Deirdre McCloskey Says Things

Some sadistic person or another referred me to this 51-page Deirdre McCloskey review of Thomas Piketty's book. I must remember to find who that person is and either play a mean prank on them in return, or demand that they buy me an expensive lunch. Fair is fair.

Deirdre McCloskey is the kind of writer who can take a perfectly fine sentence like "Capitalism has made humanity rich," and mutate it into a horror show like this:

Since those founding geniuses of Classical economics, a trade-tested betterment (a locution to be preferred to “capitalism,” with its erroneous implication that capital accumulation, not innovation, is what made us better off) has enormously enriched large parts of a humanity now seven times larger in population than in 1800, and bids fair in the next fifty years or so to enrich everyone on the planet.

I don't know about you, but I bid fair to give up well before page 51 of that locution.

But my main problem with Ms. McCloskey is not the poorly executed flowery baroque writing style, or even the reminder that plenty of people mistake flowery baroque writing for good writing. It's that McCloskey frequently makes declarations that are, to put it politely, in contradiction of the facts. She says these things with utmost confidence but without evidence or support, making it clear that the fact that she has said them is evidence enough. She argues from authority, and the authority is always herself.

This is NOT a post about Piketty or his arguments (of which I already have more than enough reason to be skeptical). It is NOT a post about McCloskey's rebuttal to those arguments. This is a post about McCloskey's style of argumentation.

Reading and critiquing McCloskey's thoughts on Piketty would be a bad move for me. First of all, it would require me to read dozens more pages of McCloskey than I have already read. Second, it would require me to know more about Piketty than I do (I haven't read Capital, nor do I own it). Third, it would turn the discussion political, which would detract from the main point of this post, which is that McCloskey is prone to silly-talk. Fourth, it would get very very very long, and you would get very very very bored.

So instead, I will simply critique the first three pages of the review, which are an introduction to the rest of the piece. McCloskey uses this introduction to praise Piketty, to compare him to physicists, and to insult most of the economics profession.

Here are nine excerpts that made my head explode:


1. p. 2:

[E]conomic history is one of the few scientifically quantitative branches of economics. In economic history, as in experimental economics and a few other fields, the economists confront the evidence (as they do not for example in most macroeconomics or industrial organization or international trade theory nowadays). 

And with a wave of her pen, Deirdre McCloskey dismisses the entire existence of the vast fields of empirical industrial organization, trade empirics, and empirical macro. Such is the power of argumentum ad verecundiam sui.

So I guess it was useless for Liran Einav, a Stanford economist who studies empirical IO, to write this in 2010:

The field of industrial organization has made dramatic advances over the last few decades in developing empirical methods for analyzing imperfect competition and the organization of markets. These new methods have diffused widely: into merger reviews and antitrust litigation, regulatory decision making, price setting by retailers, the design of auctions and marketplaces, and into neighboring fields in economics, marketing, and engineering. Increasing access to firm-level data and in some cases the ability to cooperate with governments in experimental research designs is offering new settings and opportunities to apply these ideas in empirical work.

After all, what does Einav know of his field? Deirdre McCloskey has said that Einav's field does not look at the evidence, and thus it is Truth.

Also, the Gravity Model of trade, often praised (by lesser lights, naturally) as one of the most empirically successful theories of all time, must now sadly be consigned to the graveyard, since Deirdre McCloskey has declared that trade theory fails to confront the evidence.


2. p. 2:

When you think about it, all evidence must be in the past, and some of the most interesting and scientifically relevant is in the more or less remote past... 

[Piketty] does not get entangled as so many economists do in the sole empirical tool they are taught, namely, regression analysis on someone else’s “data” (one of the problems is the very word data, meaning “things given”: scientists should deal in capta, “things seized”). 

Let's forgive the flamboyant vacuousness of the statement "When you think about it, all evidence must be in the past". Let's briefly mention the fact that that trivially true statement in no way implies the second part of the sentence. And let's move on to the fact that the two halves of the above quote are diametrically opposed to each other.

If scientists should seize "capta" instead of receiving "data", doesn't this make economic history unscientific? I mean, you can't do any experiments on history, can you? Are there any historical capta? McCloskey is barely finished praising her own field for looking at evidence when she scorns other fields for looking at very similar kinds of evidence!


3. p. 2-3:

Piketty constructs or uses statistics of aggregate capital and of inequality and then plots them out for inspection, which is what physicists, for example, also do in dealing with their experiments and observations. 

Physicists make graphs of things! Piketty makes graphs of things! Piketty is just like a physicist!

I wonder what else physicists do in dealing with their experiments and observations. Use computer software programs to display the statistics? Print out their plots on paper sheets for inspection? Sip coffee and check Twitter? I could be like a physicist too! Except I hate coffee, dammit.


4. p. 3:

Nor does [Piketty] commit the other sin, which is to waste scientific time on existence theorems. Physicists, again, don’t. If we economists are going to persist in physics envy let’s at least learn what physicists actually do. 

Wow, I'm glad that I have Deirdre McCloskey to tell me what physicists actually do. I'd hate to rely on an unreliable source like Google Scholar, who sneakily tries to convince me that physicists write papers with titles such as:

"Existence theorem for solitary waves on lattices"

"Vortex condensation in the Chern-Simons Higgs model: an existence theorem"

"General non-existence theorem for phase transitions in one-dimensional systems with short range interactions, and physical examples of such transitions"

"Existence theorem for solutions of Witten's equation and nonnegativity of total mass"

"A global existence theorem for the general coagulation–fragmentation equation with unbounded kernels"

"A Sharp Existence Theorem for Vortices in the Theory of Branes"

etc. etc. etc....

Thanks to Deirdre McCloskey's expansive sentence structure and snappish wit, I can safely assume that the 699,000 results for my Google Scholar search for "physics existence theorem" do not, in fact, exist (while the 417,000 results I get for "economics existence theorem" must be regarded as real). In addition, I can get a partial tuition reimbursement for the portion of my college physics education I spent watching professors prove existence theorems on the board.


5. p. 2:

[Piketty] does not commit one of the two sins of modern economics, the use of meaningless “tests” of statistical significance[.]

Is McCloskey unaware of the fact that physicists regularly use statistical significance testing, of the classic R.A. Fisher type?


6. p. 3:

Piketty stays close to the facts, and does not, say, wander into the pointless worlds of non-cooperative game theory, long demolished by experimental economics. 

Oh, right. Noncooperative game theory was demolished. Apparently Google and a bunch of other tech companies failed to get the memo when they hired auction theorists to design their online auctions for them.

Or perhaps by "demolished," McCloskey means "embraced by mathematicians, computer scientists, and engineers."

But DEIRDRE MCCLOSKEY SAYS THINGS, AND THUS THEY MUST BE TRUE!!

7. p. 3:

True, the book is probably doomed to be one of those more purchased than read...younger readers will remember Stephen Hawking’s A Brief History of Time (1988).

Deirdre McCloskey realizes that A Brief History of Time is only 212 pages long and has a lot of pictures, right?

It's always good to remember that just because you talk about books without having read them doesn't mean that everyone else does the same.


8. p. 4:

To be fair to Piketty, a buyer of the hardback rather than the Kindle edition is probably a more serious reader, and would go further.

This comes immediately after McCloskey claims that people buy books in order to display them on their coffee tables - something that you can't do with a Kindle version. Yet McCloskey now claims that hardback readers are more likely to be serious readers - utterly without evidence, of course.


9. p. 4:

I shall say some hard things, because they are true and important

This pretty much sums it up, folks.


So let me recap: All of these quotes came from the first three pages of a review that is 51 pages long. In three short pages, McCloskey manages to unfairly malign almost every branch of economics, make mutually contradictory assertions about how economists should use evidence, make false statements about physics that could have been corrected with a 5-second Google search, randomly insult a good popular physics book, and randomly insult Kindle readers, all in a mass of tangled, overwrought prose.

Yeah, there's no way I'm going to read 48 more pages of that. In fact, I'm not sure why I clicked on this link at all, given that everything else I've read of McCloskey's has been in the same vein (here's another example). Fool me twice, shame on me. Fool me five or six times, and I need a better hobby.

As a side note, John Cochrane agrees with my critique of the first 3 pages of McCloskey, and (more politely) notes several of the same errors. Yay!! He notes that McCloskey has written a writing guide, and failed to follow her own advice. (He also says that the review gets much better when it gets to the actual Piketty-related substance. So I suppose I'll put pages 4 through 51 on my "to read" list...possibly far down on the list...)

There is a clear lesson in all this: Do not believe things that Deirdre McCloskey says just because she says them. Google them. Find the facts. Do not nod your head in mute, placid agreement. Do not be seduced by the turgid prose style into thinking that here is an Authority.

Store of value

Two interesting posts about bitcoin by JP Koning (post 1, post 2) got me thinking about the function of money. Usually we say that money serves three functions: unit of account, medium of exchange, and store of value. But what does it mean to be a "store of value"? More specifically, what does it mean for a form of money to be a "good store of value," i.e., performing this function well?

Suppose, for simplicity's sake, that an asset's value (defined in consumption terms) follows a geometric Brownian motion with constant percentage volatility and drift. So it satisfies:

Does "good store of value" mean that sigma, the volatility, is low? Or does it mean that mu, the drift, is high? Remember that in the short term, volatility dominates drift, while in the long term, drift dominates. Also remember that there should be a tradeoff between these two - assets with higher volatility will tend to have higher systematic risk, and thus will tend to have higher expected returns (drift). In other words, in general an asset can be either a good long-term store of value, or a good short-term store of value, but not both.

Stocks are a good example of an asset with high positive drift and high volatility. Their value bounces around a lot, but it tends to increase over time. If "store of value" means "value tends to rise over time", then stocks would be a very good candidate. Stocks are a good long-term store of value.

Fiat money with a 2%-inflation-targeting central bank is a good example of an asset with negative drift and low volatility. Over time, you can expect this currency to lose value, since there will tend to be about 2% inflation every year. But the value is highly predictable - it doesn't fluctuate very much at all from day to day. Fiat-money-with-2%-inflation-targeting is a good short-term store of value.

Looking out at the world, I see a whole lot of countries that use fiat money, with something like inflation targeting, as their medium of exchange (i.e., what they use to pay for stuff). And I see zero who use stocks as the medium of exchange, even though the technology now exists for us to make payments in stock shares quite easily (it's just the same as exchanging dollars electronically, really).

So I conclude that we want the medium of exchange - i.e., money - to be a good short-term store of value (i.e., to have low volatility), and that we don't need it to be a good long-term store of value (i.e., we don't care about its expected return).

Why is this the case?

It makes sense if you think about the way that we use money. People don't know exactly when they are going to need to spend money, or how much. If they keep their wealth in assets with high expected returns and high volatility - stocks, etc. - they run the risk of having to sell in a down market in order to pay for unexpected expenses. So it makes sense to keep some of their wealth in a low-volatility, low-expected-return asset like fiat-money-with-2%-inflation-targeting, in the expectation that they'll probably have to use it to pay for something. The low expected return - the fact that cash falls in value a little bit every year - doesn't matter so much, because you don't keep the cash around that long before you spend it.

(Note that this ignores correlations, but those won't end up mattering here.)

So this is why money should be a short-term store of value rather than a long-term store of value. This is why, as David Andolfatto pointed out, gold makes such a lousy form of money.

How about bitcoin? If it keeps experiencing high volatility, then it's not going to become the medium of exchange in the U.S. or other countries with inflation targets. But if volatility falls in consumption terms - in other words, if the bitcoin prices of goods and services become very stable - then bitcoin will have a good chance of becoming the medium of exchange.

One problem, though, is that there's a bit of a chicken-and-egg situation here. The more merchants use bitcoin, the less volatile its consumption value will probably be. But in order for merchants to use it, customers have to use it, and they'll only start using it if there's low volatility.

But if bitcoin eventually manages to solve this chicken-and-egg problem, its promoters hope that it will be able to offer about the same volatility as fiat money but with a higher expected return. That would make bitcoin dominate fiat money, and would kick fiat money right out of the universe of investible assets - or, more realistically, it would force central banks to adopt an inflation target lower than the rate at which bitcoin is mined. That, I think, is the hope of bitcoin enthusiasts who say that bitcoin will "compete with central banks."

So for bitcoin to become money, it has to figure out how to massively reduce the volatility of bitcoin prices of goods and services.


Update

Eli Dourado has a good response. I think we agree on the volatility thing. I glossed over other kinds of transaction costs, which Koning addresses somewhat; on those matters, I'm pretty ignorant, so I will let Eli and JP work it out...

Tyler Cowen thinks Bitcoin's volatility is a bad sign for its chances of future adoption, because it reflects a consensus that Bitcoin will never really catch on. I disagree with Tyler. Suppose, for simplicity's sake, that milk was the only good that people consumed. And suppose that in the future, bitcoin becomes the universal medium of exchange, and that at that time the bitcoin price of milk is about the same as it is today. In this case, there is no benefit to buying a lot of bitcoin today, even if you know for certain that it's going to become universally adopted. Because the price of bitcoin is already "right", in consumption terms. Hoarding a bunch of bitcoin right now doesn't actually improve your tradeoff between future milk and present milk. So the lack of bitcoin speculation doesn't necessarily mean that people have decided that bitcoin is doomed. It could even mean the exact opposite.

A paradigm shift in empirical economics?

Empirical economics is a more and more important part of economics, having taken over the majority of top-journal publishing from theory papers. But there are different flavors of empirical econ. There are good old reduced-form, "reg y x" correlation studies. There are structural vector autoregressions. There are lab experiments. There are structural estimation papers, which estimate the parameters of more complex models that they assume/hope describe the deep structure of the economy.

Then there are natural experiments. These papers try to find some variation in economic variables that is "natural", i.e. exogenous, and look at the effect this variation has on other variables that we're interested in. For example, suppose you wanted to know the benefits of food stamps. This would be hard to identify with a simple correlation, because all kinds of things might affect whether people actually get (or choose to take) food stamps in the first place. But then suppose you found a policy that awarded food stamps to anyone under 6 feet in height, and denied them to anyone over 6 feet. That distinction is pretty arbitrary, at least in the neighborhood of the 6-foot cutoff. So you could compare people who are just over 6 feet with people who are just under, and see whether the latter do better than the former. 

That's called a "regression discontinuity design," and it's one kind of natural experiment, or "quasi-experimental design." It's not as controlled as a lab experiment or field experiment (there could be other policies that also have a cutoff of 6 feet!), but it's much more controlled than anything else, and it's more ecologically valid than a lab experiment and cheaper and more ethically uncomplicated than a field experiment. There are two other methods typically called "quasi-experimental" - these are instrumental variables and difference-in-differences.

Recently, Joshua Angrist and Jorn-Steffen Pischke wrote a book called Mostly Harmless Econometrics in which they trumpet the rise of these methods. That follows a 2010 paper called "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics." In their preface, the authors write:

[T]here is no arguing with the fact that experimental and quasi-experimental research designs are increasingly at the heart of the most influential empirical studies in applied economics. 

This has drawn some fire from fans of structural econometrics, who don't like the implication that their own methods are not "harmless". In fact, Angrist and Pischke's preface makes it clear that they do think that "[s]ome of the more exotic [econometric methods] are needlessly complex and may even be harmful." 

But when they say their methods are becoming dominant, Angrist and Pischke have the facts right.Two new survey papers demonstrate this. First, there is "The Empirical Economist's Toolkit: From Models to Methods", by Matthew Panhans and John Singleton, which deals with applied microeconomics. Panhans and Singleton write:

While historians of economics have noted the transition toward empirical work in economics since the 1970s, less understood is the shift toward "quasi-experimental" methods in applied microeconomics. Angrist and Pischke (2010) trumpet the wide application of these methods as a "credibility revolution" in econometrics that has finally provided persuasive answers to a diverse set of questions. Particularly influential in the applied areas of labor, education, public, and health economics, the methods shape the knowledge produced by economists and the expertise they possess. First documenting their growth bibliometrically, this paper aims to illuminate the origins, content, and contexts of quasi-experimental research designs[.]

Here are two of the various graphs they show:

The second recent survey paper is "Natural Experiments in Macroeconomics", by Nicola Fuchs-Schuendeln and Tarek Alexander Hassan, It demonstrates how natural experiments can be used in macro. As you might expect, it's a lot harder to find good natural experiments in macro than in micro, but even there, the technique appears to be making some inroads.

So what does all this mean?

Mainly, I see it as part of the larger trend away from theory and toward empirics in the econ field as a whole. Structural econometrics takes theory very seriously; quasi-experimental econometrics often does not. Angrist and Pischke write:

A principle that guides our discussion is that the [quasi-experimental] estimators in common use almost always have a simple interpretation that is not heavily model-dependent.

It's possible to view structural econometrics as sort of a halfway house between the old, theory-based economics and the new, evidence-based economics. The new paradigm focuses on establishing whether A causes B, without worrying too much about why. (Of course, you can use quasi-experimental methods to test structural models, at least locally - most econ models involve a set of first-order conditions or other equations that can be linearized or otherwise approximated. But you don't have to do that.) Quasi-experimental methods don't get rid of theory; what they do is to let you identify real phenomena without necessarily knowing why they happen, and then go looking for theories to explain them, if such theories don't already exist.

I see this as potentially being a very important shift. The rise of quasi-experimental methods shows that the ground has fundamentally shifted in economics - so much that the whole notion of what "economics" means is undergoing a dramatic change. In the mid-20th century, economics changed from a literary to a mathematical discipline. Now it might be changing from a deductive, philosophical field to an inductive, scientific field. The intricacies of how we imagine the world must work are taking a backseat to the evidence about what is actually happening in the world.

The driver is information technology. This does for econ something similar to what the laboratory did for chemistry - it provides an endless source of data, and it allows (some) controls. 

Now, no paradigm gets things completely right, and no set of methods is always and universally the best. In a paper called "Tantalus on the Road to Asymptopia," reknowned skeptic (skepticonomist?) Ed Leamer cautions against careless, lazy application of quasi-experimental methods. And there are some things that quasi-experimental methods just can't do, such as evaluating counterfactuals far away from current conditions. The bolder the predictions you want to make, the more you need a theory of how the world actually works. (To make an analogy, it's useful to catalogue chemical reactions, but it's more generally useful to have a periodic table, a theory of ionic and covalent bonds, etc.)

But just because you want a good structural theory doesn't mean you can always produce one. In the mid-80s, Ed Prescott declared that theory was "ahead" of measurement. With the "credibility revolution" of quasi-experimental methods, measurement appears to have retaken the lead.


Update: I posted some follow-up thoughts on Twitter. Obviously there is a typo in the first tweet; "quasi-empirical" should have been "quasi-experimental".