Reasons for "apparent status quo" bias at the Fed

As a follow-up to my last post, I want to think out loud a little more about why the Fed should have a bias toward doing nothing. Warning: these thoughts just came off the top of my head, and may be crazy. But anyway...

For a doctor, status quo bias makes sense, because of the principle of "first do no harm". For a government, status-quo bias in the form of laissez-faire bias makes sense when you believe in free markets. But the Fed is different. Because for the Fed, "doing nothing" is not really doing nothing! Even when the Fed is keeping interest rates unchanged and refusing to engage in quantitative easing (as it is now), it is still printing money, and it is still managing expectations. (In fact, since silence affects expectations differently the longer you keep it up, Fed policy is always changing even if the Fed clams up completely!) What looks like the "status quo" is really only the apparent status quo.

So why would the Fed have a natural bias toward seeming to do nothing? I thought about it, and came up with the following reasons:

1. Internal politics bias. The Fed's decisions are probably dependent on some sort of internal decision-making procedure in which the opinion of the different governors are taken into account in some way. Current Fed actions reflect a balance between hawks and doves. As long as this balance is stable, the Fed will be biased away from taking any apparent actions. Only outside events or a change in the opinions or composition of the factions within the Fed will alter the balance of power.

2. Reputational bias. Anything the Fed does is going to make someone mad. People pay more attention to things that make them mad than to things that please them. And people pay more attention when the Fed is in the news (i.e. when it appears to do something) So any action that the Fed appears to take is going to result in negative attention directed at the Fed chairman. The Fed chairman, being human, probably doesn't enjoy negative attention. So this is a reason for the Fed chairman to keep a low profile by seeming to do nothing.

3. Credibility bias. Again, people tend only to pay attention to what the Fed seems to do, rather than what  the Fed actually does. And each time the Fed seems to do something, it makes people more uncertain as to what the Fed actually wants, what it knows, what it believes, and what it is planning to do. The Fed values credibility, so it will seek to minimize taking headline-grabbing actions that make people actively wonder what the Fed is going to do in the future.

4. Asymmetric model uncertainty. This applies specifically to the Fed's reluctance to engage in quantitative easing. Paul Krugman has discussed this before. To make a long story short, history has seen many changes in the Federal Funds rate, but not many instances of QE, so it's more difficult to select a model to give you guidance when contemplating QE than when contemplating routine open-market operations. Therefore, to do QE, you have to take a much bigger leap of modeling faith. This will bias the Fed toward apparent inactivity when short-term nominal interest rates are at the Zero Lower Bound, as they are now.

So these are some reasons why Fed policy might currently be "stuck". Hawks inside the Fed are not strong enough to make Bernanke raise interest rates, and this will probably be the case for the foreseeable future. But a combination of reputation bias, credibility bias, and model uncertainty make Bernanke very reluctant to engage in further QE. And a combination of reputation bias and credibility bias make Bernanke reluctant to make additional statements about future Fed policy.

So what can academic economists do to convince Bernanke to do more QE? Well, they can write papers about QE, thus reducing (slightly) model uncertainty. They can try to get the public to realize that Fed "inaction" is really just stealth action, by couching their public complaints in different terms ("Why is the Fed doing X" rather than "Why is the Fed doing nothing"). But these efforts are not likely to have huge success. Is there any other way to reduce "apparent status quo" bias? I'm not sure.

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Macro: intuition vs. theory

Two items regarding macro policy have caught my eye this past week. The first is Gideon Rachman arguing for fiscal austerity. The second is Paul Krugman's assertion that Ben Bernanke has been assimilated by the hard-money Borg.

Why are all these people arguing for things like hard money and austerity? Do they believe in some model - some RBC variant, perhaps - that tells them that now is not the time for quantitative easing and fiscal stimulus? If so, they aren't publicizing the fact. My guess is that it's not really about models and theories at all - policymakers and pundits basically don't buy into any macro model, and so are falling back on their own reflexive intuition.

First, take Rachman. His arguments for European austerity are far weaker than his typical logical perspicacity would lead one to expect.

First, he argues that infrastructure spending in Greece and Spain over the past 30 years failed to prevent the current crisis. But that is obviously irrelevant, since Greece and Spain grew robustly before the crisis, and no advocate of stimulus believes that infrastructure spending will prevent recessions in the future.

Second, Rachman points out that European debt levels are already high. But if you broke your arm and didn't have health insurance, it would be moronic to say "Well, I'm already deeply in debt, so I shouldn't borrow any more money to treat my broken arm." If austerity hurts growth - and there is strong evidence that it does - then existing debt levels are irrelevant.

Third, Rachman says that Europe's real task is structural reform. This opinion echoes that of economists like John Cochrane. But does the case for structural reform affect the case for countercyclical fiscal policy? No. Because unless you believe that bad business environments cause recessions, improving structural factors won't stop the business cycle.

So Rachman is making weak arguments (for a more constructive rebuttal, see Ryan Avent). Why? Rachman is a smart, reasonable guy. My guess is that he doesn't really believe in any model or theory of the macroeconomy, and he's just recommending austerity because it sort of seems prudent. After all, spending more than you earn is usually a bad idea, right? I mean, come on, everybody knows that, it's obvious. It's "common sense". Economic theories, like all scientific theories, are built to be counterintuitive - if our common sense was sufficient to allow us to understand the economy, we wouldn't need science. By chucking theory and saying "Come on, cut the crap, everyone knows that austerity is the sensible, responsible, prudent thing to do," Rachman is implicitly saying that economic science is crap and common sense is all you need.

Now, Ben Bernanke. Paul Krugman points out that as a professor, Bernanke wrote papers that advocated quantitative easing; now, as a policymaker, he's much more shy about doing it. Krugman's explanation is social; being around a bunch of hard-money Fed guys (who are obsessed with the Fed's inflation-fighting credibility but blase about the Fed's depression-fighting credibility) has swayed Bernanke by good old peer pressure.

I have a somewhat different hypothesis: I think Bernanke is dealing with a severe case of model uncertainty. Think about it. A professor's job is to say "Here is a way the world might work." A policymaker has to say "OK, I am going to act as if the world works this way." The latter requires a LOT more faith in the model's correctness than the former. It seems highly likely to me that Fed Chairman Bernanke does not believe in Professor Bernanke's theories enough to make big bets on them.

The more I read about monetary policy, the more convinced I become that humankind does not really understand it very well. With some assumptions - a certain kind of price stickiness, for example - you can derive an optimal monetary policy rule. But those assumptions are almost certainly crap, included for mathematical tractability (e.g. Calvo pricing), or capturing only one small piece of what's really going on. When you're a policymaker, you don't care about mathematical tractability, and you can't afford to focus only on one piece of what's going on.

The fact is, we just don't know what monetary policy is the best. Maybe QE is a good idea (I think it is!). Maybe a rule like NGDP level forecast targeting is a good idea (I am skeptical but it doesn't sound too bad). Or maybe the amount of QE needed to produce a noticeable movement in employment is so huge that it really would cause serious inflation. Maybe monetary policy operates with "long and variable lags," as Milton Friedman suggested, meaning that it's very difficult for the Fed to know the consequences of its actions. I am not economically illiterate. I can easily find, read, understand, and explain a paper supporting any of these contentions. But at the end of the day I'm willing to bet you that I won't really know how right the paper is. At best, my opinions will probably only have shifted slightly. I am guessing this because I've never read a monetary policy paper that convinced me that "OK, this has got to be how the world works."

So I think that Ben Bernanke has been paralyzed into inaction by the realization that, his academic papers aside, he doesn't really know if QE would be good or bad.

So the upshot of this blog post is this: People do not believe in macro models. Macroeconomics is not a science that has, as of May 2012, proven itself in the way that chemistry, biology, or various branches of microeconomics have proven themselves. And so when push comes to shove - as it has - people fall back on their gut reactions, going "Hrrrrrm, austerity, yes, prudent!" or "Hrrrrrm, inflation, yes, scary!" Do I disagree with this Hrrrrrrm-ing?? Sure! MY intuition says something different. And I think the academic literature supports my position more than that of the austerians and hard-money people. But I understand how model uncertainty makes the case for stimulus and QE less than a slam-dunk.

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Why I could be a much better economist than I am

Most economists would not admit in public that they are anything less than virtuosos at what they do. But I am not "most economists". So I'll admit it: in many ways I am not that great of an economist. The part that gives me trouble is not the math - there's nothing in most econ papers that I didn't do as a sophomore in undergrad. The part that gives me trouble is the intuition.

Applied math disciplines, like physics and economics, are about 30% math skill and 70% intuition. History bears this out. Einstein, generally considered the greatest physicist of the 20th century, was no great mathematician; he needed help from Poincare, Hilbert, Minkowski, and other pure math people to work out some of the trickier aspects of relativity. But where Poincare, for example, failed to intregrate the math of special relativity (which he invented) into the rest of physics theory, Einstein's unmatched intuition allowed him to do this.

Physics was always my best academic subject by far, because I had that knack for intuition. Friends of mine who were absolutely brilliant at math (including one who published math papers in high school and now teaches at Harvard) would try taking physics classes with me, and I would end up helping them, because for some reason I could "think like a physicist" in way that allowed me to circumvent the need for tedious calculations. For example, what's the force on a charged particle that is near to a charged sheet? If you start from the math, you integrate the force from all elements of the charged sheet; it takes a few minutes of your time. But if you understand intuitively how electric fields work, you can use something called Gauss' Law to find the answer instantly; no time-wasting integral needed. If you can switch rapidly back and forth between this "symmetry" approach and the standard "furious calculation" approach as needed, you'll do well on physics tests and theory research too.

Anyway, to make a long story short, this approach never worked as well for me in economics. There are some things I seem to have good intuition for, like Bellman equations and search models. There are some things I didn't have any intuition for when I started, but got more with practice (game theory). And then there are some things that have stubbornly resisted my attempts to understand them instinctively. Much of macroeconomics falls under this heading. Reading most macro papers, I can follow the math, but I have no idea why the modeler chose to do things the way they did, and I wouldn't have been able to invent the same model if someone had told me to model the same phenomenon. This is true not only for original, breakthrough stuff, but for pedestrian models that are small tweaks on existing models.

I've wondered why this is, and I've concluded that it's mostly because there are few bedrock principles I can go back to. Example: I was sitting around with an economist friend and spinning a story about why financial market failures might make people stop working during recessions. He furrowed his brow and asked me "But how can that make people work more during booms?" To which I had no answer. It hadn't occurred to me, until that moment, that increased labor supply (or increased capital usage) was necessary for a boom. That's a simple concept, and it was built into all the models I had studied and worked through in class, but the fact of it had eluded me!

So of course I answered "Well, maybe there are no such things as 'booms', maybe what we see as 'booms' are just a normal-functioning economy, and any downward deviation in employment or growth is just a market failure." And of course, it's possible to build models like that, and maybe it's even true! But still, without understanding and accepting the idea that labor supply exceeds its sustainable long-term level during a "boom," it's hard to understand most of the popular business cycle models on a deep, intuitive level, because most of them attempt to explain the "phenomenon" of fluctuations of output and unemployment around a trend.

Another example is labor market clearing. I never really managed to pound into my head the notion that labor markets clear (because hey, unemployment exists!). And of course there are models in which labor markets don't clear, but these models are generally built by starting with a model in which labor markets clear, and then adding a friction (e.g. sticky wages) to stop them from clearing. I would have had a hard time making such models. And, perhaps of more immediate importance, I sometimes forgot the labor market clearing condition on tests! I'd be sitting there thinking "How do I close this system of equations?" for 5 or 10 minutes before I slapped my head and thought "Duh, labor market clearing!" This is in contrast to physics, where I'd whip out Gauss' Law pretty much instantly. This is the kind of dumbness that mathematical sophistication can't prevent; you can't solve a system of equations until you know which equations to write down!

(Side note: Another problem I have when making macro models is that I can't really decide which stylized facts I want to try to explain, mainly because I don't really believe in time-series econometrics, and hence I don't believe in most stylized facts. This is a somewhat different issue, though.)

Now, anyway, what I could do would be to say "Actually, it's not my fault, it's the discipline's fault. The economics Overmind has pounded a bunch of notions into people's heads that aren't really true; the only reason good macroeconomists can make their models so easily is that they share the same bunch of wrong assumptions." That would fit with the irreverent, pugnacious tone of this blog. But is isn't really true. A good economist - especially a macroeconomist - can master a form of doublethink. "I know this assumption isn't true," (s)he thinks, "but to make this model I need to act like I believe it's true." This is a trick I haven't really mastered, and it probably has more to do with my lack of an undergrad economics education than with the wholesale brainwashing of the entire econ profession.

In physics, you don't have to use doublethink, because the laws and principles you use really are true; even if you neglect friction, for example, you've probably got a good description of the motion of a hockey puck or a satellite. Econ is more about building toy worlds that don't exist - can't exist - anywhere, just to clarify your thinking. This is a mental skill that is probably best learned at age 18, and I was 26 when I started learning econ.

So, for example, I wouldn't easily be able to write anything like Larry Summers' critique of RBC models. Summers has the intuition to understand quickly, but at a very deep level, how these toy economies work and what makes them tick. I don't. And so my critique of RBC would be something more along the lines of "What are you even talking about?!" Which makes more for a cathartic blog rant than a thoughtful academic rebuttal.

Anyway, fortunately for me, I discovered (late in the game) that I have a much better intuition for finance theory (and, increasingly, for game theory!) than for macro. You don't always have to use doublethink. The CAPM might be an excellent description of risk under certain conditions. For worlds where only a certain kind of frequent, routine change occurs, Black-Scholes is probably a great model of option value.  And the decision problems of single agents trying to maximize simple utility functions in complex environments are a lot easier for my brain to work with. So I think I made the right move, in terms of transitioning toward a field where the mental techniques I learned in my undergrad physics classes have a better chance of succeeding.

But I still wish I was better at doing the other kind of economics - the doublethink, the useful oversimplification, the internally consistent fantasy storytelling. Well, I guess everyone needs goals to work toward...

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Creeds, screeds, mockeries, Thackerays...

In my last post, I snarked that "I also think, incidentally, that maybe [libertarians] should reconsider the perfection and rightness of their ideology."

To which one of my commenters responded with an off-the-cuff masterpiece of sheer lulzy brilliance. From commenter JohnR:

Oh, c'mon now; no religion ever wants to be the first one to do that. What we'll see first is a schism, where the Galtians decide that the Roarkians are virulent heretics deserving of the harshest punishment ("She's a witch!") and they both agree that Ron Paul is an apostate if not a vile blasphemer. Soon the fun will start and there will be sects, sub-sects, deviant sects, consensual sects, chemically-enhanced sects, incense-free sects, creeds, screeds, mockeries, Thackerays, Inquisitions, Crusades, Reformations, Restorations, Abominations and Free Love. Only then will the One True and Holy Church of Rand be fully established as the single pure essence of Libertarianism, with the ruling that the other 7,843 "Libertarian" churches are merely cults to be stamped out with an iron boot.

Wow. All I can say is, when this happens, I hope my house is well-stocked with popcorn, because it's going to be fun to watch.

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Giant Thursday Roundup (4/26/2012)

Work is getting more demanding again, as I teach myself how to teach finance classes. Thursday Roundup will have to take a break in the month of May. But in the meantime...

1. Simon Wren-Lewis has a great piece about modern macro methods and publication bias, and by "great" I naturally mean "agrees with stuff I've said in the past"...check out this money quote he pulls from John Muelbauer:

While DSGE models are useful research tools for developing analytical insights, the highly simplified assumptions needed to obtain tractable general equilibrium solutions often undermine their usefulness. As we have seen, the data violate key assumptions made in these models, and the match to institutional realities, at both micro and macro levels, is often very poor.

I feel like I've been saying this for quite some time...good to see I'm not alone...

2. Go read this great piece in The Atlantic on why we need more high-skilled immigration, and we need it NOW! If you still are afraid that high-skilled immigrants will TAKE YER JERBS, do a big and immediate rethink! High-skilled immigrants will CREATE YER JERB.

3. JW Mason argues against Roger Farmer's assertion (on this blog) that disequilibrium dynamics should be ignored.

4. Tyler Cowen has more on Baby Boomer retirement and the labor force participation rate. Still doesn't seem to explain the bulk of the current unemployment, but could make a difference as the economy recovers.

5. John Cochrane explains how a run on a money market fund works. A money market fund is not really "money"!

6. Mark Thoma and Tim Taylor point out something incredibly important that few people realize: U.S. government purchases have been going down, down, down. What has been going up are transfer payments.

7. Matt Yglesias attempts a rebuttal of my grandadvisor Greg Mankiw on the notion that rich people move to flee high taxes.

8. Paul Krugman argues that no, printing money doesn't distribute money away from the middle class.

9. Krugman also referees an Yglesias/Avent debate on the Zero Lower Bound, and concludes that the ZLB is not just psychological.

10. The Economist magazine has a neato series on the rise of 3D printing and what it means for manufacturing.

11. Tyler Cowen on Japan's cursed financial equilibrium. Someday it will end in a Japanese default. That day is likely to come within the decade. I may be the only person on the planet who thinks this will be a good day for the Japanese economy...

12. Frances Woolley does a great (and lengthy) Econ 101 explanation of why tax cuts are unlikely to increase government revenues. I expect every Republican and supply-sider out there to read it immediately, be convinced, and change their policy stance on this important issue .

13. Calculated Risk shows us the updated state of the housing bubble, in pictures. Noah summary: the bubble has entirely deflated, but "undershoot" may still push prices a bit lower before they bottom.

14. Joseph Stiglitz, Nobel Prize-winning economist and former physics major, blames the economics discipline for the global financial crisis.

15. Brad DeLong: What the world needs is for the "strong dollar" policy - in other words, the dollar's reserve currency status - to end, and end now.

16. Guess which sector has been responsible for the bulk of the job losses during this unusually weak recovery? Construction? No. Finance? Ha. It's government, yo. Paul Krugman has more. This of course reflects on the (lack of) wisdom of austerity. But it also makes me wonder if the real wages of government workers should be made more flexible...

17. Mike the Mad Biologist unleashes Philosophy of Science against Zombie Milton Friedman. Black box models are not enough!

18. Paul Krugman discusses how slowly "internal devaluation" takes effect. This is something I've argued with JW Mason about in the past. I still maintain that internal devaluation is better than nothing, especially when other countries peg their exchange rates to yours. But I of course agree that other countries not pegging their exchange rates to yours is the best solution, if you can make it happen.

19. Julian Sanchez argues that libertarians shouldn't use meritocracy as an argument for their ideology, and I agree. I also think, incidentally, that maybe they should reconsider the perfection and rightness of their ideology...

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Neither Real, nor Business, nor Cycles

It has often been said of the Holy Roman Empire that it was "neither Holy, nor Roman, nor an Empire." However, that joke has gotten a bit stale since Voltaire wrote it in the 1700s, so I think it's time for a new one. Real Business Cycle models, it turns out, are neither Real, nor about Business, nor about Cycles.

They are, however, the macro models that annoy me far more than any other (and I'm not alone). I'll explain the joke in increasing order of the things that annoy me.

First, "Cycles". The "business cycles" in RBC models are not periodic, like cycles in physics. But they are also not "cycles" in the sense that a bust must follow a boom. Booms and busts are just random shocks. The "business cycle" that we think we see, according to these models, is simply a statistical illusion. (Actually, RBC shares this property with New Keynesian and Old Keynesian models alike. Very few people dare to write down a model in which knowing you're in a boom today allows you to predict a bust tomorrow!)

Next, "Business". Businesses are called "firms" in economic models. But if you look at the firms in an RBC model, you will see that they bear very little resemblance to real-life firms. For one thing, they make no profits; their revenues equal their costs. For another thing, they produce only one good. (Also, like firms in many economic models, they are all identical, they live forever, they make all their decisions to serve the interests of households, and they make all decisions perfectly. Etc. etc.) In other words, they display very few of the characteristics that real businesses display. This means that the "business cycle" in an RBC model is not really the result of any interesting characteristics of businesses; everything is due to the individual decisions of consumers and workers, and to the outside force of technological progress.

Finally, "Real". This is the one that really gets me. "Real" refers to the fact that the shocks in RBC models are "real" as opposed to "nominal" shocks (I've actually never liked this terminology, since it seems to subtly imply that money is neutral, which it isn't). But one would have to be a fool not to see the subtext in the use of the term - it implies that business-cycle theories based on demand shocks are not, in fact, real; that recessions and booms are obviously caused by supply shocks. If RBC is "real", then RBC's competitors - Keynesian models and the like - must be fantasy business cycle models.

However, it turns out that RBC and reality are not exactly drinking buddies. I hereby outsource the beatdown of the substance of RBC models to one of the greatest beatdown specialists in the history of economics: the formidable Larry Summers. In a 1986 essay only slightly less devastating than his legendary dismissal of the Winklevoss twins, Summers identified three main reasons why RBC models are not, in fact, real:

1. RBC models use parameter values that are almost certainly wrong,

2. RBC models make predictions about prices that are completely, utterly wrong, and

3. The "technology shocks" that RBC models assume drive the business cycle have never been found.

I encourage everyone to go read the whole thing. Pure and utter pulpification! Actually, this essay was assigned to me on the first day of my intro macro course, but at the time I wasn't able to appreciate it.

So Real Business Cycle models are neither Real, nor about Business, nor about Cycles. Are they models? Well, sadly, yes they are...of a sort. You actually can put today's data into an RBC model and get a prediction about future data. But see, here's the thing: that prediction will be entirely driven by the most ad-hoc, hard-to-swallow part of the model!

Basically, here's how an RBC model works. You take every factor of production you can measure - capital, labor, inventories, etc. - and you factor it out, and then you're left with the part of production you can't explain, which is called the "residual". You then label this residual "technology", and you assume that it moves according to some sort of simple stochastic process - for example, an AR(1). The rest of the model is just a description of the ways in which the rest of the economy responds to that AR(1) technology "process". In RBC models, this response is usually as simple and uninteresting as possible; pretty much everything is driven by the uber-simplistic movement of "technology".

In other words, if I want to make a forecast using an RBC model, that forecast will be based on the assumption about tomorrow's level of "technology" - i.e. the part of the model that doesn't come from data we can directly measure - and that level, in turn, will be "predicted" by nothing more than the simplest stochastic equation imaginable! As you might therefore expect, RBC models do not do so well at forecasting the future (though, to be fair, a few disagree with that assessment).

(Note that this makes RBC a glaring example of what I call "Label-the-Residual Economics", in which the economist assumes that the part of the world that we can't measure is the Mysterious Force that drives everything, but that we can accurately predict the future behavior of this Mysterious Force.)

Now, some work has been done on improving RBC models since their inception - instead of technology, for example, some modelers try to tie business cycles to news about technology. But most of the macro profession has moved on to other types of DSGE models, especially new Keynesian models. And yet the RBC paradigm persists, especially at certain universities. Why? In a recent blog post, Simon Wren-Lewis lays out this case that's it all about the politics:

In RBC models, all changes in unemployment are voluntary. If unemployment is rising, it is because more workers are choosing leisure rather than work. As a result, high unemployment in a recession is not a problem at all...workers choose to work less and enjoy more free time... 

If anyone is reading this who is not familiar with macroeconomics, you might guess that this rather counterintuitive theory is some very marginal and long forgotten macroeconomic idea. 

You would be very wrong. RBC models were dominant in the 1980s, and many macroeconomists still model business cycles this way. I have even seen textbooks where the only account of the business cycle is a basic RBC model... 

One explanation [for RBC's popularity] is ideological. The commonsense view of the business cycle, and the need to in some sense smooth this cycle, is that it involves a market failure that requires the intervention of a state institution in some form. If your ideological view is to deny market failure where possible, and therefore minimise a role for the state, then it is natural enough (although hardly scientific) to ignore inconvenient facts. For the record I think those on the left are as capable of ignoring inconvenient facts: however there is not a left wing equivalent of RBC theory which plays a central role in mainstream macroeconomics.

Whether Wren-Lewis is right about this or not, I think the continued semi-popularity of RBC models definitely shifts the field of macro toward more politically conservative policy recommendations. It does this by shifting the "Overton Window". Without a strong RBC presence, macro might be primarily a debate between New Keynesians and Old Keynesians, or New Keynesians and complexity theorists, or New Keynesians and people who think we just don't know enough to really model the business cycle yet. In other words, it might be a debate between people who think that the economy can be managed effectively by central bank monetary policy, and people who think deeper government interventions are warranted. Instead, for the past two decades, academic macro has been primarily a debate between New Keynesians and RBC people - a debate between minimal-interventionists and those who oppose any sort of government intervention at all. In the "freshwater-saltwater" debate, supporters of things like fiscal stimulus were left high and dry.

At any rate, this bit about politics is a digression. The central point of this post is that Real Business Cycle models, whether politically motivated or not, are massively oversold as descriptions of the recessions and booms that we observe and live through. People should know that they contain neither Reality, nor Business, nor Cycles.

How long did it take the Holy Roman Empire to finally give up the ghost? Depressingly, it was more than half a century after Voltaire made his little joke...

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Venture capital is sucking (your money)

Many of America's tech startups are funded by venture capital. But why on earth would any venture capitalist invest in a risky, unproven new company with a risky, unproven new technology? Answer: High risk goes hand in hand with high returns. Most of the new companies will fail, but the ones who succeed will be huge, more than making up for all the failures. 

Well, that's the theory anyway. If venture capital is taking all that risk and not making stellar returns, then something is severely broken.  

Friday's finance seminar here at UMich was by Steven Kaplan of the University of Chicago's Booth Business School, who presented a paper he's writing with Robert Harris and Tim Jenkinson entitled "Private Equity: What Do We Know?". In this context, the term "private equity" refers both to buyout firms (i.e. what we normally call "private equity") and venture capital firms. The paper is all about measuring the returns that these industries have earned in recent decades.

Most of the talk focused on the buyout industry; only in the last few minutes did Kaplan actually get to talk about VC. But when he did, what I saw made my eyes bug out! Here is the key picture from the paper:

The different lines represent not different VC firms, but different data sources - each line is the average across all VC firms studied. On the x-axis we have "vintage" year, which is the year a firm started investing. On the y-axis we have the Private Market Equivalent ratio, which is a measure of how well funds did relative to the S&P 500 (a PME of greater than 1 means that a fund beat the S&P). Thus, if a line is at PME=2.5 at 1995, it means that, on average, VC firms that started investing in 1995 made 2.5 times the return of U.S. public stocks in general.

So what happened was that before the dot-com bubble burst in 2000, VCs did amazingly well. In the decade since, they've done slightly worse than the S&P 500 - in other words, they've done so poorly that you'd have been  better off buying Ye Olde Vanguard 500. And when you factor in risk, the comparison isn't even close; venture capital has a beta of well over 1, meaning that VCs are exposed to more aggregate risk than an index fund.

In other words, since the end of the dot-com bubble, venture capital has proven to be a sucker's bet. 

Now, you can respond by saying "OK, sure, but that's only one decade. What we really care about are longer-term returns." And maybe that's right. Maybe VC returns will eventually bounce back, justifying this long fallow period. BUT, whether poor VC performance in the 2000s was structural or random is something we won't be able to know for a long long time - not until we've gathered a statistically large sample of VC performance. By that time, you and I will probably be retired or dead. 

In the meantime, all we can do is guess. And dang it, but that graph sure looks like a structural break to me.  Something looks like it broke the VC business model after the dot-com crash. Maybe the new tech bubble (Facebook, etc.) will pump those returns back up, but there have been some big IPOs and some big acquisitions in Tech Bubble 2.0, and VC returns haven't really bounced back yet, so I'd be cautious. What's more, I'm starting to read about a slump in venture funding...

Could this be the (temporary) end of the VC industry? If so, is it a harbinger of technological stagnation, or simply the passing of a financial fad?

(Oh, one more thing. Kaplan et al. find that buyout firms, in contrast to VCs, have consistently beat the market over the last three decades or so. Maybe that has something to do with that enormous tax break they get for buying up firms, loading the firms up with debt, and then paying themselves a dividend while leaving the firm to die...)

Update: An anonymous commenter suggests that a few VC firms manage to consistently beat the market. It turns out she's right (at least as of 2005). This paper, also by Steve Kaplan, shows that VC firm performance is persistent; those firms that make good returns in one period are likely to make good returns in the next period. VC firm performance also appears to be highly skewed - a few firms are making most of the money. Together, these two facts suggest that there are a few really skilled VCs out there who invest successfully year after year, and a large number of truly abysmal VC firms that drag the total return way down. This begs the question of who is throwing money at all these awful VC firms when there are proven winners out there! One possibility is that the "winner" firms limit the amount of capital they are willing to accept; they know that there is a limited number of good projects, and that if they get too big they won't be able to keep returns high. This means that if an investor wants to invest in VC, she may simply not be able to give her money to one of the "winner" firms. This explanation would be bad news for proponents of market efficiency, but would be consistent with the picture of overall stagnation in the VC-funded part of the tech industry, since the driver of low returns would still be the limited number of good new tech ventures.

Update 2: Peter Thiel explains some reasons why a lot of VC funds fail.

Update 3: More reasons the VC model is broken.

Update 4: Here's a Felix Salmon blog post saying essentially the same thing as this post, except with many more charts, graphs, and explanations.

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