Tag Archives: Uncertainty

Economic Forecasting in Alternative Universes

<dweeby econo-skepticism follows>

The New York Times Magazine today has an article on the past, present and future of the Obama administration’s economic policy.  It is a good if long read and chock full of inside baseball, political speaking points delivered with some repetition lest you miss them and, most entertaining, anonymous score-settling amongst the recently departed economics team.  The narrative is mostly cheerleading, ex post facto rationalization and blame-shifting for the last two years.  And despite an intent to paint a positive picture going forward, specific points of the story are quite damning:

  • In a dramatic meeting December 16, 2008 before taking office, the new team was “warned the country was in far worse shape than anyone realized.”  Despite this deliberately seeded anecdote, one excuse offered is they didn’t understand the true magnitude of the crisis: “The problem was that the baseline economy was in worse shape than even the grim assessment of that Chicago meeting in late 2008.”
  • Economists from both the left and the right are quoted saying the strategy and guiding principles for recent economic policy are unclear: “This was all new to Obama, who, unlike Bush or Clinton, had never managed even a state economy.”  The lack of strategy is charitably described as evidence of pragmatism.
  • The stimulus package was a failure, despite being enacted in January 2009 with the prediction “that if the stimulus passed, unemployment would be at 7 percent at the end of 2010.”  Stimulus proponents continue to defend the strategy but say the particulars were simply “inadequate and poorly targeted”.  The inside-the-beltway crowd views this as a problem in expectations-setting rather than actual policy.
  • Unemployment is obviously still distressingly high and government statistics underreport the pain: “Counting those who are seeking full-time jobs while working part time and those how have stopped looking altogether, it’s closer to 17 percent.”
  • The economic team was “fractured” and “the word most commonly used by those involved is ‘dysfunctional’”.  Larry Summers bears the brunt of it (you know him from his appearance in The Social Network).  Budget Director Peter Orszag says, “Unfortunately I think the environment often brought out the worst in people instead of the best in people. And I’d include myself in that.” I have a gift suggestion for the new team.
  • They continue to flail for ideas and a strategy.  As recently as the week before Christmas, the President replies, after being presented with “familiar and uninspired” proposals, with “I’ve told you before, I want you to come with ideas that excite me.”
  • The primary speaking point, voiced by Treasury Secretary Timothy Geithner, is “it could have been so much worse.’”  Despite the litany of screw-ups mentions in the article, no one had the temerity to suggest that it could have been better as well.

My purpose in writing this is not to score partisan points (one can easily argue that Obama’s core economic policy differed little from Bush’s, and both were paltry in impact compared with the Federal Reserve), but rather to indict the whole macroeconomic-industrial complex (a sentence which to me evokes this clip starting at about 1:45).  What set me off is the implication in the article that the administration is looking not just to rejuvenate the economy, but also to salvage the reputation of government management of the economy.

Creating millions of jobs is one thing, but redeeming faith in the Keynesian dream of technocratic micromanagement of something as ridiculously complex as our economy after the last few years certainly qualifies as a big hairy audacious goal.  Especially after the economic policy team responsible admits they weren’t guided by a clear strategy or set of principles, didn’t understand quite what was going on in the economy, implemented a program that was ineffective and badly missed its predicted impact, don’t know what to do next, and were the poster child for a dysfunctional team, there is some real work necessary to believe they’ll get it right next time.  The basic problem is the economic models that underlie all these policy prescriptions seem to work better in every universe except our own.  The Times article mentions a model supporting the “it could have been so much worse” school:

Without the actions taken by Bush, Obama and the Federal Reserve, the economy was headed to what Bernanke called “Depression 2.0,” in which unemployment potentially would peak at 16.5 percent, according to a later study by Blinder and Mark Zandi, chief economist at Moody’s Analytics.

I somehow resisted the urge to pillory this study, entitled “How the Great Recession Was Brought to an End”, when it first came out.  The New York Times’ lede at the time said:

“Like a mantra, officials from both the Bush and Obama administrations have trumpeted how the government’s sweeping interventions to prop up the economy since 2008 helped avert a second Depression.  Now, two leading economists wielding complex quantitative models say that assertion can be empirically proved.”

Empirically proved!  You see, Misters Blinder and Zandi have a model of the US economy.  They can type in some parameters and find out what would have happened in the absence of the fiscal and monetary actions of the last couple years.  This model is so good, it can tell us how much worse it could have been to three significant figures.  They “empirically proved” that by the end of 2010, real GDP is 6.61% higher, there are 8.40 million more jobs, the unemployment rate is 5.46 points lower and the Low Income Home Energy Assistance Program has a Keynesian multiplier of 1.13 thanks to various government actions.

Conveniently, this counterfactual is set in an alternative universe which no one can disprove.  When it comes to forecasting things in our universe, this model and its cohorts don’t do so well.  This model that so accurately predicts events in that alternative universe didn’t predict the global financial crisis nor does it accurately predict what will happen next in our universe.  And there seems to be some kind of agreement amongst polite company not to point out the huge role of failed economic models in causing the global financial crisis (Michael Lewis’ The Big Short is a great read and a very accessible introduction to wayward economic models).  And I probably shouldn’t point out that Zandi and this model both come from Moody’s which of course used its various models to rate all those mortgage securities that blew up as AAA risks (and Moody’s of course has no incentive to pander to the government in order to keep their Federally mandated position in the bond rating oligopoly…).

The epistemic arrogance, to use Nassim Taleb’s phrase, of the macroeconomics profession is staggering.  They still have the keys to the car and are trying to pass their driver’s test by pointing to how they would have parallel parked in another universe, despite having hit the cars in front and behind them as well as sideswiping the parking meter in this universe.

The Times story does offer two bright spots.  One is perhaps they have figured out economic growth is the only hope.  The new head of the Council of Economic Advisors says “We’ve shifted out of the rescue mode.  We’ve got to move into full-fledged growth mode.”  And This Time is Different: Eight Centuries of Financial Folly makes an appearance.  I highly recommend this book, even if you just read the first and last two chapters (though you’ll miss cool things like how Newfoundland lost its sovereignty and the fact Greece has been in default roughly every other year since it gained its independence from the Ottoman Empire).  This Time is Different suggests tendencies in economic behavior and the consequences of various government policies without pretending to be able to accurately predict or control them.  The concluding paragraphs:

“The lesson of history, then, is that even as institutions and policy makers improve, there will always be temptation to stretch the limits. Just as an individual can go bankrupt no matter how rich she starts out, a financial system can collapse under the pressure of greed, politics, and profits no matter how well regulated it seems to be.

Technology has changed, the height of humans has changed, and fashions have changed. Yet the ability of governments and investors to delude themselves, giving rise to periodic bouts of euphoria that usually end in tears, seems to have remained a constant. No careful reader of Friedman and Schwartz will be surprised by this lesson about the ability of governments to mismanage financial markets, a key theme of their analysis.  As for financial markets, Kindleberger wisely titled the first chapter of his classic book “Financial Crisis: A Hardy Perennial.”

We have come full circle to the concept of financial fragility in economies with massive imbalances. All too often, periods of heavy borrowing can take place in a bubble and last for a surprisingly long time. But highly leveraged economies, particularly those in which continual rollover of short-term debt is sustained only by confidence in relatively illiquid underlying assets, seldom survive forever, particularly if leverage continues to grow unchecked. This time may seem different, but all too often a deeper look shows it is not. Encouragingly, history does point to warning signs that policy makers can look at to assess risk – if only they do not become too drunk with their credit bubble-fueled success and say, as their predecessors have for centuries, “This time is different.”

In the meantime, I await the Nixonian proclamation that “We are all Hayekians now.”

Taleb on Suckers

Extraordinarily timely Taleb essay on Edge.org:

Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let’s face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).

He actually is turning his attention to generating constructive advice for “how to live in a world we don’t understand”, but not without a few shots at the French, Ben Bernanke, Nobel Prize-winning economists and of course Wall Street along the way:

It appears that financial institutions earn money on transactions (say fees on your mother-in-law’s checking account) and lose everything taking risks they don’t understand. I want this to stop, and stop now— the current patching by the banking establishment worldwide is akin to using the same doctor to cure the patient when the doctor has a track record of systematically killing them. And this is not limited to banking—I generalize to an entire class of random variables that do not have the structure we thin[k] they have, in which we can be suckers.

Toto, We’re Not in Mediocristan Any More

More on the poor applicability of financial models to the real world from the Economist:

Goldman Sachs admitted as much when it said that its funds had been hit by moves that its models suggested were 25 standard deviations away from normal. In terms of probability (where 1 is a certainty and 0 an impossibility), that translates into a likelihood of 0.000…0006, where there are 138 zeros before the six. That is silly.

Or Maybe Your Model Leaves Something to be Desired…

From last week’s WSJ (requires a paid subscription for now, pending Rupert’s next move):

“Wednesday is the type of day people will remember in quant-land for a very long time,” said Mr. Rothman, a University of Chicago Ph.D. who ran a quantitative fund before joining Lehman Brothers. “Events that models only predicted would happen once in 10,000 years happened every day for three days.”

The Black Swan has been on bestseller lists for a couple months and we’ve seen multiple 1 in 10,000 year events over the last decade, but some people still seem to believe in their models…

Reverence for models does seem to be breaking down on other fronts.

Book Review: The Black Swan

The Black Swan, by Nassim Nicholas Taleb is sort of a follow-up to his earlier Fooled By the Randomness, which dealt with why people are poorly suited to decision-making in the face of uncertainty.

The Black Swan deals with the “impact of the highly improbable” and argues that these events, dubbed Black Swans, are far more common then we think, in part because of the perverse influence of modern statistics which assumes all kinds of things are normally distributed except for the minor detail that they aren’t.  When they make the book into a movie, Carl Friedrich Gauss will be the villain (who should be played by Max Von Sydow).  Events like 9/11, the collapse of Long-Term Capital Management and most wars are Black Swans.  No one sees them coming, but in retrospect people manage to explain them.

The book is full of wide-ranging applications of his thesis, great asides and mildly misanthropic comments about businesspeople, anyone in finance, economists, particularly Nobel Prize winners, German philosophers, forecasters of any kind, opera fans and the French.

The core of the book is the distinction between Mediocristan and Extremistan.  Mediocristan is the world of the normal distribution, where outliers are extremely rare.  Many physical characteristics have a normal distribution, such as height or weight.  In Mediocristan, it is not at all likely that an additional observation will impact the sum of all observations in any significant way.  Extremistan is very different and is the domain of the power law distribution (think of the power law curve in The Long Tail except the Taleb is all about why the head is way more important than the tail because in the real world you don’t know whether you’ve observed the head of the head yet).  An outlier observation can dwarf the sum of all previous observations, such as Bill Gates entering the room when you’re observing wealth.  Big swathes of the real world, particularly social dynamics and informational goods, are in Extremistan, are not normally distributed and we treat them as Mediocristan at our peril.

The bulk of the book examines why we are so blind to Black Swans and gets into a fair amount of behavioral psychology like the earlier book.  Not surprisingly, we tend to look for things that reaffirm our beliefs as opposed to contradict them; we’re good at constructing stories to explain things after the fact; we tend to ignore the silent evidence “of cemeteries” and focus disproportionately on the winners (think survivorship bias); assume the real world abides by clear and understandable rules; and we generally overestimate what we know and underestimate what we don’t.

The book is kind of a bummer in that he doesn’t have much of a prescription for how to survive and thrive in Extremistan: 

“I care about the premises more than the theories, and I want to minimize reliance on the theories, stay light on my feet and reduce my surprises.  I want to be broadly right rather than precisely wrong.  Elegance in the theories is often indicative of Platonicity and weakness – it invites you to seek elegance for elegance’s sake.  A theory is like medicine (or government): often useless, sometimes necessary, always self-serving, and on occasion lethal.  So it needs to be used with care, moderation and close adult supervision.”

Basically, he attributes success to “undirected trial and error” and encourages you to maximize your exposure to as many positive Black Swans as possible.  Better to be lucky than good:

“Capitalism is, amongst other things, the revitalization of the world thanks to the opportunity to be lucky.”

“Everything is transitory.  Luck both made and unmade Carthage; it both made and unmade Rome.”

He applies his thinking to a variety of different realms with very intriguing results.  As a former options trader, he basically denounces Modern Portfolio Theory as complete bunk, a castle built on shifting Gaussian sands.  He asserts that a mere ten days over the last fifty years account for HALF of the market’s performance (I assume it to be true but will adopt his stance of skeptical empiricism in the absence of verifying it).  Needless to say, that means some very fat tails.  He also revels in the various explanations of the blow-up of Long-Term Capital Management (which Roger Lowenstein chronicles quite well in the succinct When Genius Failed) and needles the Nobel Prize winning economists who were involved at length.  Taleb implied in an interview that his own portfolio is roughly 80% T-bills and 20% exposure to positive Black Swans with unlimited upside which sounds like venture capital of some form.

He arrives at a similar conclusion as Andy Kessler on globalization and division of labor.  Don’t sweat the US’s trade deficit.  That is just revenue: just look at the balance of profits (where the US runs a surplus).  He believes the US has focused on scaleable businesses where your revenue is not limited by your number of labor hours, but rather those that involve creativity and are often winner-take-all in the global economy.  We export jobs for the non-scaleable elements to others who are happy to be paid by the hour: “There is more money in designing a shoe than actually making it; Nike, Dell and Boeing can get paid for just thinking, organizing and leveraging their know-how and ideas while subcontracted factories in developing countries do the grunt work and engineers in cultured and mathematical states do the noncreative technical grind”.

He also looks at innovation.  I’ve always believed that any successful technology has a strong element of serendipity in its adoption (standards body denizens hate it when you point this out and this would be a wonderful area to add up the “silent evidence” of failures) and he makes the same point, even using the word serendipity:

“If you think that the inventions we see around us came from someone sitting in a cubicle and concocting them according to a timetable, think again: almost everything of the moment is the product of serendipity.” 

I’ll save a discussion of the role of Black Swans in Microsoft’s history for my oft-mentioned, but entirely un-started book.

In short, it is a great and thought-provoking read.  It is rife with parenth
eticals and asides like the following that also make it entertaining:

“You can even include Frenchmen (but please, not too many out of consideration for the others in the group)…”

“Line up a thousand authors (or people begging to get published, but calling themselves authors instead of waiters)…”

“The person becomes more vulnerable to all manner of fads, such as astrology, superstitions, economics. and tarot-card reading.”

“They will probably take up, depending on their temperaments, bird-watching, Scrabble, piracy, or other pastimes.”

“Everyone has an idea of utopia.  For many it means equality, universal justice, freedom from oppression, freedom from work (for some it may be the more modest, though no more attainable, society with commuter trains free of lawyers on cell phones).”

“Eventually, authors who are not often cited will drop out of the game by, say, going to work for the government (if they are of a gentle nature), or for the Mafia, or for a Wall Street firm (if they have a high level of hormones).” 

“When you are employed, hence dependent on other people’s judgment, looking busy can help you claim responsibility for the results in a random environment.  The appearance of busyness reinforces the perception of causality, of the link between results and ones’ role in them.”

“Being an executive does not require very developed frontal lobes, but rather a combination of charisma, a capacity to sustain boredom, and the ability to shallowly perform on harrying schedules.  Add to these tasks the “duty” of attending opera performances.”

“Economics is the most insular of fields; it is the one that quotes least outside itself!  Economics is perhaps the subject that currently has the highest number of philistine scholars — scholarship without erudition and natural curiosity can close your mind and lead to the fragmentation of disciplines.”

“Optimization is a case of sterile modeling…  It had no practical (or even theoretical) use, and so it became principally a competition for academic positions, a way to make people compete with mathematical muscle.  It kept Platonified economists out of the bars, solving equations at night.”

“Alas, it turns out that it was [Paul] Samuelson and most of his followers who did not know much math, or did not know how to use what math they knew, how to apply it to reality.  They only knew enough math to be blinded by it.”