What I’ve been reading and what has arrived in my pile
Jeremy Bailenson, Experience on Demand: What Virtual Reality Is, How It Works, and What It Can Do. Usually I am allergic to “general summary about some new topic in tech” books, but this one is quite good.
Michela Wrong, I Didn’t Do It For You: How the World Betrayed a Small African Nation, is in fact, as a number of you had suggested, probably the best book on Eritrea.
Matthew Engelke, How to Think Like an Anthropologist, is a very good introduction to exactly what the title promises.
Robert Wuthnow tries his hand at The Left Behind: Decline and Rage in Rural America.
Benn Steil, The Marshall Plan: Dawn of the Cold War.
Carl Zimmer, She Has Her Mother’s Laugh: The Powers, Perversions, and Potential of Heredity.
Tuesday assorted links
Title length
Abstract
We document strong and robust negative correlations between the length of the title of an economics article and different measures of scientific quality. Analyzing all articles published between 1970 and 2011 and referenced in EconLit, we find that articles with shorter titles tend to be published in better journals, to be more cited and to be more innovative. These correlations hold controlling for unobserved time-invariant and observed time-varying characteristics of teams of authors.
That is by Yann Bramoullé and Lorenzo Ductor at JEBO, via Michelle Dawson.
Bitcoin and covariance
Bitcoin and stocks bottomed at almost exactly the same moment. This is bad for Bitcoin. Part of Bitcoin’s appeal is that it is weird, and perhaps does not covary with standard financial assets in traditional ways. But at least yesterday it did, and that should be a force pushing Bitcoin lower.
Addendum from DB in the comments:
Matt Levine from yesterday: “Bloomberg tells me that Bitcoin’s daily correlation with the S&P 500 Index was 0.047 in 2017, -0.049 in 2016, 0.07 in 2015 and -0.081 in 2014. That is about as uncorrelated an asset as you could ask for — and a lot of Bitcoin buyers were asking for uncorrelated assets. So far in 2018 the correlation is 0.286. Still pretty uncorrelated! But … less so. When Bitcoin was a weird alternate-currency dream of anarchists, there was no reason for it to be correlated with stocks. When it is just an asset class that regular people trade, buying when they feel confident and selling when they feel nervous, that correlation ticks up.”
Why have some asset prices been so high?
Do they have to be bubbles? And is it so terrible if they fall? I cover those topics in my latest Bloomberg column, here is one bit:
In a volatile and uncertain time politically, we have observed sky-high prices for blue-chip U.S. equities. Other asset prices also seem to be remarkably high: home values and rentals in many of the world’s top-tier cities, negative real rates and sometimes negative nominal rates on the safest government securities, and the formerly skyrocketing and still quite high price of Bitcoin and other crypto-assets.
Might all of those somewhat unusual asset prices be part of a common pattern? Consider that over the past few decades there has been a remarkable increase of wealth in the world, most of all in the emerging economies. Say you hold enough wealth to invest: What are your options? Well, the stock markets of China and Russia are unsafe and not well developed, and many other emerging economies, such as Turkey and Brazil, have been wracked with uncertainty and political turmoil. So you might take a disproportionate share of your money and put it into high-quality, highly liquid assets. That might include the stocks of the Dow Jones Industrial Average and real estate in London, to name two possibilities.
In relative terms, the high-quality, highly liquid blue-chip assets will become expensive. So we end up with especially high price-to-earnings ratios and consistently negative real yields on safe government securities. Those price patterns don’t have to be bubbles. If this state of affairs persists, with a shortage of safe investment opportunities, those prices can stay high for a long time. They may go up further yet.
These high asset prices do reflect a reality of wealth creation. They are broadly bullish at the global scale, but they don’t have to demonstrate much if any good news about those assets per se. Rather there is an imbalance between world wealth and safe ways of transferring that wealth into the future…
To sum this all up in a single nerdy finance sentence, in a world where wealth creation has outraced the evolution of good institutions, the risk premium may be more important than you think.
In this “model,” price declines do not have to be disastrous, but rather can reflect a kind of normalization. Do read the whole thing. The theory also predicts that bond, equity, and Bitcoin prices should all decline at the same time, which is indeed what happened yesterday.
How much are illegal activities behind the demand for crypto-currency?
Cryptocurrencies are among the largest unregulated markets in the world. We find that approximately one-quarter of bitcoin users and one-half of bitcoin transactions are associated with illegal activity. Around $72 billion of illegal activity per year involves bitcoin, which is close to the scale of the US and European markets for illegal drugs. The illegal share of bitcoin activity declines with mainstream interest in bitcoin and with the emergence of more opaque cryptocurrencies. The techniques developed in this paper have applications in cryptocurrency surveillance. Our findings suggest that cryptocurrencies are transforming the way black markets operate by enabling “black e-commerce.”
Here is the paper, by Foley, Karlsen, and Putniņš, via the excellent Kevin Lewis.
The return of Nigeria’s kidnapped girls
Joe Parkinson and Drew Hinshaw at the WSJ follow up on what was a super dramatic story that turned into a neglected and under-reported tale. What is life like for the Boko Harum kidnap victims after their liberation?
The women had acclimated to the forest camps where Boko Haram insurgents threatened them at gunpoint to either convert to Islam and marry a fighter or be a slave.
About half chose slavery, which cost them access to food and shelter.
Here is another bit:
Psychologists who specialize in kidnap victims say they are unsure about the best way to simultaneously treat and educate such a large group of women—ages 18 to 27—after years of collective captivity and abuse.
The spelling bee contests, one healing piece of the curriculum, arrived as something of a surprise. It was the Chibok girls who came up with the idea.
And:
One night, plopped on couches, they watched “Akeelah and the Bee,” a movie about an 11-year-old African-American girl in Los Angeles who finds her confidence after her father’s death by winning the Scripps National Spelling Bee.
The students watched the movie again and again over bowls of popcorn. They went to their teachers with a demand: They wanted to hold their own spelling bees. The teachers agreed.
The young women began memorizing vocabulary lists and testing each others’ lexicographic skills. Their wordplay escalated into late-night spelling battles. “It was unbelievably competitive,” Mr. Braggs said.
Spelling employs a skill many of the women honed while captive: mnemonic memory. Some spent much of their time memorizing lengthy prayers and hymns. Others composed diary entries in their heads—their thoughts, injustices they suffered—they would later log in journals they kept hidden. In secret, they retold the story of Job, the biblical figure who was punished in a test of his faith.
By the way, 112 girls remain missing and 13 are presumed dead.
Monday assorted links
Federal Regulation Is Not the Cause of Declining Dynamism
My paper with the excellent Nathan Goldschlag, Is regulation to blame for the decline in American entrepreneurship? has finally been published. Our paper tests the plausible theory that regulation reduces dynamism as it builds up over time. Michael Mandel explains:
…it’s possible for every individual regulation to pass a cost-benefit test, while
the total accumulation of regulation creates a heavy burden on Americans. The number of
regulations matter, even if individually all are worthwhile.I call this the ‘pebble in the stream’ effect. Thrown one pebble in the stream, nothing happens.
Throw two pebbles in the stream, nothing happens. Throw one hundred pebbles in the stream,
and you have dammed up the stream. Which pebble did the damage? It’s not any single pebble,
it’s the accumulation.
This is also the theory of regulation and declining dynamism that Mancur Olson puts forward in his classic, The Rise and Decline of Nations. We find, however, that declining dynamism cannot be explained by growing federal regulation. The reason turns out to be simple: the decline in dynamism is widespread across many different industries and, in particular, it is widespread across heavily and lightly regulated industries. Our finding does not imply that regulation is necessarily good–regulations could fail a cost-benefit test and yet not have much of an effect on dynamism–nor does it imply that no regulation could explain declining dynamism only that we should probably look elsewhere for an explanation of declining dynamism than the cumulative growth of federal regulation. See the paper for some suggestions.
Frankly, it’s difficult to publish a paper that fails to reject the null hypothesis. A positive or negative effect is a natural stopping point–ok, they got it, let’s move on–but a zero-effect always leads to 
complaints that you didn’t run the regression in such and such a way or you could have done such and such a test. The asymmetry in paper evaluation leads to the file drawer problem where published results tend to reject the null even when a random sample of all results would find that the null is supported. We know the file drawer problem is serious because it predicts that studies with small sample sizes should have larger effect sizes–an effect that has often been found.
I can’t complain too much, however, because our paper was published in Economic Policy, a highly-ranked journal, and is the Editor’s Choice paper for that issue. The referees certainly made the paper better.
One of the things we did in the paper to counter the claim that our methods or data were defective was to look for entirely independent tests of the regulation hypothesis. If regulation is the main cause of declining U.S. dynamism, for example, then we ought to find that declining dynamism is associated with declining industry size. But when we look at dynamism, as measured by excess job reallocation rates, and industry employment what we see is that dynamism is declining in both shrinking and growing industries (see above). The paper has many additional tests.
The data and tools in our paper have other applications. Our methods, for example, can be used to distinguish between special-interest and general-interest regulation and could be used to test many other theories in political economy.
Chicago’s land tax and how the city survives being such a fiscal mess
https://twitter.com/Austan_Goolsbee/status/958696452125024256
But wait, isn’t Chicago a fiscal mess? How about the state of Illinois? It remains the case that living in Chicago is still remarkably affordable, and many of the neighborhoods have wonderful food, buildings, and offer a relatively safe (not always) and walkable environment. You may even hope to find a parking spot.
I would put it this way: there are many ways to impose a Georgist land tax, fiscal insolvency being one of them. Very wealthy people and institutions know that if they relocate to Chicago, they will be required to ante up for the final bill. And so they stay away. For a city of its size and import, Chicago just doesn’t have that many billionaires, nor do I think a rational billionaire should consider moving there.
In other words, there is a pending wealth tax. Either directly or indirectly, this will place fiscal burdens on Chicago land, the immobile factor. And this keeps down rents in Chicago now.
Overall, I do not recommend this fiscal course of action, and Chicago may well become a worse city due to eventual insolvency at the local and state levels. Still, if you are wondering how it is that Chicago is so affordable — and wonderful — right now, this is part of the answer.
I also should note that not every neighborhood in Chicago benefits from this equilibrium, as in some parts gentrification is difficult to come by.
Sunday assorted links
1. Arnold Kling on Jordan Peterson.
2. Skepticism about Amazon in health care (NYT).
3. Norway rats exchange different commodities.
4. Justin Wolfers on women in economics (NYT).
5. Lasers uncover the complexity and density of Mayan civilization. Was it the most densely populated part of the world at the time?
How Do Beavers Make Steel?
David Friedman’s beautiful explanation of trade was made famous by Steven Landsburg in his chapter the Iowa Car Crop from The Armchair Economist.
David’s observation is that there are two technologies for producing automobiles in America.
One is to manufacture them in Detroit, and the other is to grow them in Iowa. Everybody
knows about the first technology; let me tell you about the second. First you plant seeds, which are the raw material from
which automobiles are constructed. You wait a few months until
wheat appears. Then you harvest the wheat, load it onto ships,
and sail the ships eastward into the Pacific Ocean. After a few months, the ships reappear with Toyotas on them.
I learned recently from Robert Allen’s Global Economic History that Friedman’s analysis was preceded by more than three hundred years by an unknown Micmac Indian who at the height of the fur trade observed:
In truth, my brother, the Beaver does everything to perfection. He makes for us kettles, axes, swords, knives and gives us drink and food without the trouble of cultivating the ground.
When is coarse grading better?
(8) Coarse Grades: Informing the Public by Withholding Information, by Rick Harbaugh and Eric Rasmusen
Certifiers of quality often report only coarse grades to the public despite having measured quality more finely, e.g., “Pass” or “Certified” instead of “73 out of 100.” Why? We show that coarse grades result in more information being provided to the public because the coarseness encourages those of middling quality to apply for certification. Dropping exact grading in favor of the best coarse grading scheme reduces public uncertainty because the extra participation outweighs the coarser reporting. In some circumstances, the coarsest meaningful grading scheme, pass-fail grading, results in the most information.
Here is the link to American Economic Journal: Microeconomics. Of course another mechanism favoring coarse grading is that corrupt grades are easier to spot. If too many one-star Michelin restaurants are slid up to three stars, it is obvious something is going on. But if on a scale of one hundred a restaurant that ought to be a 67 is given a 73, who is really to say what those numbers are supposed to mean? There are many market settings where the coarser grading scheme is preferred over the finer alternative.
Will truckers be automated? (from the comments)
Dan Hanson writes:
I wonder how many of the people making predictions about the future of truck drivers have ever ridden with one to see what they do?
One of the big failings of high-level analyses of future trends is that in general they either ignore or seriously underestimate the complexity of the job at a detailed level. Lots of jobs look simple or rote from a think tank or government office, but turn out to be quite complex when you dive into the details.
For example, truck drivers don’t just drive trucks. They also secure loads, including determining what to load first and last and how to tie it all down securely. They act as agents for the trunking company. They verify that what they are picking up is what is on the manifest. They are the early warning system for vehicle maintenance. They deal with the government and others at weighing stations. When sleeping in the cab, they act as security for the load. If the vehicle breaks down, they set up road flares and contact authorities. If the vehicle doesn’t handle correctly, the driver has to stop and analyze what’s wrong – blown tire, shifting load, whatever.
In addition, many truckers are sole proprietors who own their own trucks. This means they also do all the bookwork, preventative maintenance, taxes, etc. These people have local knowledge that is not easily transferable. They know the quirks of the routes, they have relationships with customers, they learn how best to navigate through certain areas, they understand how to optimize by splitting loads or arranging for return loads at their destination, etc. They also learn which customers pay promptly, which ones provide their loads in a way that’s easy to get on the truck, which ones generally have their paperwork in order, etc. Loading docks are not all equal. Some are very ad-hoc and require serious judgement to be able to manoever large trucks around them. Never underestimate the importance of local knowledge.
I’ve been working in automation for 20 years. When you see how hard it is to simply digitize a paper process inside a single plant (often a multi-year project), you start to roll your eyes at ivory tower claims of entire industries being totally transformed by automation in a few years. One thing I’ve learned is a fundamentally Hayekian insight: When it comes to large scale activities, nothing about change is easy, and top-down change generally fails. Just figuring out the requirements for computerizing a job is a laborious process full of potential errors. Many automation projects fail because the people at the high levels who plan them simply do not understand the needs of the people who have to live with the results.
Take factory automation. This is the simplest environment to automate, because factories are local, closed environments that can be modified to make things simpler. A lot of the activities that go on in a factory are extremely well defined and repetitive. Factory robots are readily available that can be trained to do just about anything physically a person can do. And yet, many factories have not automated simply because there are little details about how they work that are hard to define and automate, or because they aren’t organized enough in terms of information flow, paperwork, processes, etc. It can take a team of engineers many man years to just figure out exactly what a factory needs to do to make itself ready to be automated. Often that requires changes to the physical plant, digitization of manual processes, Statistical analysis of variance in output to determine where the process is not being defined correctly, etc.
A lot of pundits have a sense that automation is accelerating in replacing jobs. In fact, I predict it will slow down, because we have been picking the low hanging fruit first. That has given us an unrealistic idea of how hard it is to fully automate a job.