the right incantations and spells ("this is just an as if theory," "these are standard assumptions," etc.), then I'm confident you can ward off even the economic history bootcamp that DeLong proposes.

Amplify’d from delong.typepad.com

two questions:

First, it does not seem to me that it is the case that nobody really believes these just-so stories. Ed Prescott of Arizona State University really does believe that large-scale recessions are caused by economy-wide episodes of the forgetting of the technological and organizational knowledge that underpins total factor productivity—with the exception of episodes like the Great Depression, which Prescott says was caused by the extraordinary pro-labor pro-union policies of Herbert Hoover that pushed real wages far above equilibrium values. Casey Mulligan of the University of Chicago really does appear to believe that large falls in the employment-to- population ratio are best seen as “great vacations”—and as the side-effects of destructive government policies like those in place today, which are leading workers to quit their jobs so they can get higher government subsidies to refinance their mortgages. (I know; I find it incredible too.) Things that strike Kocherlakota as “patently unrealistic” are not viewed as such by many of his modern macroeconomic peers and colleagues. Why not? Why do they find these just-so stories satisfactory?

Second, whether modern macroeconomics attributes our current difficulties either to causes that I agree with Kocherlakota are “patently unrealistic” or simply confesses ignorance, why do they have such a different view than we economic historians do? Whether they have rejected our interpretations and understandings or simply have built up or failed to build up their own in ignorance of what we have done, why have they not taken and used our work?

The second question is particularly disturbing to me. There is, after all, no place for economic theory of any flavor to come from than from economic history. Someone observes some instructive case or some anecdotal or empirical regularity, says “this is interesting; let's build a model of this,” and economic theory is off and running. Theory is crystalized history—it can be nothing more. After the initial crystalization it does develop on its own according to its own intellectual imperatives and processes, true, but the seed is still there. What happened to the seed?

This situation is personally and professionally dismaying. I do not say that the macroeconomic model-building of the past generation has been pointless. I don’t think that it has been pointless. But I do think that the assembled modern macroeconomists need to be rounded up, on pain of loss of tenure, and sent to a year-long boot camp with the assembled monetary historians of the world as their drill sergeants. They need to listen to and learn from Dick Sylla about Cornelius Buller’s bank rescue of 1825 and Charlie Calomiris about the Overend, Gurney crisis and Michael Bordo about the first bankruptcy of Baring brothers and Barry Eichengreen and Christy Romer and Ben Bernanke about the Great Depression.

If modern macreconomics does not reconnect—if they do not realize just what their theories are crystallized out of, and what the point of the enterprise is—then they will indeed wither and die. Read more at delong.typepad.com

 

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"The profession danced around the wrong models..."

More macro-criticism from last year - this time quotes from Joseph Stiglitz. And again, it's a case of "those guys used these models, which I think are stupid. Luckily, other people used these models which I think are smart - and these are the ones we should start using."



Again - I miss a focus on evidence and methodology: If these critics are right that our profession allowed madness to reign - how can we avoid this in the future? What should we demand from researchers who claim that they can guide policy, explain society, etc? Surely we need to do better than "they should employ the assumptions and modelling approaches that I find reasonable and that lead to the conclusions I am comfortable with"?

Amplify’d from economistsview.typepad.com

It is hard for non-economists to understand how peculiar the predominant macroeconomic models were. Many assumed demand had to equal supply – and that meant there could be no unemployment. (Right now a lot of people are just enjoying an extra dose of leisure; why they are unhappy is a matter for psychiatry, not economics.) Many used “representative agent models” – all individuals were assumed to be identical, and this meant there could be no meaningful financial markets (who would be lending money to whom?). Information asymmetries, the cornerstone of modern economics, also had no place: they could arise only if individuals suffered from acute schizophrenia, an assumption incompatible with another of the favored assumptions, full rationality.

Bad models lead to bad policy: central banks, for instance, focused on the small economic inefficiencies arising from inflation, to the exclusion of the far, far greater inefficiencies arising from dysfunctional financial markets and asset price bubbles. After all, their models said that financial markets were always efficient. Remarkably, standard macroeconomic models did not even incorporate adequate analyses of banks...: even a cursory look at the perverse incentives confronting banks and their managers would have predicted short-sighted behavior with excessive risk-taking. ...

Fortunately, while much of the mainstream focused on these flawed models, numerous researchers were engaged in developing alternative approaches. ... With a few exceptions, most central banks paid little attention to systemic risk and the risks posed by credit interlinkages. Years before the crisis, a few researchers focused on these issues, including the possibility of the bankruptcy cascades that were to play out in such an important way in the crisis. This is an example of the importance of modeling carefully complex interactions among economic agents (households, companies, banks) – interactions that cannot be studied in models in which everyone is assumed to be the same. Even the sacrosanct assumption of rationality has been attacked: there are systemic deviations from rationality and consequences for macroeconomic behavior that need to be explored.

Changing paradigms is not easy. Too many have invested too much in the wrong models. Like the Ptolemaic attempts to preserve earth-centric views of the universe, there will be heroic efforts to add complexities and refinements to the standard paradigm. The resulting models will be an improvement and policies based on them may do better, but they too are likely to fail. Nothing less than a paradigm shift will do. Read more at economistsview.typepad.com

 

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Ronald Coase on good and bad economics

This post contains no argument or data or big insight. File it under "Hey! Somebody famous said something I like the sound of!"

Amplify’d from economistsview.typepad.com

RC: The bad or wrong economics is what I called the "blackboard economics". It does not study the real world economy. Instead, its efforts are on an imaginary world that exists only in the mind of economists, for example, the zero-transaction cost world.

Ideas and imaginations are terribly important in economic research or any pursuit of science. But the subject of study has to be real. Read more at economistsview.typepad.com

 

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The Empire strikes back.... Of course it does.

I'm working my way (backwards) through a pile of blogpostings that I wanted to read. Here's a couple of quotes from a longer interview where new classical Thomas Sargent brushes off that silly criticism that has been directed towards modern macro. It is foolish, intellectually lazy, and misinformed. Basically - they were doing very well and were not at all surprised by the financial crisis, and there's already interesting work available on how to generate this stuff within their models.

Amplify’d from economistsview.typepad.com

Sargent: I know that I’m the one who is supposed to be answering questions, but perhaps you can tell me what popular criticisms of modern macro you have in mind.

Rolnick: OK, here goes. Examples of such criticisms are that modern macroeconomics makes too much use of sophisticated mathematics to model people and markets; that it incorrectly relies on the assumption that asset markets are efficient in the sense that asset prices aggregate information of all individuals; that the faith in good outcomes always emerging from competitive markets is misplaced; that the assumption of “rational expectations” is wrongheaded because it attributes too much knowledge and forecasting ability to people; that the modern macro mainstay “real business cycle model” is deficient because it ignores so many frictions and imperfections and is useless as a guide to policy for dealing with financial crises; that modern macroeconomics has either assumed away or shortchanged the analysis of unemployment; that the recent financial crisis took modern macro by surprise; and that macroeconomics should be based less on formal decision theory and more on the findings of “behavioral economics.” Shouldn’t these be taken seriously?

Sargent: Sorry, Art, but aside from the foolish and intellectually lazy remark about mathematics, all of the criticisms that you have listed reflect either woeful ignorance or intentional disregard for what much of modern macroeconomics is about and what it has accomplished. That said, it is true that modern macroeconomics uses mathematics and statistics to understand behavior in situations where there is uncertainty about how the future will unfold from the past. But a rule of thumb is that the more dynamic, uncertain and ambiguous is the economic environment that you seek to model, the more you are going to have to roll up your sleeves, and learn and use some math. That’s life.

Rolnick: Putting aside fear and ignorance of math, please say more about the other criticisms.

Sargent: Sure. As for the efficient markets hypothesis of the 1960s, please remember the enormous amount of good work that responded to Hansen and Singleton’s ruinous 1983 JPE [Journal of Political Economy] finding that standard rational expectations asset pricing theories fail to fit key features of the U.S. data.1 Far from taking the “efficient markets” outcomes for granted, important parts of modern macro are about understanding a large and interesting suite of asset pricing puzzles, brought to us by Hansen and Singleton and their followers—puzzles about empirical failures of simple versions of efficient markets theories. Here I have in mind papers on the “equity premium puzzle,” the “risk-free rate puzzle,” the “Backus-Smith” puzzle, and on and on.2

Rolnick: What about the most serious criticism—that the recent financial crisis caught modern macroeconomics by surprise?

Sargent: Art, it is just wrong to say that this financial crisis caught modern macroeconomists by surprise. That statement does a disservice to an important body of research to which responsible economists ought to be directing public attention. Researchers have systematically organized empirical evidence about past financial and exchange crises in the United States and abroad. Enlightened by those data, researchers have constructed first-rate dynamic models of the causes of financial crises and government policies that can arrest them or ignite them. The evidence and some of the models are well summarized and extended, for example, in Franklin Allen and Douglas Gale’s 2007 book Understanding Financial Crises.7 Please note that this work was available well before the U.S. financial crisis that began in 2007. Read more at economistsview.typepad.com

 

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Market failure in academic economics?

The two quotes below (first one by Paul Krugman and second by Laurence Meyer) claim that subdisciplines in Economics veer off into absurdity and silliness because you get fads: If you want to publish in peer-reviewed, well-esteemed journals, then you need to use this or that modelling approach even if it has nothing to do with reality.



The thing that gnaws at me when I read this, though, is the worry that this is one group of economists annoyed that "their" fad is not the one controlling the top journals. The claim here is pretty strong: It's not that you're accepted into top journals in spite of your absurdity, the claim is that you're accepted ONLY IF you embed your work in the currently popular absurdity. Silliness is a necessary condition for being published.



Seems to me this kind of situation presupposes a clearly crippled "scientific" culture: Unless there were accepted and widespread strategies for downplaying, ignoring or lying about the fact that your model has little or nothing to do with reality - then the problem discussed by these authors would be limited to small, limited bubbles of absurdity that were widely ridiculed in the broader economics community.

Amplify’d from krugman.blogs.nytimes.com

By the early 1980s it was already common knowledge among people I hung out with that the only way to get non-crazy macroeconomics published was to wrap sensible assumptions about output and employment in something else, something that involved rational expectations and intertemporal stuff and made the paper respectable. And yes, that was conscious knowledge, which shaped the kinds of papers we wrote. So you could do exchange rate models that actually had realistic assumptions about prices and employment, but put the focus on rational expectations in the currency market, so that people really didn’t notice. Or you could model optimal investment choices, with the underlying framework fairly Keynesian, but hidden in the background. And so on.

the real business cycle or neoclassical models. It’s what’s taught in graduate schools. It’s the only kind of paper that can be published in journals. It is called “modern macroeconomics.” The question is, what’s it good for? Well, it’s good for getting articles published in journals. It’s a good way to apply very sophisticated computational skills. But the question is, do those models have anything to do with reality? Models are always a caricature—but is this a caricature that’s so silly that you wouldn’t want to get close to it if you were a policymaker? Read more at krugman.blogs.nytimes.com

 

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Agent based modelling - sensible when modelling machines?

Agent based modelling defines simple agents and lets them act and interact in a simulation. A common complaint is that this is stupid because people are more sophisticated than these agents are. However (cfr. last post), when the major share of trading is done by algorithmic software, then this objection loses force. Surely, software should be able to mimic software. In principle, it should even be possible to collect actual trading software and pit these against each other in a virtual and purely simulated market. In practice, I doubt firms would let their "proprietary" software out of their sight.



BTW - I'm not saying the guy mentioned below (LeBaron) has found true results or that this method is splendid. I don't know enough about it to make any such claims. But the method sounds interesting: Let agents with different hypotheses about their environment, different ways of using past info to distill patterns and predictions, compete in an evolving ecosystem where growth is related to past success - and see what aggregate outcomes, persistent regularities and interesting properties we get out of it.

Amplify’d from www.nature.com

'stability' is a word few would use to describe the chaotic markets of the past few years, when complex, nonlinear feedbacks fuelled the boom and bust of the dot-com and housing bubbles, and when banks took extreme risks in pursuit of ever higher profits. In an effort to deal with such messy realities, a few economists — often working with physicists and others outside the economic mainstream — have spent the past decade or so exploring 'agent-based' models that make only minimal assumptions about human behaviour or inherent market stability (see page 685). The idea is to build a virtual market in a computer and populate it with artificially intelligent bits of software — 'agents' — that interact with one another much as people do in a real market. The computer then lets the overall behaviour of the market emerge from the actions of the individual agents, without presupposing the result. Agent-based models have roots dating back to the 1940s and the first 'cellular automata', which were essentially just simulated grids of on–off switches that interacted with their nearest neighbours. But they didn't spark much interest beyond the physical-science community until the 1990s, when advances in computer power began to make realistic social simulations more feasible. Since then they have found increasing use in problems such as traffic flow and the spread of infectious diseases (see page 687). Indeed, points out Helbing, agent-based models are the social-science analogue of the computational simulations now routinely used elsewhere in science to explore complex nonlinear processes such as the global climate.

LeBaron has spent the past decade and a half working with colleagues, including a number of physicists, to develop an agent-based model of the stock market. In this model, several hundred agents attempt to profit by buying and selling stock, basing their decisions on patterns they perceive in past stock movements. Because the agents can learn from and respond to emerging market behaviour, they often shift their strategies, leading other agents to change their behaviour in turn. As a result, prices don't settle down into a stable equilibrium, as standard economic theory predicts. Much as in the real stock market, the prices keep bouncing up and down erratically, driven by an ever-shifting ecology of strategies and behaviours.

Nor is the resemblance just qualitative, says LeBaron. Detailed analyses of the agent-based model show that it reproduces the statistical features of real markets, especially their susceptibility to sudden, large price movements. "Traditional models do not go very far in explaining these features," LeBaron says. Read more at www.nature.com

 

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Wall Street 3 - The Rise of the Machines

Discussed algorithmic trading recently with an economics professor and mentioned the claim that this can create instabilities. For instance, if too many use similar programs, these can create feedback loops such that sales trigger new sales that trigger new sales etc. Or that the mix of currently existing strategies interact in such a way that they create a bubble. The response was that this is unlikely to happen - as traders will take into account the nature of and intereactions between the different strategies that are out there. As Robert Anton Wilson said, you can always see the invisible hand as long as you look hard enough and long enough (or something along those lines).

Amplify’d from www.wired.com

Over the past decade, algorithmic trading has overtaken the industry. From the single desk of a startup hedge fund to the gilded halls of Goldman Sachs, computer code is now responsible for most of the activity on Wall Street. (By some estimates, computer-aided high-frequency trading now accounts for about 70 percent of total trade volume.) Increasingly, the market’s ups and downs are determined not by traders competing to see who has the best information or sharpest business mind but by algorithms feverishly scanning for faint signals of potential profit.

at its worst, it is an inscrutable and uncontrollable feedback loop. Individually, these algorithms may be easy to control but when they interact they can create unexpected behaviors—a conversation that can overwhelm the system it was built to navigate. On May 6, 2010, the Dow Jones Industrial Average inexplicably experienced a series of drops that came to be known as the flash crash, at one point shedding some 573 points in five minutes. Less than five months later, Progress Energy, a North Carolina utility, watched helplessly as its share price fell 90 percent. Also in late September, Apple shares dropped nearly 4 percent in just 30 seconds, before recovering a few minutes later.

And they started applying those methods to every aspect of the financial industry. Some built algorithms to perform the familiar function of discovering, buying, and selling individual stocks (a practice known as proprietary, or “prop,” trading). Others devised algorithms to help brokers execute large trades—massive buy or sell orders that take a while to go through and that become vulnerable to price manipulation if other traders sniff them out before they’re completed. These algorithms break up and optimize those orders to conceal them from the rest of the market. (This, confusingly enough, is known as algorithmic trading.) Still others are used to crack those codes, to discover the massive orders that other quants are trying to conceal. (This is called predatory trading.)

The result is a universe of competing lines of code, each of them trying to outsmart and one-up the other. “We often discuss it in terms of The Hunt for Red October, like submarine warfare,” says Dan Mathisson, head of Advanced Execution Services at Credit Suisse. “There are predatory traders out there that are constantly probing in the dark, trying to detect the presence of a big submarine coming through. And the job of the algorithmic trader is to make that submarine as stealth as possible.”

In late September, the Commodity Futures Trading Commission and the Securities and Exchange Commission released a 104-page report on the May 6 flash crash. The culprit, the report determined, was a “large fundamental trader” that had used an algorithm to hedge its stock market position. The trade was executed in just 20 minutes—an extremely aggressive time frame, which triggered a market plunge as other algorithms reacted, first to the sale and then to one another’s behavior. The chaos produced seemingly nonsensical trades—shares of Accenture were sold for a penny, for instance, while shares of Apple were purchased for $100,000 each. (Both trades were subsequently canceled.) The activity briefly paralyzed the entire financial system. Read more at www.wired.com

 

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The rational agent has been found

He was in a comic book.

Also, he was a mean, evil criminal...

From The Prediction Machine: "

Source: 'Fantastic Four Giant' #5. Invented by Stan Lee and Jack Kirby.

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"

Truth and beauty in economics

Hans directed me to the following quote from Keynes recently used by Krugman in his blog:

The completeness of the Ricardian victory is something of a curiosity and a mystery.... That it reached conclusions quite different from what the ordinary uninstructed person would expect, added, I suppose, to its intellectual prestige. That its teaching, translated into practice, was austere and often unpalatable, lent it virtue. That it was adapted to carry a vast and consistent logical superstructure, gave it beauty. That it could explain much social injustice and apparent cruelty as an inevitable incident in the scheme of progress, and the attempt to change such things as likely on the whole to do more harm than good, commended it to authority. That it afforded a measure of justification to the free activities of the individual capitalist, attracted to it the support of the dominant social force behind authority.

This inspired me to try a more old-fashioned style in expressing my own views on the matter.

Theories and beliefs are supported by how right they feel to us and how well they survive confrontation with the facts. The first criteria speaks to human cognitive preferences - the desire for parsimonious, consistent and elegant structures that we can "see" how work and that we can admire in their precise beauty. The second criteria speaks to empirical truth, the grudgingly admitted recognition that messy facts and the jumble of a complex world are the stuff that we are, in the final analysis, trying to understand. And when practical difficulties, methodological weaknesses or an implicit cultural agreement free us from the need of confrontations with empirical data, we become even more strongly wedded to pursuing, protecting and promoting the "truths" we believe ourselves so strongly to see.  

 

I need to start smoking a pipe and use a mechanical typewriter if I’m going to keep on like this.

Geographical distribution of scientific claims

Richard Dawkins pokes fun at the geographical distribution of religious faiths, and claims that “we immediately see […] how totally ridiculous that is” when we imagine a world where scientific beliefs were distributed in the same way.

LOL.

Yeah, cause that would be totally silly. Like if, say, macroeconomists along US coastlines tended to claim totally opposite things from those around the large inland freshwater lakes regarding why depressions occur, whether fiscal policy works, whether markets are efficient, etc. If that’s how things were, you might even suspect that macro-economics wasn’t a science at all, which it obviously is: I mean, come on! They’ve got equations, econometrics and jargon that could confuse an audience more thoroughly than a medieval Pope speaking in Latin and tongues. And the holy trinity has nothing on the representative agent – I mean, forget being three and one at the same time, this dude is all of us!!!

Also fun to note: Prankster Paul Krugman takes Dawkin’s joke and runs with it, cooking up some fanciful story about so-called Freshwater and Saltwater economics in the US here (especially section IV and onward) and here. Nice imagining of an alternative bizarro world there that makes it obvious to all just how far from a religion economics in real life actually is.

Efficient Market Hypothesis and criticism

IN a recent blogpost the odd and quirky Robin Hanson discusses How To Dis EMH (Efficient Market Hypothesis) and (more importantly) - how not to. He shows some quotes of the debates going on and argues that you cannot judge EMH unless you can at the time do better than it and prove that you can do this consistenly over time.

So the clearest way for EMH skeptics to show they are right is to collect a track record showing that they can predict, ahead of time, when prices are too high, vs. too low. There’s little point in picking out some year old event, and saying, “see that price drop was too big.” Monday morning quarterbacking is way too easy.

...

But all this continual harping year after year on how EMH is obviously wrong, based on selective stories of past prices you say were obviously wrong, sounds awful suspicious when you don’t bother to publicly flag price errors at the time, much less to collect and publicize a track record of such error flags. (E.g., care to declare which prices are wrong today?) What’s up with that?

It's an interesting point that I agree with to a point, but there's something odd about it as well. I think it may have something to do with what we mean by "criticism of EMH". Hanson's point is valid if a critic says that the EMH is often obviously wrong and can easily be improved. But what if a critic says that the quality of forward looking predictions (including his/her own) is generally poor, and that this translates into an extreme volatility in stock markets and markets in futures and derivatives? If this is so, and if there are significant and real costs to sharply and vigorously yanking the economy towards whatever-our-best-guesstimate-of-the-future-is-right-now, then we might not want our economy to be as dependent on the estimates of the future. We may be able to choose or influence at a social or policy level how "forward looking" our economy is in its adjustments - and we may not want the ADHD economy that wants to pull up all roots and set sails towards whatever the future seems to hold at any given instant.

From Economics to Ideology to Real World Disaster?

Two interesting articles I recently read tied nicely together as a story about how the search for intellectual sophistication and grand theory in economics generated a doctrinaire belief in the free markets marvels and ability to police itself, which became an intellectual alibi and ideological fuel for a "hands-off-the-economy" Conservative movement, that in turn removed all road-blocks to a Financial Crisis and completely bungled the reconstruction of Iraq.

Phew... that was a long sentence...

Anyway - this piece by Kenneth Davidson in the American Interest argues that George Stigler and Milton Friedman turned the Chicago School of Economics into the hotbed of laissez faire economics that it is still regarded as today. And how this in turn helped along a new policy of deregulation that created the recent Financial Crisis.

Once it abandoned its political concerns with economic power, Chicago theory, with its axioms of profit maximization, perfect information and self-correcting markets, had no advice to limit the downside risks of economic and financial disaster. The fruitful blending of social and economic concerns pioneered by Simons may not be suitable to a modern economy, but his concern about the dangers of centralizing economic power remains an issue that is ignored by the Chicago School. Doctrine supplanted healthy intellectual doubt, theoretical purity trumped common sense and historical memory, acolytes took over from masters, and a different kind of irrational exuberance was the result. We’re all now paying the price.

The other piece, by Naomi Klein, in the Atlantic from 2004, describes the reasoning behind the Iraq reconstruction effort - basically, the attempt to set up a totally free and rigorous free market paradise that would have every capitalist in the Milky Way clamoring to invest and generate jobs, wealth and prosperity for all. While clearly biased against this ideology, there are numerous interesting quotes and witty observations - though it seems weird to both argue that their attempt was foiled because it was illegal against international law and to argue that the chaos of Iraq that followed should be proof that a full and perfect implementation of free market laws and regulations does not work.

And - as always - both authors can be attacked by any economist worth his salt. Because academic economics, of course, has nuances and spends much of its time discussing and analyzing flaws and caveats to the simplified picture that these authors attack. Its just that no conclusion ever lives on except as it does in broad stroke form. Friedman's essay on positive economics becomes "unrealistic assumptions are fine and lead to true welfare conclusions because it is all as if theory". A "perfect competition" reference model and "rationality assumption" with selfish preferences becomes "the broad truth" and what policy makers with bachelors in Economics and even the intuitions of many sophisticated researchers reach for.

Or something like that - what's the point? - if you recall this in the future it may all be reduced to "he blames economics for Iraq and everything that goes wrong" anyway... ;-)

Distorting the truth to make the case that economists distort the truth?

Hans made me aware of this: In a recent blogpost entitled "What Should Economists Study?" Brad DeLong writes the following:

As one of the students interviewed for the original The Making of an Economist, let me say that there was a distressingly wide gap between what we told Colander and Klamer and what they heard: we were not nearly as stupid and as narrow as they wanted us to be.

Bit of a let-down, since several of their claims seemed to ring true to me, but worth noting. Seems a bit silly to ignore empirical data when it contradicts your hypothesis that economists too frequently ignore empirical data.

BTW - don't recall this book as arguing that economist students were stupid or narrow. It's argument was more that the education they were offered seemed - to them - to be narrow and stupid. As far as I recall from skimming it several years ago.

The evidence I see vs. the evidence I don't want to see

Tyler Cowen writes about a restaurant where you roll 3 dice after your meal and get the pizza for free if you roll 4-3-1. He writes:

I take this as evidence against the view that people systematically miscalculate expected utility in repeated, real market settings. If they did, you would expect to see commercial lures like this much more often. Maybe in mortgage markets, or credit card markets, people are overoptimistic about the bad (too many floating rate mortgages or too many people accepting the risk of high default fees), but I don't think in pizza markets they are overoptimistic about the good. A restaurant which makes this kind of offer, of course, has to charge systematically higher prices, the greater the customer's chance of winning the lottery,

I wholeheartedly agree. If people systematically miscalculated expected utility in repeated, real market settings you would see a lot more stuff like, for instance, rip-off "extra warranties" when you purchase electronic equipment, or maybe even "lotteries," slot machines, roulette games etc. with negative expected payoff that people participated in regularly, etc. Good thing that's only the stuff of science fiction.

Extreme belief in market similar to extreme beliefs in the State?

It’s a bit childish, but it’s also fun to see a ridicule or teasing wrapped up in an academic argument. The short and blunt version: “Ha ha! Modern macro is doing the same thing as the planned economy guys they (rightly) think are stupid. That means the modern macro guys are stupid as well!”

The argument is an interesting and (I think) insightful analogy that bunches the free-market macroeconomists in with old-style planned-economy advocates that they are politically opposed to :-)

In the old debates about planned vs. market based economies, the “libertarian” economist Friedrich Hayek (who believed on theoretical grounds any intervention in the market would set in motion a slippery slope to totalitarianism) argued the importance of information: Prices, emerging in free markets, were the only way of gathering the often tacit knowledge of market participants into a form that communicated the relative values of various uses of a resource. A lack of market-based prices meant ignorance regarding the value of resources, and misallocation of capital and manpower etc.

Keeping this in mind, it is fun to see the argument that modern representative agent macroeconomics make the same mistake as the advocates of planned economies. Both ignore the importance of dispersed knowledge, over-emphasize the ease with which information/data can be gathered and provide a true and total picture of the world, and base their work on one or more agents having this total understanding of the world (the central planner, or the representative agent).

models vs. economists

I have appreciated that quote by George Box for quite some time, but only when I realized what it implies about the models' creators I saw its true beauty:

"All economists are wrong, but some are useful."

Should I have written `some' with a capital S...?

Scroogenomics: Economist wants to improve the efficiency of Christmas

My grandmother always gave me really big underwear for Christmas. I never wore it. Joel Waldfogel must have had similar experiences since he has written a book on the topic. Not underwear, but Christmas and gift giving in general. Here is the main story.

Serious economist: Giving a gift is not efficient if the recipeint values the gift less than the full cost of the gift. In fact, even if they value it higher than the costs, it may not be efficient since  - assuming you know your own preferences better than other people - you could have spent the money on something that gave you an even higher surplus. So, obviously we should only give each other money. By not doing so Americans waste around $12 billion per year, according to very unbiased estimations.

I do not know whether to laugh or cry. I once read a satirical paper about this is an economics journal. To my surprise I then found that the American Economic Journal has published several articles on the topic - with lots of discussion. And please tell me that I was wrong, please tell me that I just mistunderstood the article, please, please ... but it seems to me that these papers were not satirical.

And now a book has been published by one of the participants: Scroogenomics. The $12 billion is from the book. I have not read it and I pray to God that it is satirical, clever and funny ... but from the description it sounds like he is a serious economist.

Why do I hope this? I would not mind getting more money and less baggy underwear, but the nature and meaning of a gift-exchange is often very different when it involves money. Ariely has some observations on this in his book Predictably Irrational. For instance, bringing wine to a dinner party is OK. Giving money instead is not. Maybe economists would advise us to change the norms, but maybe also economist should recognize that this is not all there is to it. Waldfogel probably knows all this, but goes on anyway. So instead of just saying that it is absurd, I did a real survey and asked people about their willingness to sell gifts and at what price. The result? Many gifts were valued much higher than the cost. Why? Probably because of the sentimental value. So instead of destroying value, Christmas gifts increased value in my calculations.

Wow, I cannot believe I was tricked into doing this. Taking the discussion seriously and playing on their court. Even if the estimation had shown a loss I do not believe we should take it seriously. There are simply too many aspects of gift giving that will be left out in of the quantification to make the conclusion credible. Verdict: Absurd!Afternote: On no, he is serious! See interview.

Will the crisis change economics?

Q. In your view, what can save economics?

A. I am very pessimistic about whether we can actually pull out of this. I think we have created a locomotive. This is the sociology of the economics profession. We have created a monster that is very difficult to stop.

Q. Could real-world empirical facts or a severe economic cataclysm change it?

A. That would certainly change it, but I do not see that around the corner. Perhaps I am too pessimistic, and it is very depressing to stay there. There does not seem to me to be any way out.

(Mark Blaug, The problems with formalism – Interview with Mark Blaug, Challenge, May-June 1998)

Paul Roemer, The Nobel Prize for Elinor Ostrom

In a short essay about the The Nobel Prize for Elinor Ostrom, Paul Roemer writes: 

Bravo to the political scientist who showed that she was a better economist than the economic imperialists who can’t tell the difference between assuming and understanding.

Well said!