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Economics

Forecasting your way to Foolishness

I was  arguing in the last post that forecasts are much less useful for monetary policy  than people think. This is of course anathema and unthinkable to many people. The most fashionable current monetary framework, inflation targeting (or potential variants like nominal GDP targeting) are entirely reliant on forecasting the economy 1-2 years ahead. Hundreds of people are employed in central banks to do such projections. The process has the surface appearance of rigor and seriousness and technical knowledge. Monetary policy only has an impact with a lag, and those lags are famously long and variable. So, the argument goes, use of forecasts is essential.

This is almost universally accepted, but dead wrong. People overemphasize the relatively consistent lag and underemphasize the “variable” element. It is not just that economic forecasts of the future are notoriously inaccurate and unreliable. Our understanding of the transmission process from policy instruments to the real economy is also alarmingly vague, as the debates over the impact of QE showed.

That is an argument for caution, rather than technocratic overconfidence that we can predict inflation or GDP to a decimal point or two two years out. A less overconfident central bank is less likely to make serious policy errors. The development of precise models and projections tends to make people highly overconfident, however.

Standard academic thinking about monetary policy, with its targets and  policy rules,  is in fact a generation behind the rest of society. Most of business abandoned formal, rigorous planning methods based on forecasts and targets in the 1980s and 1990s, as Henry Mintzberg showed.  Corporations fired most of their economic forecasters and planners. Such formal methods had turned out to be mostly disastrous in practice. It made it more likely that people would ignore crucial new data, not less.

In fact, smarter central bankers tend to acknowledge the limits of projections. As they see it, the real value of projections is a matter of imposing consistency on the central banks outlook, rather than being able to confidently predict the future. It is a way of adding up the current data from different sectors of the economy to produce a unified picture.

But that could be done by simply using outside commercial forecasts, or international forecasts by bodies like the IMF or OECD. Central bank forecasts often perform very slightly better than individual outside forecasts, but hardly commensurate with the staff  resources and attention devoted to them. Averaging different forecasts is usually more accurate than any single forecast in any case.

Central banks shouldn’t be banned from looking at outside forecasts. They should just be forced to pay much less attention to forecasting and projections in general.

In any case, consistency is overrated in practice. Setting interest rates is not like proving a mathematical theorem.  Imposing consistency is often a way to ignore trade-offs or puzzles or genuine disagreement.

Forecasts are often  more of a distraction than an aid. Central banks actually tend to make decisions in a very different way in practice, as Lindblom argued decades ago.  They mostly make successive limited comparisons, because in practice it is too hard and unreliable to do anything else. No central bank makes decisions in an automatic way based on the forecast or a policy rule alone. They get into trouble when they rely on their consistent models too much, and think too little about the flaws or unexpected developments. In other words, using elaborate forecasts is a sign of ineptitude, not practical skill.

That also means markets misunderstand practical central bank policy when they think the models are as important as the staff economists who produce claim, or trust the official accounts of all the meetings that go into the forecast round.  As often happens, the way things happen is often different to the version in the official description or organization chart, and often even different to what people tell themselves they are doing.

If you can’t reliably predict, you need ways to control your exposure and adapt. “First, do no harm” is the best rule for monetary policy, not elaborate technical theater.

 

By | September 28, 2016|Central Banks, Economics, Federal Reserve, Forecasting, Monetary Policy|Comments Off on Forecasting your way to Foolishness

Let’s ban forecasts in central banks

People should learn from their mistakes, or so we usually all agree. Yet that mostly doesn’t happen. Instead, we get disturbing “serenity” and denial, and we had a prime example of it this week. So it is crucial we develop ways to make learning from mistakes more likely. I’d ban forecasts altogether in central banks if it would make officials pay more attention to what surprises them.

The most powerful institutions in the world economy can’t predict very well. But at least they could learn to adjust to the unexpected.

The Governor of the Bank of England, Mark Carney, testified before Parliament this week to skeptical MPs. The Bank, along with the IMF, Treasury, and other economists, predicted near-disaster if the UK voted for Brexit. So far, however, the UK economy is surprising everyone with its resilience.

So did Carney make a mistake? According to the Telegraph,

If Brexiteers on the Commons Treasury Committee were hoping for some kind of repentance, or at least a show of humility, they were to be sorely disappointed. Mr Carney was having none of it. At no stage had the Bank overstepped the mark or issued unduly alarmist warnings about the consequences of leaving, he insisted. He was “absolutely serene” about it all.

This is manifestly false and it did not go down well, at least with that particular opinion writer.

Arrogant denial is, I suppose, part of the central banker’s stock in trade. If a central bank admits to mistakes, then its authority and mystique is diminished accordingly.

I usually have a lot of regard for Carney, and worked at the Bank of England in the 1990s. But this response makes no sense. Central banking likes to think of itself as a technical trade, with dynamic stochastic general equilibrium models and optimum control theories. Yet the core of it has increasingly come down to judging subjective qualities like credibility, confidence, and expectations.

Economic techniques are really no use at all for this.  Credibility is not a technical matter of commitment, time consistency and determination, as economists often think since Kydland & Prescott. It is much more a matter of whether people consider you are aware of the situation and can balance things appropriately, not bind yourself irrevocably to a preexisting strategy or deny mistakes.  It is as much a matter of character and honesty as persistence.

The most frequent question hedge funds used to ask me about the Fed or other central banks was “do they see x?”  What happens if you are surprised? Will you ignore or deny it and make a huge mistake?  Markets want to know that central banks are alert, not stuck in a rut.  They want to know if officials are actively testing their views, not pretending to be omniscient. People want to know that officials aren’t too wrapped up in a model or theory or hiding under their desks instead of engaging with the real world.

It might seem as if denial is a good idea, at least in the short term. But it is the single most durable and deadly mistake in policymaking over the centuries. The great historian Barbara Tuchman called it “wooden-headedness,” or persistence in error.

The Bank of England, like other monetary authorities, issues copious Inflation Reports and projections and assessments. But it’s what they don’t know, or where they are most likely to miss something, which is most important. Perhaps the British press is being too harsh on Carney. Yet central banks across the world have hardly distinguished themselves in the last decade.

We need far fewer predictions in public policy, and far more examination of existing policy and how to adjust it in response to feedback. Forget about intentions and forecasts. Tell us what you didn’t expect and didn’t see, and what you’re going to do about it as a result. Instead of feedforward, we need feedback policy, as Herbert Simon suggested about decision-making.  We need to adapt, not predict. That means admitting when things don’t turn out the way you expected.

By | September 10, 2016|Adaptation, Central Banks, Communication, Decisions, Economics, Forecasting, Time inconsistency|Comments Off on Let’s ban forecasts in central banks

How the most common prescription doesn’t cure bias

One of the main messages of most psychological research into bias, and the hundreds of  popular books that have followed,  is that most people just aren’t intuitively good at thinking statistically. We make mistakes about the influence of sample size, and about representativeness and likelihood. We fail to understand regression to the mean, and often make mistakes about causation.

However, suggesting statistical competence as a universal cure can lead to new sets of problems. An emphasis on statistical knowledge and tests can introduce its own blind spots, some of which can be devastating.

The discipline of psychology is itself going through a “crisis’ over reproducibility of results, as this Bloomberg view article from the other week discusses. One recent paper found that only 39 out of a sample of 100 psychological experiments could be replicated. That would be disastrous for the position of psychology as a science, as if results cannot be replicated by other teams their validity must be in doubt. The p-value test of statistical significance is overused as a marketing tool or way to get published. Naturally, there are some vigorous rebuttals in process.

It is, however, a problem for other disciplines as well, which suggests the issues are  genuine, deeper and more pervasive. John Ioannidis has been arguing the same about medical research for some time.

He’s what’s known as a meta-researcher, and he’s become one of the world’s foremost experts on the credibility of medical research. He and his team have shown, again and again, and in many different ways, that much of what biomedical researchers conclude in published studies—conclusions that doctors keep in mind when they prescribe antibiotics or blood-pressure medication, or when they advise us to consume more fiber or less meat, or when they recommend surgery for heart disease or back pain—is misleading, exaggerated, and often flat-out wrong. He charges that as much as 90 percent of the published medical information that doctors rely on is flawed.

The same applies to economics, where many of the most prominent academics apparently do not understand some of the statistical measures they use. A paper (admittedly from the 1990s) found that 70% of the empirical papers in the American Economic Review, the most prestigious journal in the field,” did not distinguish statistical significance from economic, policy, or scientific significance.”  The conclusion:

We would not assert that every econoimst misunderstands statistical significance, only that most do, and these some of the best economic scientists.

Of course, the problems and flaws in statistical models in the lead up to the great crash of 2008 are also multiple and by now famous. If bank management and traders do not understand the “black box” models they are using, and their limits, tears and pain are the usual result.

The takeaway is not to impugn statistics. It is that people are nonetheless very good at making a whole set of different mistakes when they tidy up one aspect of their approach. More statistical rigor can also mean more blind spots to other issues or considerations, and use of  technique in isolation from common sense.

The more technically proficient and rigorous you believe you are, often the more vulnerable you become to wishful thinking or blind spots. Technicians often have a remarkable ability to miss the forest for the trees, or twigs on the trees.

It also means there are (even more) grounds for mild skepticism about the value of many academic studies to practitioners.

By | March 30, 2016|Big Data, Economics, Expertise, Psychology, Quants and Models|Comments Off on How the most common prescription doesn’t cure bias

Market Turmoil: Looking at the wrong things

The whole global economy is unravelling, if you believe some recent media claims. But oil and commodity price swings,  weaker emerging markets, or even renewed recession worries are not that unusual. In fact, this kind of news is completely normal and routine, as are the the scale of  share price falls so far Even a dip into recession in the US is a very normal occurrence. So why the air of panic?

I suggested in the last post  the underlying deeper concern is  whether policymakers have any “ammunition” left in the locker. The fear is any setback will feed on itself and turn into a downward spiral.  We are already at the zero bound on monetary policy, and we are still suffering a fiscal hangover from the 2008 crash. There are growing doubts among the public across the world about the competence of policymakers, which is also showing up in revolts against “the establishment.”  If there is another  downturn or any kind of problem, perhaps the policymakers can’t cope.

Let’s focus on economic policy, and leave the political side for later.  Are policymakers really out of options if there’s another market slide?  The answer is … actually yes, there are few effective policy options left. But the economy isn’t like a simple machine in which you can pull levers anyway. It’s complex, evolutionary and (mostly) resilient.  That means looking at the problem in a different way.

Avoiding Quackery

Central banks can always find something to do to appear busy or engaged. So we have seen the introduction of negative rates by the Bank of Japan last week, as well as talk of another round of QE by the Fed if recovery falls apart.

There were even rumors going around the other week that the Fed was intervening indirectly to affet the VIX, an index of market volatility, which is likely absurd.

In the end, the Fed could finally hire the helicopters Friedman and Bernanke mused about, and throw hundred dollar bills out the door in a new city every day to stimulate the economy. Would it help?

If a doctor doesn’t know what’s wrong with a patient, there are  always things which give the appearance of useful action, from trying random drugs right up to amputating limbs.

The question is whether the unconventional cure works, or perhaps has such severe side effects it makes things worse.  You can always try giving an aspirin to cure a heart attack, but it might not help much. If you get too unconventional in economic policy, just like in medicine you can end up in quackery, with snake oils, balsams and elixirs that promise to cure everything – with no actual effect.

And sometimes there is just nothing more even the most advanced medicine can do for a patient, despite the shiniest machines and telegenic doctors dramatically applying the defibrillator and yelling “clear!”  They give electric shocks to the patient .. .  while watching the screen trace flatline.  The same might be true in economic policy if the disease is serious enough.

The reality is the normal tools and cures are mostly played out. At best, the current “unconventional policy” central bank cures are very imperfect substitutes for cutting the main policy rate in a usual downturn. Sure, monetary policy can always increase the quantity of money, or try to push people into riskier assets by making riskless assets like bank balances or short-term bonds less attractive, or inflate away some debt claims. The markets mostly firmly believe that QE boosts the equity market (for a while.)

The problem is transmission from the financial sector to the real economy.  Or, as it sometimes called,  the old problems of “pushing on a string” or liquidity traps or animal spirits.   If there’s no demand for credit then the price of credit is irrelevant. If corporations are retaining profits and more focused on share buybacks than any new borrowing, then they don’t care about bond market conditions.

Also, it is hard to affect longer-term cycles or stock problems by acting on short-term flows. Ray Dalio argues we are at the end of a 70-year credit cycle, for example.

Buying time, not jump-starting the economy

Smarter central bankers know that there’s a limit to what they can do, or at least do effectively.  Just like most other economic phenomena, there is  diminishing marginal utility to most policy tools. The more realistic thinking behind the scenes  is at best they can buy time for other  processes to work themselves out, or perhaps offset some of the pain of restructuring and recovery in the real economy.  Central bankers can still stop bank runs or Bagehot-styles liquidity panics, but they can’t jump-start a whole economy.

And in any case perhaps, they sometimes think,  they are just letting politicians off the hook anyway. Monetary policy just enables the lazy politicians to avoid making tough decisions.  For example, fiscal policy – more government spending –  would be more effective than simply reducing the cost of money.

The trouble is fiscal policy has definite limits too (although the Paul Krugmans of the world have difficulty recognizing that.) Japan has spent trillions on stimulus and building infrastructure in the last two decades, running its debt to GDP up to more than 245%. There is plenty of concrete to show for it, but not a lot of vitality or growth. Bond markets more generally are potentialy fragile.

Getting Real

So if there are limits to stimulating demand, at some point you have to focus on the health of the real economy itself and the deeper sources of vitality and growth.  That  is where we need to look. The conventional economic answer here is you need to push through structural reform – more flexible labor markets, deregulation, more efficient tax collection, the usual range of things that the IMF always recommends.

Politicians have not been particularly good at that. Europe is always ducking such structural reform. A thousand initiatives to build “the next Silicon Valley” in Southeast Asia or Northern France or the Gulf States have faltered.

Economic Resilience

So here’s another thought:  perhaps even if the policymakers have no ammunition left, it might not matter so much.

The critical underlying assumption is this: how resilient is the economy anyway? How likely is to fix itself regardless of the policymakers?

Indeed, there is a long-standing and ferocious  argument that central bank intervention has usually made things worse. Attempts by the Fed to “fine-tune” the economy have usually led to errors and mistiming and moral hazard.  Central banks have a tendency to hit the accelerator just when they should be braking, and vice versa (in retrospect.) The belief in a “Greenspan put” or bank rescues has just made Wall Street reckless and greedy.

Indeed, until the 1930s, economists generally believed in laissez-faire. Intervention could only make things worse, delay adjustment and prolong the pain.  Andrew Mellon, Hoover’s Treasury Secretary, notoriously thought pain was necessary to “purge the rottenness in the system.”

Many libertarians still take this view, advocating a return to the gold standard or free banking. (I have got cornered by rich former used car dealers at the Cato Institute in DC arguing precisely that. At length.)

The Keynesian revolution denied all that. Sometimes the economy could get stuck in a much less desirable state or equilibrium and policymakers have to act.  And modern electorates flatly will not accept it. As Karl Polanyi argued, the gold standard would be impossible now because voters would revolt.

There is also the “BIS view” that the Fed in particular has overstimulated for two decades in order to avoid confronting the real problems. I’ll look at that another time.

I doubt the economy is inherently stable or that we can put much faith in equilibrium or simple “optimal control” ideas about policy.  But the economy is more resilient than we sometimes think.

So the most urgent question, we now see,  is what makes economies resilient?  And are we in trouble on that basis?    Maybe the economy isn’t like a machine where we can easily pull policy levers to make it change course. We’ve been looking for answers in the wrong places. It needs a different kind of thinking about economic policy, which involves complexity and leverage. Next.

 

 

By | February 7, 2016|Adaptation, Central Banks, Economics, Federal Reserve, Monetary Policy|Comments Off on Market Turmoil: Looking at the wrong things

Market Pessimism: Nothing left to shoot the bear?

So as we all dig ourselves out from the snow on the East Coast, the S&P is sliding again. There’s no sign of hibernation from the bears.  In fact, there seems to be an unusual amount of pessimism and angst out there among professional investors, and wider unease among the public which shows up in support for populist or socialist candidates in the Presidential race.

So how much should we worry? Is it time to plunge our head in a snowdrift and hope for the best? Let’s take the positive view first, and then go to the dark side.

So far the stock market slide is nothing out of the ordinary, of course, uncomfortable and morale-deflating as it is. We usually get a 10% correction in equity prices every two years or so, based on the historical record. So far it’s a bear cub, rather than a raging grizzly.

Let’s say it gets worse from here. 20% corrections are more lumpy in when they occur, but the long term average is they hit every 3 1/2 years or so. That’s a definite scrape from the bear, but not life-threatening. And we’re still very far away from that.

50% or more plunges, like 2008, are extremely rare, far out the tail of the probability distribution, occurring every generation. Or two. Or three.  But because we have painful memories of the most recent collapse, press stories about “worse than 2008” sell newspapers right now. Everything looks dangerous, but just like major earthquakes or hurricanes, it is likely to be decades before another hits us.

Putting this together, the most likely outcome, just in bare statistical terms, is a kind of regression to the mean and therefore recovery rather than another 2008-style catastrophe. That happens much more often in situations like this than a further slide to doom.

The trouble is frequency statistics can mislead. What if something more fundamental is broken? What if there’s cumulative damage?  There are always plenty of “This time it’s different” arguments for potential disaster when markets are weak.

So what is different right now?  What is so deep-seated and cumulative it could put us in 50% territory?

The main cause of recent market weakness appears to be the slide in oil prices, as well as concerns about a slowdown in China with knock-on effects on commodity producers. Add to those multiple pressures  on emerging markets the recent Fed rate rise, which may have disproportionate impact on the outer fringes of the dollar zone.

Yet oil and commodity price swings are anything but unusual. A decline in oil prices is bad for the energy sector but good for just about everyone else in the major western economies. The same applies to a first Fed rate rise in a cycle, even if it does tend to upset markets.

And it isn’t at all clear yet that China really has had a ‘hard landing’, as opposed to volatility on its equity markets. Many people have lost their shirts predicting collapse in the Chinese economy over the last ten or fifteen years.

There is clearly a massive debt hangover, and massive surplus capacity. Let’s affirm it: China has plenty of problems. But it could be a chronic gradual headache for years, rather than a spectacular meltdown which causes the whole world economy to crash. Or a painful temporary interlude, like the many spectacular crashes as the US nonetheless rose to the pinnacle of the world economy between 1865 and 1914.

The same applies to tension in the Middle East. There is obviously a heightened chance of serious conflict, as low oil prices cut budgets and the Saudis are increasingly fretful about Iranian resurgence. But that too could be a chronic, slow-moving problem rather than an immediate hot war. Sunni-Shia tensions date back to before 680AD, after all.  This is not unprecedented or unusual territory. “Trouble in the Middle East” is barely even news these days. And if a ship does get sunk or riots break out in a smaller Gulf state,  oil is likely to spike – offsetting other worries.

None of this is likely to derail the US economy. It’s compatible with a rotation in economic activity from emerging markets towards the US, rather than a collapse in the world economy. On this story, the US with its relatively minimal exposure to foreign weakness takes over its usual role as the  ‘locomotive’ pulling much of the rest of the world economy.  Safe-haven capital flows to the US, interest rates rise as the Fed normalizes, the dollar accordingly rises giving a boost to exporters in other countries, and the locomotive is on its way.

Sure enough, there are some reasons to doubt that it is happening just yet – American consumers may be saving some of the dollars they are not spending at the gas pump, or driving more miles than before.   But there is no reason to despair, or disbelieve altogether than the US is not going to gain significant impetus from lower energy prices before long.

There are other reasons many people worry about western economies,  most notably rising inequality  and technological threats to labor. There may be hidden bubbles after all the monetary liquidity we’ve had washing around.  I’ll look at those another time – but there’s no reason to think that markets have suddenly become much more concerned about these explanations  since New Year’s Day.

The deeper, different problem

Instead, the most interesting possibility is markets are concerned at a deeper level about what we can call the ammunition argument. Let’s say any of these potential threats materializes.  We don’t have to predict which one, or time it to the day. Then what?

The US recovery is still fragile. The EU is beset by problems of its own making. The central banks are already at or extremely near the zero lower bound for conventional policy. Fiscal policy is more constrained by the massive buildup of debt from the last major collapse. There is much more suspicion (especially in the US Congress) about bank rescues or lender-of-last resort functions, including more legal chains on Fed actions in a crisis.

So if something does go wrong – the Fed misjudges the strength of the recovery and raises rates too much, say, a Chinese credit crisis leads to emerging market commodity disasters which cause strains in European banks who have lent too much money to middle-income countries – there is no ammunition in the locker.

If we take out the rifle to defend ourselves agains the charging bear, we’ll just hear a muted empty “click” and the bear’s jaws will close on our throat. Unlike any other potential crisis in the last hundred years, we’re defenseless.

On this argument, no-one can really predict the stock market (or the Middle East). It’s not a matter of predicting specific outcomes. But if anything goes wrong, we’re bear food.  Talk to Murphy about his law.

And then? This is the deeper fear. Policymakers can’t do anything.  They may stage a few theatrics, write “bang” on a piece of paper and wave it at the bear, perhaps. And whatever they do, they’ll likely mess it up. (They’ll probably misspell “bang”).  It’s also linked to wider suspicions that elites don’t know what they’re doing.

This ammunition argument is the really important question, and deserves more consideration in the next post. It’s probably not true, but it’s a serious argument.

 

By | January 25, 2016|Central Banks, Cyclical trends, Economics, Equities, Financial Crisis, Market Behavior|Comments Off on Market Pessimism: Nothing left to shoot the bear?

How Armchair Economics leads to Arbitrary Assumptions

Even as recently as ten years ago you could get a sustainable advantage in markets and business by having better information. You could have better contacts and sources and data. But the internet has eroded most of that away. Regulators have closed off many other private information channels. The hedge fund industry has struggled (at least in performance terms) ever since rules for equity analysts were tightened around 2003-4.

Of course, it is not too hard to be better informed than the average person on the street (even Wall St). But being sustainably better informed than your closest competitors is almost impossible, and that is what matters. In any case,  the real problem is now usually dealing with too much information.  You’re swamped with it. You’re drowning in it. You don’t have time to read all the information you get.

So the key to performance is now : what you notice in the midst of all the information.  That’s a matter of skill. It’s hard to replicate.  It depends on “feel” and experience, and what you expect to see,  and the assumptions you make.

The assumptions you don’t even realize you are making matter even more, because that is where the problems that lead to market crashes and company bankruptcies and shattered careers usually come from. It’s also where you are most likely to be able to move the needle on performance to the upside.

How do you look for those critical assumptions? That has to be on the mind of every responsible leader. But some of our ingrained habits of thought make the problem much worse. In its attempt to become a general science of rational choice, economics as a discipline has either ignored assumptions or made them for reasons of theoretical tractability, “as if” they reflect real world evidence. Theories become extended development of basic assumptions. Take this (a little bitter) criticism by Herbert Simon in an interview.

Again we have economic theory created in the arm-chair with no empirical evidence?
A. They don’t talk about evidence at all. You read the pages where Lucas talks about why businessmen can’t figure out what’s happened to prices and it is just what he feels as he sits there smoking his cigarettes in his armchair. I don’t know what Keynes smoked, but when you look at the pages where he talks about labor’s money illusion, no evidence is cited. So the real differences in economics, as compared with psychology, is that almost everybody operates within the theoretical logic of utility-maximization in the neoclassical model. When economists want to explain particular phenomena in the real world, they have to introduce new assumptions.The distinctive change in the behavior of the economic actors comes from a change in the behavioral assumptions. No empirical evidence is given to support those changes. They emerge from the mind of the economic theorist sitting in his armchair.

Simon won the Nobel Prize in Economics in 1978, eight years before giving the interview.  If anything, the problem has got worse since, and it shows up in policymaking and the way economists approach markets. When it comes to real decisions, arbitrary assumptions are very often fatal.

By | September 29, 2014|Assumptions, Decisions, Economics, Industry Trends|Comments Off on How Armchair Economics leads to Arbitrary Assumptions

The joke in central bank communications

One of the greatest minds in twentieth-centry strategy was Thomas Schelling, who won the Nobel Prize for Economics in 2005 for his work on game theory back in the 1950s.  Schelling was, however, extremely skeptical about treating strategy as “a branch of mathematics.” According to Lawrence Freedman, Schelling claimed he learned more about strategy from reading ancient Greek history and looking at salesmanship than studying game theory.

So, as often happens, one of the brilliant and creative founders of an abstract approach warned (slightly dimmer) followers against misusing or over applying it.

“One cannot, without empirical evidence,” Schelling observed, “deduce whatever understandings can be perceived in a non-zero-sum game of maneuver any more than one can prove, by purely formal deduction, that a particular joke is bound to be funny .”

Mainstream economics, however, went in a different direction. Now think of what this means for all the economic papers on policy rules and credibility/communication in monetary policy that I referred to in the last post. Most of the problem of central bank communication come from trying to prove by deduction much the same thing as a joke is funny.

By | August 31, 2014|Central Banks, Communication, Economics, Monetary Policy, Quants and Models|Comments Off on The joke in central bank communications

Yellen: More humming-bird than dove

The markets are a little worried about this well-written recent piece about Fed Chair Janet Yellen In the New Yorker. This extract (below) in particular is leading some to wonder whether she will be dangerously dovish and overcommitted to fighting unemployment, and will eventually cause a huge inflationary meltdown.

The more constrained Yellen’s world becomes, the more her instinct will be to return to the distilled essence of herself, the unrepentant Keynesian; the pressure to demonstrate hawkish capabilities comes from without, and the Keynesian inclinations from within. “You can’t think about what is happening in the economy constructively, from a policy standpoint, unless you have some theoretical paradigm in mind,” she told me. Alan Blinder told me that, in the mid-nineteen-nineties, when he and Yellen were both Fed governors and felt they might have momentarily pushed Greenspan into a more dovish position, one of them said to the other, “I think we might have just saved five hundred thousand jobs.” He went on, “We felt pretty good about that. . . . Now she can raise her sights—one million jobs. Two million.”

More and more people are getting uneasy about comparisons to the 1970s. Back then, the Fed misjudged slack in the economy, and dealt poorly with the oil shocks. Inflation got embedded and it took the vicious 1980-1982 recession to restore stability. Being lax about inflation eventually caused the worst unemployment in decades. Is the Fed doing the same thing again, adding a few more shots of tequila to the punch at the party just when everyone needs to sober up and get ready to drive home?

I’d draw a different conclusion from some of the color in the article, however, which matches my own impressions of her. She’s “cautious”, “over prepared”, the “reality” person compared to her much more fiercely partisan husband. She doesn’t like to go out on a limb with extreme positions, such as the incident where she didn’t say much during the big Born/Summers confrontation mentioned in the article. She makes a point of trying to summarize other people’s views at meetings.

In other words, she has a definite point of view, but she ISN’T a flaming ideological partisan firebrand. She is temperamentally pragmatic. Her main Keynesian vice is believing a little too much in aggregate demand as the be-all and end-all. But that is self-correcting given signs of inflation. She is emphasizing unemployment right now because she thinks there is essentially no inflation threat.

Journalists can overemphasize the relevance of academic debates to practical policymaking, because conflict makes for a good story. (Instead, it ‘s usually the unexamined assumptions that everyone agrees about about that cause the most trouble.)

In fact, as I noted here, policy is more incremental in practice. It is made by “muddling through” with tiny adjustments every six weeks, not arguing about questions of ultimate theoretical principle in seminar-room style. Consider: The difference in the Committee’s projected “dots” for timing of raising interest rates is not nearly as large as theoretical differences about economic models.

In fact, it’s likely that Yellen will eventually surprise the markets by flipping towards a focus on inflation more dramatically than expected.

The bigger danger – and this is where the hawks on the FOMC have a legitimate point – is that she will be too activist and overconfident, and will unintentionally cause problems by being too ambitious about what policy can achieve.

First do no harm

The New Yorker article discusses how new classical economists came to believe that monetary policy could achieve little if anything at all. Only Plosser has some sympathy for that extreme view in the committee. All the others think that the Fed can contribute significantly to the economy.

But many acknowledge that the Fed can also make serious mistakesas happened in the 1970s. It quite easy to make the swings and oscillations in the economy even worse. It’s like pushing a kid on a swing. If you give an extra shove when they are at the top of the cycle, you can make the swings even more hair-raising. That produces squeals of delight in children. . but disaster in economic cycles.

The Fed is still giving the largest shove in recorded history to the economy, as QE slowly tapers and nominal interest rates remain at effectively zero, And it is very difficult to get the timing of shoves right. It is typical for economists to be unsure whether the economy has emerged from recession for six months or longer. Data has a habit of getting revised in ways that massively changes the picture of the current economy. Lags are notoriously “long and variable.” For years central bankers has an instinctive distrust of trying to “fine tune” the economy with too much precision as a result.

It’s not the goal of monetary policy, hawk or dove, which is the risk with Yellen. She’s not chained to a dove’s perch. Instead, she’s more likely to be like a humming bird, in frenetic motion. The blur of flapping wings is the risk.

For central bankers, it’s usually better to me like an eagle, hardly twitching a muscle, patiently watching and floating high above the fray below, and then striking at just the right moment.

By | July 25, 2014|Central Banks, Current Events, Cyclical trends, Economics, Federal Reserve, Monetary Policy|Comments Off on Yellen: More humming-bird than dove

Picking higher-hanging fruit

Pessimism about technology and growth has become fashionable recently, following arguments by Robert Gordon and Tyler Cowen. The “low-hanging fruit” is gone, says Cowen in The Great Stagnation: How America Ate All the Low-Hanging Fruit of Modern History.

The great economic historian Joel Mokyr is having none of it, however. People develop better tools, which lead to better new technologies, which lead to better tools.

If this historical model holds some truth, the best may still be to come for modern societies. Only in recent decades has science learned to use high-powered computing and the storage of massive amounts of searchable (and thus accessible) data at negligible costs. The vast array of instruments and machines that can see, analyze, and manipulate entities at the sub-cellular and sub-molecular level promise advances in areas that can be predicted only vaguely. But these tools, to beat Cowen’s metaphor into the ground, allow us to build taller ladders to pick higher-hanging fruit. We can also plant new trees that will grow fruits that no one today can imagine.

I previously mentioned Mokyr here, especially the interaction between formal expertise and practical know-how in the take-off of the industrial revolution.

The question is, of course, how it affects the labor market.

 

By | April 5, 2014|Adaptation, Economics, Organizational Culture and Learning, Technology|Comments Off on Picking higher-hanging fruit

What bad-tempered cows can tell us about economic policymaking

The economic models policymakers and academics use can sometimes be very remote from practical experience. Actual decision-makers know that theories and plans are often of little help, and can sometimes be outright dangerous.

One American teenager learnt that the hard way when he joined with some friends to try to raise cattle on a desolate stretch of land in Wisconsin, named Rock Marsh.  The cattle wandered into flooded land or got caught on fences or failed to thrive in the winter. Bad-tempered cows did not cooperate with the plan.

But unlike most teen ventures, Herbert Simon took the experience and eventually turned it into a Nobel Prize in Economics in 1978. As he puts it in his autobiography, Models of My Life:

In essence our failure was a vivid demonstration, which I have never forgotten, that theories, however plausible and “obviously” valid, can be destroyed totally by the obstinate facts of the real world… No doubt my later deep skepticism of the a priorisms of mainstream economics had some of its origins in this experience.

Simon is one of the titanic intellectual figures of the last century. As the lines here hint, he was no orthodox economist, despite winning the Nobel  “for his pioneering research into the decision-making process within economic organizations.” For most of his career he worked outside economics altogether. He followed his interest in how people actually make decisions into psychology and computing and organization science.

He is also  one of the founding fathers of modern cognitive psychology, which  led to the “cognitive revolution” in many disciplines today. He did massively important work in the study of expertise and human problem solving. He investigated complex adaptive systems. And he was one of the main pioneers of artificial intelligence and machine learning, which is the forerunner of many of the algorithms and approaches underlying modern software engineering.

But he is most known for his investigation into “bounded rationality”.  People, he said,  do not have the capacity or knowledge to make optimal decisions in the way mainstream neoclassical economics believes (or at least assumes for working purposes.) Instead, they look for and find solutions which are “good enough”, or as he called it, they satisfice. They make decisions within and through organizations. They use different representations of problems.

Why does it matter? I’ve been looking at how our understanding of decision-making has evolved since WW2. Mainstream economics and finance continue to be based essentially on the microeconomics of expected utility which Simon attacked in the 1950s –  albeit in the last decade or two with small tweaks from Kahneman & Tversky’s Prospect Theory and other kinds of behavioral economics. But beginning in the 1960s more and more work surfaced which showed the standard economic view of the way people make decisions had major gaps and flaws.

Simon’s approach did not in the end prevail in the Economics Department of even his own university, Carnegie-Mellon. The career imperatives and mathematical requirements for economists were too strong to resist. As a result, most PhD-educated economists still stick very much to traditional methodologically-individualist, constrained-optimization approaches. Much of the standard analysis of the economy and markets contains  serious blind spots as a result.

Sometimes bad-tempered cows are more useful than an economics PhD from MIT.

By | March 28, 2014|Adaptation, Decisions, Economics, Expertise, Organizational Culture and Learning|Comments Off on What bad-tempered cows can tell us about economic policymaking