What would a new macroeconomics look like?

Dec 9 JDN 2458462

In previous posts I have extensively criticized the current paradigm of macroeconomics. But it’s always easier to tear the old edifice down than to build a better one in its place. So in this post I thought I’d try to be more constructive: What sort of new directions could macroeconomics take?

The most important change we need to make is to abandon the assumption of dynamic optimization. This will be a very hard sell, as most macroeconomists have become convinced that the Lucas Critique means we need to always base everything on the dynamic optimization of a single representative agent. I don’t think this was actually what Lucas meant (though maybe we should ask him; he’s still at Chicago), and I certainly don’t think it is what he should have meant. He had a legitimate point about the way macroeconomics was operating at that time: It was ignoring the feedback loops that occur when we start trying to change policies.

Goodhart’s Law is probably a better formulation: Once you make an indicator into a target, you make it less effective as an indicator. So while inflation does seem to be negatively correlated with unemployment, that doesn’t mean we should try to increase inflation to extreme levels in order to get rid of unemployment; sooner or later the economy is going to adapt and we’ll just have both inflation and unemployment at the same time. (Campbell’s Law provides a specific example that I wish more people in the US understood: Test scores would be a good measure of education if we didn’t use them to target educational resources.)

The reason we must get rid of dynamic optimization is quite simple: No one behaves that way.

It’s often computationally intractable even in our wildly oversimplified models that experts spend years working onnow you’re imagining that everyone does this constantly?

The most fundamental part of almost every DSGE model is the Euler equation; this equation comes directly from the dynamic optimization. It’s supposed to predict how people will choose to spend and save based upon their plans for an infinite sequence of future income and spending—and if this sounds utterly impossible, that’s because it is. Euler equations don’t fit the data at all, and even extreme attempts to save them by adding a proliferation of additional terms have failed. (It reminds me very much of the epicycles that astronomers used to add to the geocentric model of the universe to try to squeeze in weird results like Mars, before they had the heliocentric model.)

We should instead start over: How do people actually choose their spending? Well, first of all, it’s not completely rational. But it’s also not totally random. People spend on necessities before luxuries; they try to live within their means; they shop for bargains. There is a great deal of data from behavioral economics that could be brought to bear on understanding the actual heuristics people use in deciding how to spend and save. There have already been successful policy interventions using this knowledge, like Save More Tomorrow.

The best thing about this is that it should make our models simpler. We’re no longer asking each agent in the model to solve an impossible problem. However people actually make these decisions, we know it can be done, because it is being done. Most people don’t really think that hard, even when they probably should; so the heuristics really can’t be that complicated. My guess is that you can get a good fit—certainly better than an Euler equation—just by assuming that people set a target for how much they’re going to save (which is also probably pretty small for most people), and then spend the rest.

The second most important thing we need to add is inequality. Some people are much richer than others; this is a very important fact about economics that we need to understand. Yet it has taken the economics profession decades to figure this out, and even now I’m only aware of one class of macroeconomic models that seriously involves inequality, the Heterogeneous Agent New Keynesian (HANK) models which didn’t emerge until the last few years (the earliest publication I can find is 2016!). And these models are monsters; they are almost always computationally intractable and have a huge number of parameters to estimate.

Understanding inequality will require more parameters, that much is true. But if we abandon dynamic optimization, we won’t need as many as the HANK models have, and most of the new parameters are actually things we can observe, like the distribution of wages and years of schooling.

Observability of parameters is a big deal. Another problem with the way the Lucas Critique has been used is that we’ve been told we need to be using “deep structural parameters” like the temporal elasticity of substitution and the coefficient of relative risk aversion—but we have no idea what those actually are. We can’t observe them, and all of our attempts to measure them indirectly have yielded inconclusive or even inconsistent results. This is probably because these parameters are based on assumptions about human rationality that are simply not realistic. Most people probably don’t have a well-defined temporal elasticity of substitution, because their day-to-day decisions simply aren’t consistent enough over time for that to make sense. Sometimes they eat salad and exercise; sometimes they loaf on the couch and drink milkshakes. Likewise with risk aversion: many moons ago I wrote about how people will buy both insurance and lottery tickets, which no one with a consistent coefficient of relative risk aversion would ever do.

So if we are interested in deep structural parameters, we need to base those parameters on behavioral experiments so that we can understand actual human behavior. And frankly I don’t think we need deep structural parameters; I think this is a form of greedy reductionism, where we assume that the way to understand something is always to look at smaller pieces. Sometimes the whole is more than the sum of its parts. Economists obviously feel a lot of envy for physics; but they don’t seem to understand that aerodynamics would never have (ahem) gotten off the ground if we had first waited for an exact quantum mechanical solution of the oxygen atom (which we still don’t have, by the way). Macroeconomics may not actually need “microfoundations” in the strong sense that most economists intend; it needs to be consistent with small-scale behavior, but it doesn’t need to be derived from small-scale behavior.

This means that the new paradigm in macroeconomics does not need to be computationally intractable. Using heuristics instead of dynamic optimization and worrying less about microfoundations will make the models simpler; adding inequality need not make them so much more complicated.

What does a central bank actually do?

Aug 26 JDN 2458357

Though central banks are a cornerstone of the modern financial system, I don’t think most people have a clear understanding of how they actually function. (I think this may be by design; there are many ways we could make central banking more transparent, but policymakers seem reluctant to show their hand.)

I’ve even seen famous economists make really severe errors in their understanding of monetary policy, as John Taylor did when he characterized low-interest-rate policy as a “price ceiling”.

Central banks “print money” and “set interest rates”. But how exactly do they do these things, and what on Earth do they have to do with each other?

The first thing to understand is that most central banks don’t actually print money. In the US, cash is actually printed by the Department of the Treasury. But cash is only a small part of the money in circulation. The monetary base consists of cash in vaults and in circulation; the US monetary base is about $3.6 trillion. The money supply can be measured a few different ways, but the standard way is to include checking accounts, traveler’s checks, savings accounts, money market accounts, short-term certified deposits, and basically anything that can be easily withdrawn and spent as money. This is called the M2 money supply, and in the US it is currently over $14.1 trillion. That means that only 25% of our money supply is in actual, physical cash—the rest is all digital. This is actually a relatively high proportion for actual cash, as the monetary base was greatly increased in response to the Great Recession. When we say that the Fed “prints money”, what we really mean is that they are increasing the money supply—but typically they do so in a way that involves little if any actual printing of cash.

The second thing to understand is that central banks don’t exactly set interest rates either. They target interest rates. What’s the difference, you ask?

Well, setting interest rates would mean that they made a law or something saying you have to charge exactly 2.7%, and you get fined or something if you don’t do that.

Targeting interest rates is a subtler art. The Federal Reserve decides what interest rates they want banks to charge, and then they engage in what are called open-market operations to try to make that happen. Banks hold reservesmoney that they are required to keep as collateral for their loans. Since we are in a fractional-reserve system, they are allowed to keep only a certain proportion (usually about 10%). In open-market operations, the Fed buys and sells assets (usually US Treasury bonds) in order to either increase or decrease the amount of reserves available to banks, to try to get them to lend to each other at the targeted interest rates.

Why not simply set the interest rate by law? Because then it wouldn’t be the market-clearing interest rate. There would be shortages or gluts of assets.

It might be easier to grasp this if we step away from money for a moment and just think about the market for some other good, like televisions.

Suppose that the government wants to set the price of a television in the market to a particular value, say $500. (Why? Who knows. Let’s just run with it for a minute.)

If they simply declared by law that the price of a television must be $500, here’s what would happen: Either that would be too low, in which case there would be a shortage of televisions as demand exceeded supply; or that would be too high, in which case there would be a glut of televisions as supply exceeded demand. Only if they got spectacularly lucky and the market price already was $500 per television would they not have to worry about such things (and then, why bother?).

But suppose the government had the power to create and destroy televisions virtually at will with minimal cost.
Now, they have a better way; they can target the price of a television, and buy and sell televisions as needed to bring the market price to that target. If the price is too low, the government can buy and destroy a lot of televisions, to bring the price up. If the price is too high, the government can make and sell a lot of televisions, to bring the price down.

Now, let’s go back to money. This power to create and destroy at will is hard to believe for televisions, but absolutely true for money. The government can create and destroy almost any amount of money at will—they are limited only by the very inflation and deflation the central bank is trying to affect.

This allows central banks to intervene in the market without creating shortages or gluts; even though they are effectively controlling the interest rate, they are doing so in a way that avoids having a lot of banks wanting to take loans they can’t get or wanting to give loans they can’t find anyone to take.

The goal of all this manipulation is ultimately to reduce inflation and unemployment. Unfortunately it’s basically impossible to eliminate both simultaneously; the Phillips curve describes the relationship generally found that decreased inflation usually comes with increased unemployment and vice-versa. But the basic idea is that we set reasonable targets for each (usually about 2% inflation and 5% unemployment; frankly I’d prefer we swap the two, which was more or less what we did in the 1950s), and then if inflation is too high we raise interest rate targets, while if unemployment is too high we lower interest rate targets.

What if they’re both too high? Then we’re in trouble. This has happened; it is called stagflation. The money supply isn’t the other thing affecting inflation and unemployment, and sometimes we get hit with a bad shock that makes both of them high at once. In that situation, there isn’t much that monetary policy can do; we need to find other solutions.

But how does targeting interest rates lead to inflation? To be quite honest, we don’t actually know.

The basic idea is that lower interest rates should lead to more borrowing, which leads to more spending, which leads to more inflation. But beyond that, we don’t actually understand how interest rates translate into prices—this is the so-called transmission mechanism, which remains an unsolved problem in macroeconomics. Based on the empirical data, I lean toward the view that the mechanism is primarily via housing prices; lower interest rates lead to more mortgages, which raises the price of real estate, which raises the price of everything else. This also makes sense theoretically, as real estate consists of large, illiquid assets for which the long-term interest rate is very important. Your decision to buy an apple or even a television is probably not greatly affected by interest rates—but your decision to buy a house surely is.

If that is indeed the case, it’s worth thinking about whether this is really the right way to intervene on inflation and unemployment. High housing prices are an international crisis; maybe we need to be looking at ways to decrease unemployment without affecting housing prices. But that is a tale for another time.

“DSGE or GTFO”: Macroeconomics took a wrong turn somewhere

Dec 31, JDN 2458119

The state of macro is good,” wrote Oliver Blanchard—in August 2008. This is rather like the turkey who is so pleased with how the farmer has been feeding him lately, the day before Thanksgiving.

It’s not easy to say exactly where macroeconomics went wrong, but I think Paul Romer is right when he makes the analogy between DSGE (dynamic stochastic general equilbrium) models and string theory. They are mathematically complex and difficult to understand, and people can make their careers by being the only ones who grasp them; therefore they must be right! Nevermind if they have no empirical support whatsoever.

To be fair, DSGE models are at least a little better than string theory; they can at least be fit to real-world data, which is better than string theory can say. But being fit to data and actually predicting data are fundamentally different things, and DSGE models typically forecast no better than far simpler models without their bold assumptions. You don’t need to assume all this stuff about a “representative agent” maximizing a well-defined utility function, or an Euler equation (that doesn’t even fit the data), or this ever-proliferating list of “random shocks” that end up taking up all the degrees of freedom your model was supposed to explain. Just regressing the variables on a few years of previous values of each other (a “vector autoregression” or VAR) generally gives you an equally-good forecast. The fact that these models can be made to fit the data well if you add enough degrees of freedom doesn’t actually make them good models. As Von Neumann warned us, with enough free parameters, you can fit an elephant.

But really what bothers me is not the DSGE but the GTFO (“get the [expletive] out”); it’s not that DSGE models are used, but that it’s almost impossible to get published as a macroeconomic theorist using anything else. Defenders of DSGE typically don’t even argue anymore that it is good; they argue that there are no credible alternatives. They characterize their opponents as “dilettantes” who aren’t opposing DSGE because we disagree with it; no, it must be because we don’t understand it. (Also, regarding that post, I’d just like to note that I now officially satisfy the Athreya Axiom of Absolute Arrogance: I have passed my qualifying exams in a top-50 economics PhD program. Yet my enmity toward DSGE has, if anything, only intensified.)

Of course, that argument only makes sense if you haven’t been actively suppressing all attempts to formulate an alternative, which is precisely what DSGE macroeconomists have been doing for the last two or three decades. And yet despite this suppression, there are alternatives emerging, particularly from the empirical side. There are now empirical approaches to macroeconomics that don’t use DSGE models. Regression discontinuity methods and other “natural experiment” designs—not to mention actual experiments—are quickly rising in popularity as economists realize that these methods allow us to actually empirically test our models instead of just adding more and more mathematical complexity to them.

But there still seems to be a lingering attitude that there is no other way to do macro theory. This is very frustrating for me personally, because deep down I think what I would like to do as a career is macro theory: By temperament I have always viewed the world through a very abstract, theoretical lens, and the issues I care most about—particularly inequality, development, and unemployment—are all fundamentally “macro” issues. I left physics when I realized I would be expected to do string theory. I don’t want to leave economics now that I’m expected to do DSGE. But I also definitely don’t want to do DSGE.

Fortunately with economics I have a backup plan: I can always be an “applied micreconomist” (rather the opposite of a theoretical macroeconomist I suppose), directly attached to the data in the form of empirical analyses or even direct, randomized controlled experiments. And there certainly is plenty of work to be done along the lines of Akerlof and Roth and Shiller and Kahneman and Thaler in cognitive and behavioral economics, which is also generally considered applied micro. I was never going to be an experimental physicist, but I can be an experimental economist. And I do get to use at least some theory: In particular, there’s an awful lot of game theory in experimental economics these days. Some of the most exciting stuff is actually in showing how human beings don’t behave the way classical game theory predicts (particularly in the Ultimatum Game and the Prisoner’s Dilemma), and trying to extend game theory into something that would fit our actual behavior. Cognitive science suggests that the result is going to end up looking quite different from game theory as we know it, and with my cognitive science background I may be particularly well-positioned to lead that charge.

Still, I don’t think I’ll be entirely satisfied if I can’t somehow bring my career back around to macroeconomic issues, and particularly the great elephant in the room of all economics, which is inequality. Underlying everything from Marxism to Trumpism, from the surging rents in Silicon Valley and the crushing poverty of Burkina Faso, to the Great Recession itself, is inequality. It is, in my view, the central question of economics: Who gets what, and why?

That is a fundamentally macro question, but you can’t even talk about that issue in DSGE as we know it; a “representative agent” inherently smooths over all inequality in the economy as though total GDP were all that mattered. A fundamentally new approach to macroeconomics is needed. Hopefully I can be part of that, but from my current position I don’t feel much empowered to fight this status quo. Maybe I need to spend at least a few more years doing something else, making a name for myself, and then I’ll be able to come back to this fight with a stronger position.

In the meantime, I guess there’s plenty of work to be done on cognitive biases and deviations from game theory.

What good are macroeconomic models? How could they be better?

Dec 11, JDN 2457734

One thing that I don’t think most people know, but which immediately obvious to any student of economics at the college level or above, is that there is a veritable cornucopia of different macroeconomic models. There are growth models (the Solow model, the Harrod-Domar model, the Ramsey model), monetary policy models (IS-LM, aggregate demand-aggregate supply), trade models (the Mundell-Fleming model, the Heckscher-Ohlin model), large-scale computational models (dynamic stochastic general equilibrium, agent-based computational economics), and I could go on.

This immediately raises the question: What are all these models for? What good are they?

A cynical view might be that they aren’t useful at all, that this is all false mathematical precision which makes economics persuasive without making it accurate or useful. And with such a proliferation of models and contradictory conclusions, I can see why such a view would be tempting.

But many of these models are useful, at least in certain circumstances. They aren’t completely arbitrary. Indeed, one of the litmus tests of the last decade has been how well the models held up against the events of the Great Recession and following Second Depression. The Keynesian and cognitive/behavioral models did rather well, albeit with significant gaps and flaws. The Monetarist, Real Business Cycle, and most other neoclassical models failed miserably, as did Austrian and Marxist notions so fluid and ill-defined that I’m not sure they deserve to even be called “models”. So there is at least some empirical basis for deciding what assumptions we should be willing to use in our models. Yet even if we restrict ourselves to Keynesian and cognitive/behavioral models, there are still a great many to choose from, which often yield inconsistent results.

So let’s compare with a science that is uncontroversially successful: Physics. How do mathematical models in physics compare with mathematical models in economics?

Well, there are still a lot of models, first of all. There’s the Bohr model, the Schrodinger equation, the Dirac equation, Newtonian mechanics, Lagrangian mechanics, Bohmian mechanics, Maxwell’s equations, Faraday’s law, Coulomb’s law, the Einstein field equations, the Minkowsky metric, the Schwarzschild metric, the Rindler metric, Feynman-Wheeler theory, the Navier-Stokes equations, and so on. So a cornucopia of models is not inherently a bad thing.

Yet, there is something about physics models that makes them more reliable than economics models.

Partly it is that the systems physicists study are literally two dozen orders of magnitude or more smaller and simpler than the systems economists study. Their task is inherently easier than ours.

But it’s not just that; their models aren’t just simpler—actually they often aren’t. The Navier-Stokes equations are a lot more complicated than the Solow model. They’re also clearly a lot more accurate.

The feature that models in physics seem to have that models in economics do not is something we might call nesting, or maybe consistency. Models in physics don’t come out of nowhere; you can’t just make up your own new model based on whatever assumptions you like and then start using it—which you very much can do in economics. Models in physics are required to fit consistently with one another, and usually inside one another, in the following sense:

The Dirac equation strictly generalizes the Schrodinger equation, which strictly generalizes the Bohr model. Bohmian mechanics is consistent with quantum mechanics, which strictly generalizes Lagrangian mechanics, which generalizes Newtonian mechanics. The Einstein field equations are consistent with Maxwell’s equations and strictly generalize the Minkowsky, Schwarzschild, and Rindler metrics. Maxwell’s equations strictly generalize Faraday’s law and Coulomb’s law.
In other words, there are a small number of canonical models—the Dirac equation, Maxwell’s equations and the Einstein field equation, essentially—inside which all other models are nested. The simpler models like Coulomb’s law and Newtonian mechanics are not contradictory with these canonical models; they are contained within them, subject to certain constraints (such as macroscopic systems far below the speed of light).

This is something I wish more people understood (I blame Kuhn for confusing everyone about what paradigm shifts really entail); Einstein did not overturn Newton’s laws, he extended them to domains where they previously had failed to apply.

This is why it is sensible to say that certain theories in physics are true; they are the canonical models that underlie all known phenomena. Other models can be useful, but not because we are relativists about truth or anything like that; Newtonian physics is a very good approximation of the Einstein field equations at the scale of many phenomena we care about, and is also much more mathematically tractable. If we ever find ourselves in situations where Newton’s equations no longer apply—near a black hole, traveling near the speed of light—then we know we can fall back on the more complex canonical model; but when the simpler model works, there’s no reason not to use it.

There are still very serious gaps in the knowledge of physics; in particular, there is a fundamental gulf between quantum mechanics and the Einstein field equations that has been unresolved for decades. A solution to this “quantum gravity problem” would be essentially a guaranteed Nobel Prize. So even a canonical model can be flawed, and can be extended or improved upon; the result is then a new canonical model which we now regard as our best approximation to truth.

Yet the contrast with economics is still quite clear. We don’t have one or two or even ten canonical models to refer back to. We can’t say that the Solow model is an approximation of some greater canonical model that works for these purposes—because we don’t have that greater canonical model. We can’t say that agent-based computational economics is approximately right, because we have nothing to approximate it to.

I went into economics thinking that neoclassical economics needed a new paradigm. I have now realized something much more alarming: Neoclassical economics doesn’t really have a paradigm. Or if it does, it’s a very informal paradigm, one that is expressed by the arbitrary judgments of journal editors, not one that can be written down as a series of equations. We assume perfect rationality, except when we don’t. We assume constant returns to scale, except when that doesn’t work. We assume perfect competition, except when that doesn’t get the results we wanted. The agents in our models are infinite identical psychopaths, and they are exactly as rational as needed for the conclusion I want.

This is quite likely why there is so much disagreement within economics. When you can permute the parameters however you like with no regard to a canonical model, you can more or less draw whatever conclusion you want, especially if you aren’t tightly bound to empirical evidence. I know a great many economists who are sure that raising minimum wage results in large disemployment effects, because the models they believe in say that it must, even though the empirical evidence has been quite clear that these effects are small if they are present at all. If we had a canonical model of employment that we could calibrate to the empirical evidence, that couldn’t happen anymore; there would be a coefficient I could point to that would refute their argument. But when every new paper comes with a new model, there’s no way to do that; one set of assumptions is as good as another.

Indeed, as I mentioned in an earlier post, a remarkable number of economists seem to embrace this relativism. “There is no true model.” they say; “We do what is useful.” Recently I encountered a book by the eminent economist Deirdre McCloskey which, though I confess I haven’t read it in its entirety, appears to be trying to argue that economics is just a meaningless language game that doesn’t have or need to have any connection with actual reality. (If any of you have read it and think I’m misunderstanding it, please explain. As it is I haven’t bought it for a reason any economist should respect: I am disinclined to incentivize such writing.)

Creating such a canonical model would no doubt be extremely difficult. Indeed, it is a task that would require the combined efforts of hundreds of researchers and could take generations to achieve. The true equations that underlie the economy could be totally intractable even for our best computers. But quantum mechanics wasn’t built in a day, either. The key challenge here lies in convincing economists that this is something worth doing—that if we really want to be taken seriously as scientists we need to start acting like them. Scientists believe in truth, and they are trying to find it out. While not immune to tribalism or ideology or other human limitations, they resist them as fiercely as possible, always turning back to the evidence above all else. And in their combined strivings, they attempt to build a grand edifice, a universal theory to stand the test of time—a canonical model.

The unending madness of the gold standard

JDN 2457545

If you work in economics in any capacity (much like “How is the economy doing?” you don’t even really need to be in macroeconomics), you will encounter many people who believe in the gold standard. Many of these people will be otherwise quite intelligent and educated; they often understand economics better than most people (not that this is saying a whole lot). Yet somehow they continue to hold—and fiercely defend—this incredibly bizarre and anachronistic view of macroeconomics.

They even bring it up at the oddest times; I recently encountered someone who wrote a long and rambling post arguing for drug legalization (which I largely agree with, by the way) and concluded it with #EndTheFed, not seeming to grasp the total and utter irrelevance of this juxtaposition. It seems like it was just a conditioned response, or maybe the sort of irrelevant but consistent coda originally perfected by Cato and his “Carthago delenda est. “Foederale Reservatum delendum est. Hey, maybe that’s why they’re called the Cato Institute.

So just how bizarre is the gold standard? Well, let’s look at what sort of arguments they use to defend it. I’ll use Charles Kadlic, prominent Libertarian blogger on Forbes, as an example, with his “Top Ten Reasons That You Should Support the ‘Gold Commission’”:

  1. A gold standard is key to achieving a period of sustained, 4% real economic growth.
  2. A gold standard reduces the risk of recessions and financial crises.
  3. A gold standard would restore rising living standards to the middle-class.
  4. A gold standard would restore long-term price stability.
  5. A gold standard would stop the rise in energy prices.
  6. A gold standard would be a powerful force for restoring fiscal balance to federal state and local governments.
  7. A gold standard would help save Medicare and Social Security.
  8. A gold standard would empower Main Street over Wall Street.
  9. A gold standard would increase the liberty of the American people.
  10. Creation of a gold commission will provide the forum to chart a prudent path toward a 21st century gold standard.

Number 10 can be safely ignored, as clearly Kadlic just ran out of reasons and to make a round number tacked on the implicit assumption of the entire article, namely that this ‘gold commission’ would actually realistically lead us toward a gold standard. (Without it, the other 9 reasons are just non sequitur.)

So let’s look at the other 9, shall we? Literally none of them are true. Several are outright backward.

You know a policy is bad when even one of its most prominent advocates can’t even think of a single real benefit it would have. A lot of quite bad policies do have perfectly real benefits, they’re just totally outweighed by their costs: For example, cutting the top income tax rate to 20% probably would actually contribute something to economic growth. Not a lot, and it would cut a swath through the federal budget and dramatically increase inequality—but it’s not all downside. Yet Kadlic couldn’t actually even think of one benefit of the gold standard that actually holds up. (I actually can do his work for him: I do know of one benefit of the gold standard, but as I’ll get to momentarily it’s quite small and can easily be achieved in better ways.)

First of all, it’s quite clear that the gold standard did not increase economic growth. If you cherry-pick your years properly, you can make it seem like Nixon leaving the gold standard hurt growth, but if you look at the real long-run trends in economic growth it’s clear that we had really erratic growth up until about the 1910s (the surge of government spending in WW1 and the establishment of the Federal Reserve), at which point went through a temporary surge recovering from the Great Depression and then during WW2, and finally, if you smooth out the business cycle, our growth rates have slowly trended downward as growth in productivity has gradually slowed down.

Here’s GDP growth from 1800 to 1900, when we were on the classical gold standard:

US_GDP_growth_1800s

Here’s GDP growth from 1929 to today, using data from the Bureau of Economic Analysis:

US_GDP_growth_BEA

Also, both of these are total GDP growth (because that is what Kadlic said), which means that part of what you’re seeing here is population growth rather than growth in income per person. Here’s GDP per person in the 1800s:

US_GDP_growth_1800s

If you didn’t already know, I bet you can’t guess where on those graphs we left the gold standard, which you’d clearly be able to do if the gold standard had this dramatic “double your GDP growth” kind of effect. I can’t immediately rule out some small benefit to the gold standard just from this data, but don’t worry; more thorough economic studies have done that. Indeed, it is the mainstream consensus among economists today that the gold standard is what caused the Great Depression.

Indeed, there’s a whole subfield of historical economics research that basically amounts to “What were they thinking?” trying to explain why countries stayed on the gold standard for so long when it clearly wasn’t working. Here’s a paper trying to argue it was a costly signal of your “rectitude” in global bond markets, but I find much more compelling the argument that it was psychological: Their belief in the gold standard was simply too strong, so confirmation bias kept holding them back from what needed to be done. They were like my aforementioned #EndTheFed acquaintance.

Then we get to Kadlic’s second point: Does the gold standard reduce the risk of financial crises? Let’s also address point 4, which is closely related: Does the gold standard improve price stability? Tell that to 1929.

In fact, financial crises were more common on the classical gold standard; the period of pure fiat monetary policy was so stable that it was called the Great Moderation, until the crash in 2008 screwed it all up—and that crash occurred essentially outside the standard monetary system, in the “shadow banking system” of unregulated and virtually unlimited derivatives. Had we actually forced banks to stay within the light of the standard banking system, the Great Moderation might have continued indefinitely.

As for “price stability”, that’s sort of true if you look at the long run, because prices were as likely to go down as they were to go up. But that isn’t what we mean by “price stability”. A system with good price stability will have a low but positive and steady level of inflation, and will therefore exhibit some long-run increases in price levels; it won’t have prices jump up and down erratically and end up on average the same.

For jump up and down is what prices did on the gold standard, as you can see from FRED:

US_inflation_longrun

This is something we could have predicted in advance; the price of any given product jumps up and down over time, and gold is just one product among many. Tying prices to gold makes no more sense than tying them to any other commodity.

As for stopping the rise in energy prices, energy prices aren’t rising. Even if they were (and they could at some point), the only way the gold standard would stop that is by triggering deflation (and therefore recession) in the rest of the economy.

Regarding number 6, I don’t see how the fiscal balance of federal and state governments is improved by periodic bouts of deflation that make their debt unpayable.

As for number 7, saving Medicare and Social Security, their payments out are tied to inflation and their payments in are tied to nominal GDP, so overall inflation has very little effect on their long-term stability. In any case, the problem with Medicare is spiraling medical costs (which Obamacare has done a lot to fix), and the problem with Social Security is just the stupid arbitrary cap on the income subject to payroll tax; the gold standard would do very little to solve either of those problems, though I guess it would make the nominal income cap less binding by triggering deflation, which is just about the worst way to avoid a price ceiling I’ve ever heard.

Regarding 8 and 9, I don’t even understand why Kadlic thinks that going to a gold standard would empower individuals over banks (does it seem like individuals were empowered over banks in the “Robber Baron Era”?), or what in the world it has to do with giving people more liberty (all that… freedom… you lose… when the Fed… stabilizes… prices?), so I don’t even know where to begin on those assertions. You know what empowers people over banks? The Consumer Financial Protection Bureau. You know what would enhance liberty? Ending mass incarceration. Libertarians fight tooth and nail against the former; sometimes they get behind the latter, but sometimes they don’t; Gary Johnson for some bizarre reason believes in privatization of prisons, which are directly linked to the surge in US incarceration.

The only benefit I’ve been able to come up with for the gold standard is as a commitment mechanism, something the Federal Reserve could do to guarantee its future behavior and thereby reduce the fear that it will suddenly change course on its past promises. This would make forward guidance a lot more effective at changing long-term interest rates, because people would have reason to believe that the Fed means what it says when it projects its decisions 30 years out.

But there are much simpler and better commitment mechanisms the Fed could use. They could commit to a Taylor Rule or nominal GDP targeting, both of which mainstream economists have been clamoring for for decades. There are some definite downsides to both proposals, but also some important upsides; and in any case they’re both obviously better than the gold standard and serve the same forward guidance function.

Indeed, it’s really quite baffling that so many people believe in the gold standard. It cries out for some sort of psychological explanation, as to just what cognitive heuristic is failing when otherwise-intelligent and highly-educated people get monetary policy so deeply, deeply wrong. A lot of them don’t even to seem grasp when or how we left the gold standard; it really happened when FDR suspended gold convertibility in 1933. After that on the Bretton Woods system only national governments could exchange money for gold, and the Nixon shock that people normally think of as “ending the gold standard” was just the final nail in the coffin, and clearly necessary since inflation was rapidly eating through our gold reserves.

A lot of it seems to come down to a deep distrust of government, especially federal government (I still do not grok why the likes of Ron Paul think state governments are so much more trustworthy than the federal government); the Federal Reserve is a government agency (sort of) and is therefore not to be trusted—and look, it has federal right there in the name.

But why do people hate government so much? Why do they think politicians are much less honest than they actually are? Part of it could have to do with the terrifying expansion of surveillance and weakening of civil liberties in the face of any perceived outside threat (Sedition Act, PATRIOT ACT, basically the same thing), but often the same people defending those programs are the ones who otherwise constantly complain about Big Government. Why do polls consistently show that people don’t trust the government, but want it to do more?

I think a lot of this comes down to the vague meaning of the word “government” and the associations we make with particular questions about it. When I ask “Do you trust the government?” you think of the NSA and the Vietnam War and Watergate, and you answer “No.” But when I ask “Do you want the government to do more?” you think of the failure at Katrina, the refusal to expand Medicaid, the pitiful attempts at reducing carbon emissions, and you answer “Yes.” When I ask if you like the military, your conditioned reaction is to say the patriotic thing, “Yes.” But if I ask whether you like the wars we’ve been fighting lately, you think about the hundreds of thousands of people killed and the wanton destruction to achieve no apparent actual objective, and you say “No.” Most people don’t come to these polls with thought-out opinions they want to express; the questions evoke emotional responses in them and they answer accordingly. You can also evoke different responses by asking “Should we cut government spending?” (People say “Yes.”) versus asking “Should we cut military spending, Social Security, or Medicare?” (People say “No.”) The former evokes a sense of abstract government taking your tax money; the latter evokes the realization that this money is used for public services you value.

So, the gold standard has acquired positive emotional vibes, and the Fed has acquired negative emotional vibes.

The former is fairly easy to explain: “good as gold” is an ancient saying, and “the gold standard” is even a saying we use in general to describe the right way of doing something (“the gold standard in prostate cancer treatment”). Humans have always had a weird relationship with gold; something about its timeless and noncorroding shine mesmerizes us. That’s why you occasionally get proposals for a silver standard, but no one ever seems to advocate an oil standard, an iron standard, or a lumber standard, which would make about as much sense.

The latter is a bit more difficult to explain: What did the Fed ever do to you? But I think it might have something to do with the complexity of sound monetary policy, and the resulting air of technocratic mystery surrounding it. Moreover, the Fed actively cultivates this image, by using “open-market operations” and “quantitative easing” to “target interest rates”, instead of just saying, “We’re printing money.” There may be some good reasons to do it this way, but a lot of it really does seem to be intended to obscure the truth from the uninitiated and perpetuate the myth that they are almost superhuman. “It’s all very complicated, you see; you wouldn’t understand.” People are hoarding their money, so there’s not enough money in circulation, so prices are falling, so you’re printing more money and trying to get it into circulation. That’s really not that complicated. Indeed, if it were, we wouldn’t be able to write a simple equation like a Taylor Rule or nominal GDP targeting in order to automate it!

The reason so many people become gold bugs after taking a couple of undergraduate courses in economics, then, is that this teaches them enough that they feel they have seen through the veil; the curtain has been pulled open and the all-powerful Wizard revealed to be an ordinary man at a control panel. (Spoilers? The movie came out in 1939. Actually, it was kind of about the gold standard.) “What? You’ve just been printing money all this time? But that is surely madness!” They don’t actually understand why printing money is actually a perfectly sensible thing to do on many occasions, and it feels to them a lot like what would happen if they just went around printing money (counterfeiting) or what a sufficiently corrupt government could do if they printed unlimited amounts (which is why they keep bringing up Zimbabwe). They now grasp what is happening, but not why. A little learning is a dangerous thing.

Now as for why Paul Volcker wants to go back to Bretton Woods? That, I cannot say. He’s definitely got more than a little learning. At least he doesn’t want to go back to the classical gold standard.

The credit rating agencies to be worried about aren’t the ones you think

JDN 2457499

John Oliver is probably the best investigative journalist in America today, despite being neither American nor officially a journalist; last week he took on the subject of credit rating agencies, a classic example of his mantra “If you want to do something evil, put it inside something boring.” (note that it’s on HBO, so there is foul language):

As ever, his analysis of the subject is quite good—it’s absurd how much power these agencies have over our lives, and how little accountability they have for even assuring accuracy.

But I couldn’t help but feel that he was kind of missing the point. The credit rating agencies to really be worried about aren’t Equifax, Experian, and Transunion, the ones that assess credit ratings on individuals. They are Standard & Poor’s, Moody’s, and Fitch (which would have been even easier to skewer the way John Oliver did—perhaps we can get them confused with Standardly Poor, Moody, and Filch), the agencies which assess credit ratings on institutions.

These credit rating agencies have almost unimaginable power over our society. They are responsible for rating the risk of corporate bonds, certificates of deposit, stocks, derivatives such as mortgage-backed securities and collateralized debt obligations, and even municipal and government bonds.

S&P, Moody’s, and Fitch don’t just rate the creditworthiness of Goldman Sachs and J.P. Morgan Chase; they rate the creditworthiness of Detroit and Greece. (Indeed, they played an important role in the debt crisis of Greece, which I’ll talk about more in a later post.)

Moreover, they are proven corrupt. It’s a matter of public record.

Standard and Poor’s is the worst; they have been successfully sued for fraud by small banks in Pennsylvania and by the State of New Jersey; they have also settled fraud cases with the Securities and Exchange Commission and the Department of Justice.

Moody’s has also been sued for fraud by the Department of Justice, and all three have been prosecuted for fraud by the State of New York.

But in fact this underestimates the corruption, because the worst conflicts of interest aren’t even illegal, or weren’t until Dodd-Frank was passed in 2010. The basic structure of this credit rating system is fundamentally broken; the agencies are private, for-profit corporations, and they get their revenue entirely from the banks that pay them to assess their risk. If they rate a bank’s asset as too risky, the bank stops paying them, and instead goes to another agency that will offer a higher rating—and simply the threat of doing so keeps them in line. As a result their ratings are basically uncorrelated with real risk—they failed to predict the collapse of Lehman Brothers or the failure of mortgage-backed CDOs, and they didn’t “predict” the European debt crisis so much as cause it by their panic.

Then of course there’s the fact that they are obviously an oligopoly, and furthermore one that is explicitly protected under US law. But then it dawns upon you: Wait… US law? US law decides the structure of credit rating agencies that set the bond rates of entire nations? Yes, that’s right. You’d think that such ratings would be set by the World Bank or something, but they’re not; in fact here’s a paper published by the World Bank in 2004 about how rather than reform our credit rating system, we should instead tell poor countries to reform themselves so they can better impress the private credit rating agencies.

In fact the whole concept of “sovereign debt risk” is fundamentally defective; a country that borrows in its own currency should never have to default on debt under any circumstances. National debt is almost nothing like personal or corporate debt. Their fears should be inflation and unemployment—their monetary policy should be set to minimize the harm of these two basic macroeconomic problems, understanding that policies which mitigate one may enflame the other. There is such a thing as bad fiscal policy, but it has nothing to do with “running out of money to pay your debt” unless you are forced to borrow in a currency you can’t control (as Greece is, because they are on the Euro—their debt is less like the US national debt and more like the debt of Puerto Rico, which is suffering an ongoing debt crisis you may not have heard about). If you borrow in your own currency, you should be worried about excessive borrowing creating inflation and devaluing your currency—but not about suddenly being unable to repay your creditors. The whole concept of giving a sovereign nation a credit rating makes no sense. You will be repaid on time and in full, in nominal terms; if inflation or currency exchange has devalued the currency you are repaid in, that’s sort of like a partial default, but it’s a fundamentally different kind of “default” than simply not paying back the money—and credit ratings have no way of capturing that difference.

In particular, it makes no sense for interest rates on government bonds to go up when a country is suffering some kind of macroeconomic problem.

The basic argument for why interest rates go up when risk is higher is that lenders expect to be paid more by those who do pay to compensate for what they lose from those who don’t pay. This is already much more problematic than most economists appreciate; I’ve been meaning to write a paper on how this system creates self-fulfilling prophecies of default and moral hazard from people who pay their debts being forced to subsidize those who don’t. But it at least makes some sense.

But if a country is a “high risk” in the sense of macroeconomic instability undermining the real value of their debt, we want to ensure that they can restore macroeconomic stability. But we know that when there is a surge in interest rates on government bonds, instability gets worse, not better. Fiscal policy is suddenly shifted away from real production into higher debt payments, and this creates unemployment and makes the economic crisis worse. As Paul Krugman writes about frequently, these policies of “austerity” cause enormous damage to national economies and ultimately benefit no one because they destroy the source of wealth that would have been used to repay the debt.

By letting credit rating agencies decide the rates at which governments must borrow, we are effectively treating national governments as a special case of corporations. But corporations, by design, act for profit and can go bankrupt. National governments are supposed to act for the public good and persist indefinitely. We can’t simply let Greece fail as we might let a bank fail (and of course we’ve seen that there are serious downsides even to that). We have to restructure the sovereign debt system so that it benefits the development of nations rather than detracting from it. The first step is removing the power of private for-profit corporations in the US to decide the “creditworthiness” of entire countries. If we need to assess such risks at all, they should be done by international institutions like the UN or the World Bank.

But right now people are so stuck in the idea that national debt is basically the same as personal or corporate debt that they can’t even understand the problem. For after all, one must repay one’s debts.

Why Millennials feel “entitled”

JDN 2457064

I’m sure you’ve already heard this plenty of times before, but just in case here are a few particularly notable examples: “Millennials are entitled.” “Millennials are narcissistic.” “Millennials expect instant gratification.

Fortunately there are some more nuanced takes as well: One survey shows that we are perceived as “entitled” and “self-centered” but also “hardworking” and “tolerant”. This article convincingly argues that Baby Boomers show at least as much ‘entitlement’ as we do. Another article points out that young people have been called these sorts of names for decades—though actually the proper figure is centuries.

Though some of the ‘defenses’ leave a lot to be desired: “OK, admittedly, people do live at home. But that’s only because we really like our parents. And why shouldn’t we?” Uh, no, that’s not it. Nor is it that we’re holding off on getting married. The reason we live with our parents is that we have no money and can’t pay for our own housing. And why aren’t we getting married? Because we can’t afford to pay for a wedding, much less buy a home and start raising kids. (Since the time I drafted this for Patreon and it went live, yet another article hand-wringing over why we’re not getting married was publishedin Scientific American, of all places.)

Are we not buying cars because we don’t like cars? No, we’re not buying cars because we can’t afford to pay for them.

The defining attributes of the Millennial generation are that we are young (by definition) and broke (with very few exceptions). We’re not uniquely narcissistic or even tolerant; younger generations always have these qualities.

But there may be some kernel of truth here, which is that we were promised a lot more than we got.

Educational attainment in the United States is the highest it has ever been. Take a look at this graph from the US Department of Education:

Percentage of 25- to 29-year-olds who completed a bachelor’s or higher degree, by race/ethnicity: Selected years, 1990–2014

education_attainment_race

More young people of every demographic except American Indians now have college degrees (and those figures fluctuate a lot because of small samples—whether my high school had an achievement gap for American Indians depended upon how I self-identified on the form, because there were only two others and I was tied for the highest GPA).

Even the IQ of Millennials is higher than that of our parents’ generation, which is higher than their parents’ generation; (measured) intelligence rises over time in what is called the Flynn Effect. IQ tests have to be adjusted to be harder by about 3 points every 10 years because otherwise the average score would stop being 100.

As your level of education increases, your income tends to go up and your unemployment tends to go down. In 2014, while people with doctorates or professional degrees had about 2% unemployment and made a median income of $1590 per week, people without even high school diplomas had about 9% unemployment and made a median income of only $490 per week. The Bureau of Labor Statistics has a nice little bar chart of these differences:

education_employment_earnings

Now the difference is not quite as stark. With the most recent data, the unemployment rate is 6.7% for people without a high school diploma and 2.5% for people with a bachelor’s degree or higher.

But that’s for the population as a whole. What about the population of people 18 to 35, those of us commonly known as Millennials?

Well, first of all, our unemployment rate overall is much higher. With the most recent data, unemployment among people ages 20-24 is a whopping 9.4%. For ages 25 to 34 it gets better, 5.3%; but it’s still much worse than unemployment at ages 35-44 (4.0%), 45-54 (3.6%), or 55+ (3.2%). Overall, unemployment among Millennials is about 6.7% while unemployment among Baby Boomers is about 3.2%, half as much. (Gen X is in between, but a lot closer to the Boomers at around 3.8%.)

It was hard to find data specifically breaking it down by both age and education at the same time, but the hunt was worth it.

Among people age 20-24 not in school:

Without a high school diploma, 328,000 are unemployed, out of 1,501,000 in the labor force. That’s an unemployment rate of 21.9%. Not a typo, that’s 21.9%.

With only a high school diploma, 752,000 are unemployed, out of 5,498,000 in the labor force. That’s an unemployment rate of 13.7%.

With some college but no bachelor’s degree, 281,000 are unemployed, out of 3,620,000 in the labor force. That’s an unemployment rate of 7.7%.

With a bachelor’s degree, 90,000 are unemployed, out of 2,313,000 in the labor force. That’s an unemployment rate of 3.9%.

What this means is that someone 24 or under needs to have a bachelor’s degree in order to have the same overall unemployment rate that people from Gen X have in general, and even with a bachelor’s degree, people under 24 still have a higher unemployment rate than what Baby Boomers simply have by default. If someone under 24 doesn’t even have a high school diploma, forget it; their unemployment rate is comparable to the population unemployment rate at the trough of the Great Depression.

In other words, we need to have college degrees just to match the general population older than us, of whom only 20% have a college degree; and there is absolutely nothing a Millennial can do in terms of education to ever have the tiny unemployment rate (about 1.5%) of Baby Boomers with professional degrees. (Be born White, be in perfect health, have a professional degree, have rich parents, and live in a city with very high employment, and you just might be able to pull it off.)

So, why do Millennials feel like a college degree should “entitle” us to a job?

Because it does for everyone else.

Why do we feel “entitled” to a higher standard of living than the one we have?
Take a look at this graph of GDP per capita in the US:

US_GDP_per_capita

You may notice a rather sudden dip in 2009, around the time most Millennials graduated from college and entered the labor force. On the next graph, I’ve added a curve approximating what it would look like if the previous trend had continued:

US_GDP_per_capita_trend

(There’s a lot on this graph for wonks like me. You can see how the unit-root hypothesis seemed to fail in the previous four recessions, where economic output rose back up to potential; but it clearly held in this recession, and there was a permanent loss of output. It also failed in the recession before that. So what’s the deal? Why do we recover from some recessions and take a permanent blow from others?)

If the Great Recession hadn’t happened, instead of per-capita GDP being about $46,000 in 2005 dollars, it would instead be closer to $51,000 in 2005 dollars. In today’s money, that means our current $56,000 would be instead closer to $62,000. If we had simply stayed on the growth trajectory we were promised, we’d be almost 10 log points richer (11% for the uninitiated).

So, why do Millennials feel “entitled” to things we don’t have? In a word, macroeconomics.

People anchored their expectations of what the world would be like on forecasts. The forecasts said that the skies were clear and economic growth would continue apace; so naturally we assumed that this was true. When the floor fell out from under our economy, only a few brilliant and/or lucky economists saw it coming; even people who were paying quite close attention were blindsided. We were raised in a world where economic growth promised rising standard of living and steady employment for the rest of our lives. And then the storm hit, and we were thrown into a world of poverty and unemployment—and especially poverty and unemployment for us.

We are angry about how we had been promised more than we were given, angry about how the distribution of what wealth we do have gets ever more unequal. We are angry that our parents’ generation promised what they could not deliver, and angry that it was their own blind worship of the corrupt banking system that allowed the crash to happen.

And because we are angry and demand a fairer share, they have the audacity to call us “narcissistic”.