Data Source

Justin Fox started it, and Robin Hanson has a good restatement of the puzzle:

The S&P 500 are five hundred big public firms listed on US exchanges. Imagine that you wanted to create a new firm to compete with one of these big established firms. So you wanted to duplicate that firm’s products, employees, buildings, machines, land, trucks, etc. You’d hire away some key employees and copy their business process, at least as much as you could see and were legally allowed to copy.

Forty years ago the cost to copy such a firm was about 5/6 of the total stock price of that firm. So 1/6 of that stock price represented the value of things you couldn’t easily copy, like patents, customer goodwill, employee goodwill, regulator favoritism, and hard to see features of company methods and culture. Today it costs only 1/6 of the stock price to copy all a firm’s visible items and features that you can legally copy. So today the other 5/6 of the stock price represents the value of all those things you can’t copy.

Check out his list of hypotheses.  Scott Sumner reports:

Here are three reasons that others have pointed to:

1. The growing importance of rents in residential real estate.
2. The vast upsurge in the share of corporate assets that are “intangible.”
3. The huge growth in the complexity of regulation, which favors large firms.

It’s easy enough to see how this discrepancy may have evolved for the tech sector, but for the Starbucks sector of the economy I don’t quite get it.  A big boost in monopoly power can create a larger measured role for accounting intangibles, but Starbucks has plenty of competition, just ask Alex.  Our biggest monopoly problems are schools and hospitals, which do not play a significant role in the S&P 500.

Another hypothesis — not cited by Sumner or Hanson —  is that the difference between book and market value of firms is diverging over time.  That increasing residual gets classified as an intangible, but we are underestimating the value of traditional physical capital, and by more as time passes.

Cowen’s second law (“There is a literature on everything”) now enters, and leads us to Beaver and Ryan (pdf), who study biases in book to market value.  Accounting conservatism, historical cost, expected positive value projects, and inflation all can contribute to a widening gap between book and market value.  They also suggest (published 2000) that overestimations of the return to capital have bearish implications for future returns.  It’s an interesting question when the measured and actual means for returns have to catch up with each other, what predictions this eventual catch-up implies, and whether those predictions have come true.  How much of the growing gap is a “bias component” vs. a “lag component”?  Heady stuff, the follow-up literature is here.

Perhaps most generally, there is Hulten and Hao (pdf):

We find that conventional book value alone explains only 31 percent of the market capitalization of these firms in 2006, and that this increases to 75 percent when our estimates of intangible capital are included.

So some of it really is intangibles, but a big part of the change still may be an accounting residual.  Their paper has excellent examples and numbers, but note they focus on R&D intensive corporations, not all corporations, so their results address less of the entire problem than a quick glance might indicate.  By the way, all this means the American economy (and others too?) has less leverage than the published numbers might otherwise indicate.

Here is a 552 pp. NBER book on all of these issues, I have not read it but it is on its way in the mail.  Try also this Robert E. Hall piece (pdf), he notes a “capital catastrophe” occurred in the mid-1970s, furthermore he considers what rates of capital accumulation might be consistent with a high value for intangible assets.  That piece of the puzzle has to fit together too.  This excellent Baruch Lev paper (pdf) considers some of the accounting issues, and also how mismeasured intangible assets often end up having their value captured by insiders; that is a kind of rent-seeking explanation.  See also his book Intangibles.  Don’t forget the papers of Erik Brynjolfsson on intangibles in the tech world, if I recall correctly he shows that the cross-sectoral predictions line up more or less the way you would expect.  Here is a splat of further references from scholar.google.com.

I would sum it up this way: measuring intangible values properly shows much of this change in the composition of American corporate assets has been real.  But a significant gap remains, and accounting conventions, based on an increasing gap between book and market value, are a primary contender for explaining what is going on.  In any case, there remain many underexplored angles to this puzzle.

Addendum: I wish to thank @pmarca for a useful Twitter conversation related to this topic.

How many robot alarms are there anyway?

Every day, the bedside cardiac monitors threw off some 187 audible alerts. No, not 187 audible alerts for all the beds in the five ICUs; 187 alerts were generated by the monitors in each patient’s room, an average of one alarm buzzing or beeping by the bedside every eight minutes. Every day, there were about 15,000 alarms across all the ICU beds. For the entire month, there were 381,560 alarms across the five ICUs. Remember, this is from just one of about a half-dozen systems connected to the patients, each tossing off its own alerts and alarms.

And those are just the audible ones.

If you add the inaudible alerts, those that signal with flashing lights and text-based messages, there were 2,507,822 unique alarms in one month in our ICUs, the overwhelming majority of them false.

That is all from Bob Wachter, an interesting piece.

Peter Orszag reports:

During roughly the same period, the return on invested capital — that is, how much profit is generated for each dollar of investment — also grew more unequal between companies. While the typical return was roughly constant, at about 10 percent, returns became more dispersed over time.

In particular, from 1965 to 1967, only 1 percent of non-financial firms earned returns of 50 percent or more, but from 2005 to 2007, 14 percent did. In other words, 50 years ago, one out of 100 firms earned 50 percent returns. More recently, one out of seven did.

These data suggest three things: First, the typical return to capital hasn’t changed much, which is what you would expect, given that the capital-output ratio excluding land and housing has been stable.

Second, from company to company, that return has become much more unequal, as has productivity. Some of this inequality between companies in returns and productivity tends to spill over into wages. And this is precisely what we’ve seen. It explains more of the rise in overall earnings inequality than does the increased gaps between the pay of higher earners and rank-and-file workers within a given company.

The full article is here.

“What jumped out for me was the survey that revealed that in some cases as many as 39 percent of our learners are teachers,”

There are two ways to view this.  One is that educators are simply talking to each other.  The alternative — more likely in my view — is that on-line and face-to-face education are in fact complements, but also that our educators know much less than they sometimes let on.  They need MOOCs to learn the material, or more optimistically to improve their presentations of it.

And how is this for the law of demand?:

Across 12 courses, participants who paid for “ID-verified” certificates (with costs ranging from $50 to $250) earned certifications at a higher rate than other participants: 59 percent, on average, compared with 5 percent. Students opting for the ID-verified track appear to have stronger intentions to complete courses, and the monetary stake may add an extra form of motivation.

I’ve long thought the standard meme “Only [small number goes here] percent of starters complete free MOOCS” was a weak argument.  This shows you why.

The piece discusses other interesting results as well.

Gary Solon, in a new survey paper, takes issue with the earlier results of Greg Clark, which had suggested social mobility was roughly constant across a wide spectrum of cases.  Solon writes:

…the results reported by Clark do not reflect a universal law of social mobility.  Quite to the contrary, other studies based on group-average data, even surnames data, frequently produce intergenerational coefficient estimates much smaller than Clark’s.

A second testable prediction of Clark’s hypothesis…is that instrumental variables (IV) estimation of the regression of son’s log earnings on father’s log earnings should yield a coefficient estimate in the 0.7-0.8 range if father’s long earnings are instrumented with grandfather’s log earnings.  When Lindahl et al, estimated that regression with their data from Malmo, Sweden, the IV coefficient estimate was 0.15, considerably higher than their ordinary least squares (OLS) estimate of 0.303.  They obtained a remarkably similar comparison of IV and OLS estimates when they used years of education instead of log earnings as the status measure.  The pattern of IV estimates exceeding OLS estimates is consistent with Clark’s general story about measurement error in particular indicators as proxies for social status.  It is equally consistent with all the alternative stories listed in section II for why grandparental status may not be “excludable” from a multigenerational regression.  What the results are not consistent with is a universal law of social mobility in which the intergenerational coefficient is always 0.7 or more…

A third testable prediction…is that using an omnibus index that combines multiple indicators of social status should make the intergenerational coefficient estimate “much closer to that of the underlying latent variable.”  [But]…The resulting estimate was not “much closer” to the 0.7-0.8 range.

In sum, when Clark’s hypothesis is subjected to empirical tests, it does not fare so well.

Here is an ungated version.

New brokerage accounts have surged since China’s bull market got running mid-2014. The number of new trading accounts hit a five-year high in early March. But as you can see in the chart above, a lot of those new investors probably aren’t the savviest.

Some 67.6% of households that opened new accounts in the past quarter haven’t graduated from high school, according Orlik’s chart, which comes from a large-scale quarterly national survey of household assets and income conducted by Gan Li of the Southwestern University of Finance and Economics. Only 12% have a college education. Among existing investors surveyed, only 25.5% lack a high school diploma; 40.3% have finished college.

From Gwynn Guilford, there is more here.

Here is the abstract of his piece “Air Conditioning, Migration, and Climate-Related Rent Differentials“:

This paper explores whether the spread of air conditioning in the United States from 1960 to 1990 affected quality of life in warmer areas enough to influence decisions about where to live, or to change North-South wage and rent differentials. Using measures designed to identify climates in which air conditioning would have made the biggest difference, I found little evidence that the flow of elderly migrants to MSAs with such climates increased over the period. Following Roback (1982), I analyzed data on MSA wages, rents, and climates from 1960 to 1990, and find that the implicit price of these hot summer climates did not change significantly from 1960 to 1980, then became significantly negative in 1990. This contrary to what one would expect if air conditioning made hot summers more bearable. I presented evidence that hot summers are an inferior good, which would explain part of the negative movement in the implicit price of a hot summer, and evidence consistent with the hypothesis that the marginal person migrating from colder to hotter MSAs dislikes summer heat more than does the average resident of a hot MSA, which would also exert downward pressure on the implicit price of a hot summer.

The pointer is from Ross Emmett in the MR comments section, very useful comments overall.  Biddle has two other pieces on the history of air conditioning, and Biddle has other interesting pieces as well, he is apparently an underappreciated economist.

Here Scott Sumner details the import of state income taxes.  In my view not the “main” factor, but a significant factor nonetheless, excerpt: “On the west coast, all states grew faster than the national average. Yes, its climate is nicer that the south central region.  But look at the more detailed data and you’ll see that hot and sunny Washington state and Alaska grew the fastest of five bordering the Pacific.  And oh by the way, Washington and Alaska are the only two with no state income tax.”  I’ll add this point: to the extent income inequality is rising, a relatively small number of cross-state migrants can lead to a noticeable difference in cross-state growth and job creation rates.  And the high earners are precisely those who are most able and most likely to leave a high-tax state for a low-tax state.

musiclife

That is from Dianne Theodora Kenny, via Ted Gioia.  Kenny notes:

For male musicians across all genres, accidental death (including all vehicular incidents and accidental overdose) accounted for almost 20% of all deaths. But accidental death for rock musicians was higher than this (24.4%) and for metal musicians higher still (36.2%).

Suicide accounted for almost 7% of all deaths in the total sample. However, for punk musicians, suicide accounted for 11% of deaths; for metal musicians, a staggering 19.3%. At just 0.9%, gospel musicians had the lowest suicide rate of all the genres studied.

Murder accounted for 6.0% of deaths across the sample, but was the cause of 51% of deaths in rap musicians and 51.5% of deaths for hip hop musicians, to date.

Beware selection, because of course most rap musicians aren’t dead yet.  This problem will be more extreme, the younger is the genre.  Another selection effect may be that getting killed, or dying in an unusual way, contributes to your fame.

Paul Krugman has had a few posts on this question, most recently this one, the first one here.  Krugman is right in asserting a major role for air conditioning, but there is a subtle framing point which is sometimes neglected.  The most on-point study is this piece from Jordan Rappaport (pdf):

U.S. residents have been moving en masse to places with nice weather. Well known is the migration towards places with warm winters, which is often attributed to the introduction of air conditioning. But people have also been moving to places with cooler, less-humid summers, which is the opposite of what is expected from the introduction of air conditioning. Nor can the movement to nice weather be primarily explained by shifting industrial composition or by elderly migration. Instead, a large portion of weather-related moves appear to be the result of an increased valuation of nice weather as a consumption amenity, probably due to broad-based rising per capita income.

Overall Rappaport concludes that “nice [warm] weather is a normal good” is the more important driving force behind the movement to the Sun Belt than is air conditioning per se, though of course air conditioning makes nice warm weather all the nicer.  Evidence from compensating differentials also indicates that “…the decreased discomfort from heat and humidity afforded by air-conditioning has not been the primary driver of the move to nice weather.” (p.26)

From 1880 to 1910, Americans overall are moving to places with bad (cold) weather.  In the 1920s they start moving, on net, to places with nicer weather and that trend has not let up.  The arrival of affordable air conditioning in the postwar era bumps this up a bit, but the main trend already was in place.  Furthermore air conditioning has been in the south for quite a while now, but migration in that direction continues.  In his second post on the topic, Krugman refers to this as a “gradual adjustment” to AC, but it seems to better fit the nice weather as a normal good story.  We’ll know more if we see this migration continuing, but I expect it will.  At some point it won’t be plausible to call the ongoing movement a “lagged response” to the introduction of air conditioning, but again it will fit the normal good story pretty smoothly.

Note also that life expectancy is notably higher in warm weather than cold weather.  Deschenes and Moretti conclude (pdf): “…The longevity gains associated with mobility from the Northeast to the Southwest account for 4% to 7% of the total gains in life expectancy experienced by the U.S. population over the past thirty years.”

That again points toward a “normal good” explanation, with air conditioning playing a supporting role.

That all said, if you look at the larger political debate going on here, Krugman is correct in arguing that lower taxes are the not main reason for this migration, even though the median voter in these states probably approves of such relatively low tax rates.  In any case, there is a clearer and better version of the weather hypothesis which can be put forward.

Addendum: David Beckworth adds commentary and some fascinating maps.

From The New Left Review, Moretti and Pestre report:

Three new semantic clusters characterize the language of the Bank from the early 1990s on. The first—and most important—has to do with finance: here, alongside a few predictable adjectives (financial, fiscal, economic) and nouns (loans, investment, growth, interest, lending, debt), we find a landslide of fair value, portfolio, derivative, accrual, guarantees, losses, accounting, assets; a little further down the list, equity, hedging, liquidity, liabilities, creditworthiness, default, swaps, clients, deficit, replenishment, repurchase, cash. In terms of frequency and semantic density, this cluster can only be compared to the material infrastructures of the 1950s–60s; now, however, work in agriculture and industry has been replaced by an overwhelming predominance of financial activities.

…The second cluster has to do with management—a noun that, in absolute terms, is the second most frequent of the last decade (lower than loans, but higher than risk and investment!). In the world of ‘management’, people have goals and agendas; faced with opportunities, challenges and critical situations, they elaborate strategies. To appreciate the novelty, let’s recall that, in the 1950s–60s, issues were studied by experts who surveyed and conducted missions, published reports, assisted, advised and suggested programmes. With the advent of management, the centre of gravity shifts towards focusing, strengthening and implementing; one must monitor, control, audit, rate (Figure 2); ensure that everything is done properly while also helping people to learn from mistakes. The many tools at the manager’s disposal (indicators, instruments, knowledge, expertise, research) enhance effectiveness, efficiency, performance, competitiveness and—it goes without saying—promote innovation.

The concept of governance is another clear winner in more recent times, and furthermore the reports seem to overuse the word “and” relative to the word “the.”  That I can believe.  The article is interesting throughout, hat tip goes to Avinash Celstine.

At the Massachusetts Institute of Technology, a premier source of young recruits, only 9.9 percent of undergraduates went into finance in 2013, compared with the 31 percent that took jobs on Wall Street in 2006, before the financial crisis. Software companies, meanwhile, hired 28.1 percent of M.I.T. graduates in 2013, compared with 10.5 percent in 2006.

That is from Popper and Dougherty in the NYT, via Binyamin Appelbaum.

Will Radford and Mathias Gallé have a new and interesting paper on this topic, here is one excerpt:

Law and corporate professions had around 15% of female representation…the medical domain (doctors) had a female probability of 0.23…Religion does not score at the bottom with regards to female presentation (although very low with 0.08). From the professions we selected, Engineering was the lowest (0.05). The highest scoring profession was IT (0.52), which is partly due to the fact that many computer voices were female (computer had 460 female occurrences, versus 247 male ones; and enterprise computer from “Star Trek” was almost exclusively female)

By the way, the number of female writers and directors (in their IMDB database) was at a six year low in 2014.

If you look at most frequent roles for gender, women are assigned hostess, girl, woman, waitress, and mother.  For men, the list swings toward narrator, announcer, doctor, detective, bartender, soldier, and police officer.

In 1980-200, the top “newly popular” role (for both sexes) was “additional voices.”  For the time period 2000-present it was “zombie,” next was “housemate.”

The paper is here (pdf), hat tip goes to Samir Varma.

Here is a new and interesting article on whether there is greater female influence over cinematic box office these days.

In just about every field I looked at, having a successful parent makes you way more likely to be a big success, but the advantage is much smaller than it is at the top of politics.

Using the same methodology, I estimate that the son of an N.B.A. player has about a one in 45 chance of becoming an N.B.A. player. Since there are far more N.B.A. slots than Senate slots, this is only about an 800-fold edge.

Think about the N.B.A. further. The skills necessary to be a basketball player, especially height, are highly hereditary. But the N.B.A. is a meritocracy, with your performance easy to evaluate. If you do not play well, you will be cut, even if the team is the New York Knicks and your name is Patrick Ewing Jr. Father-son correlation in the N.B.A. is only one-eleventh as high as it is in the Senate.

Emphasis added by me.  And this:

An American male is 4,582 times more likely to become an Army general if his father was one; 1,895 times more likely to become a famous C.E.O.; 1,639 times more likely to win a Pulitzer Prize; 1,497 times more likely to win a Grammy; and 1,361 times more likely to win an Academy Award. Those are pretty decent odds, but they do not come close to the 8,500 times more likely a senator’s son is to find himself chatting with John McCain or Dianne Feinstein in the Senate cloakroom.

That is all from Seth Stephens-Davidowitz.

There are just 6 per cent more people working in greater Los Angeles than there were 25 years ago. By contrast, the Inland Empire has nearly doubled in size. In fact, the absolute number of jobs added in the Inland Empire since 1990 is nearly double the absolute number of jobs added in greater LA. To get a sense of how wild that is, the entire workforce of the Inland Empire was only 13 per cent the size of Los Angeles’s back in 1990. Even now, there are more than three workers in Los Angeles for every one in the Inland Empire.

It’s a little hard to see given the scale of the chart, but it’s also worth noting that LA experienced a Depression-level drop in employment in the early 1990s. Between January, 1990 and November, 1993, employment in the America’s second-biggest metro area fell by nearly 11 per cent. Employment didn’t return to its previous peak until July, 1999. Talk about a lost decade! (It may help explain this.)

That is from Matthew C. Klein, there is more here, about other American cities too, possibly FT-gated but interesting throughout.

Maybe this is too strange and squirrelly an example to deserve mention on MR, but I found it fascinating.  It starts with this:

This year’s rebounding leaderboard, at least in terms of rebounds per game, is topped by DeAndre Jordan and Andre Drummond, who also finished 1-2 last season. In a bygone era, you’d simply say they are the league’s best rebounders at this time. Yet it might not be that way at all.

There seems to be a huge oops:

Both the Clippers and Pistons have better defensive rebound rates with their star rebounders on the bench. How is that possible?

This is a big topic, but one possible reason could be the simple fact that neither Jordan nor Drummond is particularly concerned with boxing out…Drummond blocks out on the defensive glass just 5.97 times per 100 opportunities, lowest in the league among centers with at least 500 chances.

Jordan is a little better at 9.64, but that’s still the 11th-lowest total.

In other words, what really matters is marginal rebounding prowess, adjusting for how many rebounds you take away from the other players on your team.  Maybe an individual can pull in the ball more often by positioning himself to grab the low hanging fruit rebounds — often taking them from other team members — rather than boxing out the other team for the tough, contested rebounds.

Measurement really is changing the world.  The article is here, by Bradford Doolittle, ESPN gated.  Here is more on DeAndre Jordan, also ESPN gated.  That is one media source I pay for gladly.