Data Source

Research shows that about a quarter of the world’s wealthiest entrepreneurs dropped out of university or high school before going on to join the financial elite, a greater proportion than those who achieved masters degrees.

Here is the Murad Ahmed FT piece.  Only about five percent of these super-billionaires have achieved a doctorate.

The paper title is Believing there is no free will corrupts intuitive cooperation, and the authors are John Protzko, Brett Ouimette, and Jonathan Schooler.  The abstract is this:

Regardless of whether free will exists, believing that it does affects one’s behavior. When an individual’s belief in free will is challenged, one can become more likely to act in an uncooperative manner. The mechanism behind the relationship between one’s belief in free will and behavior is still debated. The current study uses an economic contribution game under varying time constraints to elucidate whether reducing belief in free will allows one to justify negative behavior or if the effects occur at a more intuitive level of processing. Here we show that although people are intuitively cooperative, challenging their belief in free will corrupts this behavior, leading to impulsive selfishness. If given time to think, however, people are able to override the initial inclination toward self-interest induced by discouraging a belief in free will.

I would say that we need a large swathe of society to believe in ideals of free will and individual responsibility, even though such concepts are not entirely faultless from a metaphysical point of view.  For a given thinker, it is worth asking whether he or she adds to or takes away from that social belief.  For some writers, the concepts of individual blame and responsibility apply only to their intellectual adversaries!

For the pointer I thank Ben Southwood.

There has been some back and forth on this topic over the last few years, but it now seems to be settled.  Neil Irwin reports:

new research…indicates the proportion of American workers who don’t have traditional jobs — who instead work as independent contractors, through temporary services or on-call — has soared in the last decade. They account for vastly more American workers than the likes of Uber alone.

Most remarkably, the number of Americans using these alternate work arrangements rose 9.4 million from 2005 to 2015. That was greater than the rise in overall employment, meaning there was a small net decline in the number of workers with conventional jobs.

…The labor economists Lawrence F. Katz of Harvard and Alan B. Krueger of Princeton found that the percentage of workers in “alternative work arrangements” — including working for temporary help agencies, as independent contractors, for contract firms or on-call — was 15.8 percent in the fall of 2015, up from 10.1 percent a decade earlier. (Only 0.5 percent of all workers did so through “online intermediaries,” and most of those appear to have been Uber drivers.)

And the shift away from conventional jobs and into these more distant employer-employee relationships accelerated in the last decade. By contrast, from 1995 to 2005, the proportion had edged up only slightly, to 10.1 percent from 9.3 percent. (The data are based on a person’s main job, so someone with a full-time position who does freelance work on the side would count as a conventional employee.)

Here is the full NYT coverage.

Georgeanne M. Artz, Kevin D. Duncan, Arthur P. Hall and Peter F. Orazem have a new paper on that topic.  The answer seems to be that state-level business conditions do not matter so much, at least not in their currently measurable forms:

This study submits 11 business climate indexes to tests of their ability to predict relative economic performance on either side of state borders. Our results show that most business climate indexes have no ability to predict relative economic growth regardless of how growth is measured. Some are negatively correlated with relative growth. Many are better at reporting past growth than at predicting the future. In the end, the most predictive business climate index is the Grant Thornton Index which was discontinued in 1989.

While I don’t think this is the final word on the topic, the burden of proof clearly lies on the side which claims they do matter a good deal.

This is one of my favorite links of the year so far, namely how every Chinese province got its name.  I cannot recommend it to most of you however, but if you ever have worried about Shanxi vs. Shaanxi, this is the place to go:

Shaanxi is unique amongst Chinese provinces in being the only one whose name is rendered not in Hanyu Pinyin but in Gwoyeu Romatzyh (GR), the romanization system used in pre-Communist China. Instead of using accents above letters as in Pinyin, tones in GR were reflected in spelling. In Pinyin, which was invented in 1958, the provinces Shanxi and Shaanxi are indistinguishable in spelling, so the old romanization was retained to remove this ambiguity. However, authorities still tacked on the Pinyin “xi” instead of the GR “shi” to spell out the second character, making Shaanxi’s name even more unusual by combining two entirely different romanization systems within a single name.

I say the most obscure Chinese province is the very small Ningxia 寧夏, outlined in red below, what do you think?  Or does it count only as an autonomous region?  Is Gansu perhaps a runner up?

ningxia

Which is the most obscure American state to an outsider?  Nebraska?  Idaho?  Somewhere else?  (I say it helps the Dakotas that you have two of them.)  I believe the Clintons put Arkansas on the map, globally speaking that is, thereby removing it from contention for this honor.

…sometimes known as “illegal aliens.”  Here goes:

…the work propensity of undocumented men is much larger than that of other groups in the population; that this gap has grown over the past two decades; and that the labor supply elasticity of undocumented men is very close to zero, suggesting that their labor supply is almost perfectly inelastic.

That is from George J. Borjas, hat tip goes to Luke Hamilton Carlso.

VIX2

Source and discussion here at the FT.

That is the conclusion from a new paper by Rebecca Diamond and Peta Persson (pdf), on Swedish data, here is part of the abstract:

Despite the fact that test score manipulation [by teachers] does not, per se, raise human capital, it has far-reaching consequences for the beneficiaries, raising their grades in future classes, high school graduation rates, and college initiation rates; lowering teen birth rates; and raising earnings at age 23. The mechanism at play suggests important dynamic complementarities: Getting a higher grade on the test serves as an immediate signaling mechanism within the educational system, motivating students and potentially teachers; this, in turn, raises human capital; and the combination of higher effort and higher human capital ultimately generates substantial labor market gains. This highlights that a higher grade may not primarily have a signaling value in the labor market, but within the educational system itself.

Again, the result is that “encouragement effects,” or alternatively “writing off effects,” are stronger than many of us might think.  Tell people enough times that they are a certain way, and eventually they will start to believe you.  I would say this is evidence for my “beasts into men” theory of education, though other interpretations are not ruled out.

For the pointer I thank Ben Southwood.

From Alexander Dubbs:

We use a simple machine learning model, logistically-weighted regularized linear least squares regression, in order to predict baseball, basketball, football, and hockey games. We do so using only the thirty-year record of which visiting teams played which home teams, on what date, and what the final score was. No real “statistics” are used. The method works best in basketball, likely because it is high-scoring and has long seasons. It works better in football and hockey than in baseball, but in baseball the predictions are closer to a theoretical optimum. The football predictions, while good, can in principle be made much better, and the hockey predictions can be made somewhat better. These findings tells us that in basketball, most statistics are subsumed by the scores of the games, whereas in baseball, football, and hockey, further study of game and player statistics is necessary to predict games as well as can be done.

That is an almost Hayekian result, and I wonder what the people at 538 will think of it.

For the pointer I thank Agustin Lebron.

Opportunity!  That is from Justin Wolfers.

*Engineers of Jihad*

by on March 18, 2016 at 2:16 am in Books, Data Source, Education | Permalink

The authors are Diego Gambetta and Steffen Hertog and the subtitle is The Curious Connection between Violent Extremism and Education.  This is an interesting and important book, and the core message is pretty simple:

In the Islamist sample [of terrorists] we were able to find the discipline of study for 207 of the 231 individuals who at some point had full or partial exposure to higher education…Unsurprisingly, the second most numerous group comprises 38 individuals who pursued Islamic studies.  But the largest group among the Islamist extremists is that of the engineers: 93 out of 207 individuals, or 44.9 percent of those whose type of degree we know, studied this subject.

And here is from the book’s conclusion:

Our findings about disciplines, personality traits, and political preferences are remarkably consistent.  The outstanding result we obtained is that the distribution of traits across disciplines mirrors almost exactly the distribution of disciplines across militant groups…engineers are present in groups in which social scientists, humanities graduates, and women are absent, and engineers possess traits — proneness to disgust, need for closure, in-group bias, and (at least tentatively) simplism…

Definitely recommended.

That is his new book and the subtitle is A New Approach for the Age of Globalization.

To be sure, this is an interesting work and it does go beyond the published articles by Milanovic many of you already are familiar with.  It is the best source on whether global inequality has gone up or down.  The chapter on the Kuznets curve –which considers whether there are general time series patterns in the historical evolution of inequality — will help you see that question in a new light, even though the final answer is the expected inconclusive one.

But ultimately the book is too sprawling and the conceptual discussions are not enlightening or sometimes they are absent altogether.  Not all inequalities are created alike, but we are offered insufficient tools for sorting out which inequalities might matter and whether those are what the data are picking up.  For one example of where this book goes wrong, Milanovic writes “It is the fundamentally ambivalent nature of globalization that I hope to bring out in this book.”  Yet almost all of the historical data involve examples where living standards have been going up because of globalization.  You might plausibly think “inequality on average is bad,” but that doesn’t mean you have to think that the Pareto-improving wealth boosts from globalization, even if they raise measured inequality, are ambiguous in normative terms.  They aren’t, they are strongly positive.

Or to cite another point, the author argues that “income and wealth inequality” are “the root cause” of prostitution.  A significant cause to be sure, but are not other inequalities — non-pecuniary inequalities for instance — relevant here?  I predict there would be plenty of prostitution in a society with full income equality or more realistically a guaranteed annual income.

There is plenty of talk of how plutocracy and rising inequality have an inexorable stranglehold on the American landscape, but very little consideration of whether inequality of happiness has gone up, or what kind of future technologies might lead to more equal real wage distributions.

Overall this book is worth reading, but still it is an example of how the economics profession emphasizes one kind of rigor and almost completely neglects rigor in argumentation and the application of concepts.

Eric Chyn, from the University of Michigan, has an interesting job market paper on this topic., which suddenly is being debated again.  The title is “Moved to Opportunity: The Long-Run Effect of Public Housing Demolition on Labor Market Outcomes of Children.” Here is the abstract:

This paper provides new evidence on the effects of moving out of disadvantaged neighborhoods on the long-run economic outcomes of children. My empirical strategy is based on public housing demolitions in Chicago which forced households to relocate to private market housing using vouchers. Specifically, I compare adult outcomes of children displaced by demolition to their peers who lived in nearby public housing that was not demolished. Displaced children are 9 percent more likely to be employed and earn 16 percent more as adults. These results contrast with the Moving-to-Opportunity (MTO) relocation study, which detected effects only for children who were young when their families moved. To explore this discrepancy, this paper also examines a housing voucher lottery program (similar to MTO) conducted in Chicago. I find no measurable impact on labor market outcomes for children in households that won vouchers. The contrast between the lottery and demolition estimates remains even after re-weighting the demolition sample to adjust for differences in observed characteristics. Overall, this evidence suggests lottery volunteers are negatively selected on the magnitude of their children’s gains from relocation. This implies that moving from disadvantaged neighborhoods may have substantially larger impact on children than what is suggested by results from voucher experiments where parents elect to participate.

Justin Fox argues that moving is hard, but basically more of the poor should move, at least using standard economic metrics for family well-being.  Results from the Katrina natural experiment indicate the same.  Ultimately we wish to protect people, not places per se.

Trump performed no better in states where the economy was the biggest issue than in other states. In the ten states where the economy was the top issue, Trump won eight, or 80 percent. In the five states where the economy was second, Trump won four . . . or 80 percent. His average margin of victory was 7.8 points in states where the economy ranked second but just 6.9 points in states where the economy was the top issue.

Trump also did worse among voters for whom the economy was a top issue than among other voters. He won voters who chose the economy as their top issue in 10 of 15 states, worse than his showing among voters over all, which he carried in 12 of 15. While he won jobs-and-economy voters in ten states, he won immigration voters in twelve, and terrorism voters in twelve. In all 15 states, Trump’s margin of victory was higher among at least one other category of voters than it was among jobs-and-economy voters. In eight states, Trump’s margins were greater on at least two other issues, and in two states his margins were lowest among jobs-and-economy voters.

…I believe that Trumpism is being driven primarily by cultural anxiety — by dissatisfaction with cultural change and perceived cultural decline.

Here is the Scott Winship NR piece.

I have been seeing so many pieces about how GOP elites are responsible for the rise of Trump.  These pieces offer many valid criticisms, but I have an alternative or should I say complementary theory: the people who have voted for Trump are responsible for the rise of Trump.  How is that for a complex account of causation and individual responsibility?

coreinflation

Source here.  As I’ve been saying, I see very little chance of an aggregate demand-based recession this year, the Fed’s December interest rate hike was not an obvious mistake, and we are not in any operative way in a liquidity trap right now.