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Entrepreneurial Marxism

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Carl Packman on Twitter has described my vision of socialism as “entrepreneurial Marxism.” I like that. Entrepreneurial Marxism is necessary, roughly compatible with Marx, and feasible.

Let’s start with the necessary. Here, we Marxists have a paradox. On the one hand, Marx thought that socialism required material abundance: it was the solution to Keynes’ problem (pdf) of what to do with our leisure time. As G.A.Cohen put it:

[Marx] thought that anything short of an abundance so complete that it removes all major conflicts of interests would guarantee continued social strife, "a struggle for necessities and all the old filthy business". It was because he was so uncompromisingly pessimistic about the social consequences of anything less than limitless abundance that Marx needed to be so optimistic about the possibility of that abundance (Self-ownership, Freedom and Equality, p10-11)

He thought capitalism would deliver such abundance: “No social order is ever destroyed before all the productive forces for which it is sufficient have been developed.” Lplong

This might, however, be too optimistic. Over the last ten years, productivity has almost stagnated – something we’ve not seen (except briefly in the 1880s) since the start of the industrial revolution. This suggests we’ll need a form of post-capitalism which delivers economic growth. Now, I’ll concede that a centrally planned economy might be good at generating growth in the sense of more of the same; it can deliver more pig-iron. But this isn’t the sort of growth we need now.  As Gilles Saint-Paul points out (pdf), growth must come from an increased variety of products. Centrally planned economies are lousy at this. Decentralized entrepreneurship is better.

And such entrepreneurship isn’t wholly incompatible with Marx. To Marx, it is our human nature to work and produce:

In creating a world of objects by his personal activity, in his work upon inorganic nature, man proves himself a conscious species-being (Economic and Philosophic Manuscripts.)

It’s for this reason, largely, that he condemned capitalism. Capitalism, he thought, forced us to do meaningless drudge work under the domination of others, and thus alienated us from both our nature and each other. It’s for this reason that Jon Elster has written: “Self-realization through creative work is the essence of Marx’s communism.” (Making Sense of Marx, p521.)

It’s likely that, for some at least, this self-realization will take the form of working under one’s own steam. In fact, Marx saw this:

A being does not regard himself as independent unless he is his own master, and he is only his own master when he owes his existence to himself. (Economic and Philosophic Manuscripts, quoted by Erich Fromm)

Marxists have traditionally interpreted this as to mean that collective self-mastery is necessary, through democratic control of the means of production. That’s true enough. For some people, though, it might mean individual own-mastery – working for oneself.

But wouldn’t this entail the very exploitation of others that Marx hated?

Maybe not so much. Even under capitalism, the profits (and hence exploitation) from innovative activity are small. And the prospects for exploitation under post-capitalism might be less, to the extent that intellectual property laws would be less friendly to incumbents and because fulfilling work elsewhere would make it hard for entrepreneurs to attract labour without offering something decent.

But wouldn’t this kill off innovation and entrepreneurship? Not necessarily, and not simply because I suspect a lot of such activity arises from intrinsic motives such as the urge to create things and solve problems. It’s also because there’ll be offsetting stimuli to entrepreneurship. One is that higher aggregate demand would close the innovations gap. Another is that post-capitalism would ensure a high supply of finance, for example via a state investment bank. And a third is that lower rewards to rent-seeking would force some bosses out of cushy monopolies and bureaucracies and into entrepreneurship.

Of course, I appreciate that all this will be sneered at from both sides – from Marxists claiming (with some justification) that I’m being unfaithful to Marx, and from some rightists who can’t get their tiny minds around the possibility that there are economic models other than capitalism and central planning. But I don’t give a shit.

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5 days ago
He clearly gives a shit. He hasn't addressed the level of coercion required to get to his destination, even if you assume the destination is optimal.
Princeton, NJ or NYC
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How Progressives See New York

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It's been a while since I have written about what progressives see when they look at New York.  But Maggie's Farm this morning gives a pointer to an article in the current New Republic that is an extreme example of the genre.  The article, by Amy Rose Spiegel, is titled "Who Killed New York City?".  Spiegel's piece is actually a review of two books -- "Vanishing New York" by Jeremiah Ross, and "Arbitrary Stupid Goal" by Tamara Shopsin.  Perhaps I should mention that an uncle of Ms. Shopsin's is a near neighbor of mine in Greenwich Village.

Just to set the table, here is my own take, from my "About" page, of the overall nature of change in Greenwich Village and New York City in the time I have lived here since the 1970s:

When I moved to this neighborhood in the 1970s the old buildings were here, but there were public safety issues and overall a slight air of seediness.  The subsequent years have seen renovation of older buildings, an influx of wealthier residents, and great improvement in the quality of the stores and restaurants.  Public safety has improved dramatically.  All in all, it has been a great place to live and raise a family.

 What's not to like?  Well, if you think like that, you are not a New York City progressive!

Let's get a few choice quotes from Spiegel's article (mostly from her summary of Moss's book):

Moss’s Vanishing New York is a history of how “wholesome” and corporate America caulked over the dark cracks and corners that once distinguished New York’s spirit, life, and community from the rest of the country’s. The book is an effortful reference for how New York morphed from a syncretic collection of diasporas—both extra-national and of the identity and mind—into a bland sovereignty of the mega-rich. . . .  [Moss] demonstrate[s] how 20th-century New York buckled under mercenary policies and institutions designed to benefit the rich. The 21st-century city became punitive, extraditing, and sometimes carceral toward the poor, nonwhite, and queer—and, now, to the middle class, like citizens with independent businesses of interest to real-estate vultures, or those living in subsidized residences, or in black areas. “Working-class and lower-income black, brown, and immigrant people [are] exiled to the suburbs as more affluent whites take the cities … the colorized suburb now receives the brutal treatment the inner city once did—neglect, predatory lending, and militarized policing that too often ends in the murder of black people.” New York’s role has flipped with suburbia’s: it is now closed to those without means. . . .  The city became untethered from its people and their homes, free-falling skyward in the luxury developments coaxed up by the global-finance billionaire Mayor Mike Bloomberg from 2001 until 2014. Glassy new buildings grayed the city’s appearance, affordability, and feeling. 

So, according to Spiegel and Ross, it just couldn't get more horrible.  But is any of this remotely connected to reality?  Where do these people get this stuff?  Certainly not by looking at any readily-available data or statistics.  Nor is there any examination of the plethora of progressive policies and redistribution programs that have been in effect throughout the period in question.  How could all of those programs have failed so miserably?  And if they didn't work, why will the next set of similar efforts do any better?

I could go on forever about this, but let's just consider a couple of those statements from the Spiegel piece in some detail:

“Working-class and lower-income black, brown, and immigrant people [are] exiled to the suburbs as more affluent whites take the cities . . . .

It is true that there has been a recent influx of some more affluent whites into a few neighborhoods of the City that previously were either lower-income areas (Lower East Side of Manhattan, Williamsburg and Bushwick in Brooklyn), or industrial or business areas (Long Island City in Queens and Downtown Brooklyn).  These areas constitute maybe 5% of the City's land area at most.  Look at the overall demographic data for the City and you find that this influx of affluent whites into a few areas is so small in the overall picture that you can't even find it.  Here is a link to a Wikipedia compilation of demographic data for New York City by race and borough for the censuses from 1900 through 2010.  Non-hispanic whites declined by about 500,000 from 1980 to 1990, another 350,000 from 1990 to 2000, and another 75,000 from 2000 to 2010.  Over that period, the percentage of non-hispanic whites in the City's population went from 52% to 33%.  The number of blacks grew by about 350,000 between 1980 and 2000, before registering a slight decline of about 40,000 between 2000 and 2010.  Hispanics have increased rapidly, by almost a million people and 10% of the population, with the rapid increase continuing right through the 2010 census (and beyond as far as I know).  Asians have also seen significant increases, even more so in the most recent years.  When you look at these numbers, you realize that these New Republic people just don't have any idea what they are talking about.

[New York] is now closed to those without means. . . .     

Again, try to find this in any data that you can locate.  It's funny, but the "poverty rate" reported by the Census Bureau for New York City for the most recent period available (July 2016) is 20.6%, a good 7 points above the full U.S. rate of 13.5%.  I have been very critical of these numbers, but they are the official numbers.  If you are going to take the position, in the face of these numbers, that "New York is closed to those without means," don't you owe us at least some explanation of how it could be that the official data show New York with proportionately far more "people without means" than the rest of the country?  And how is it that New York's huge suite of programs to assist those "without means" and help them to live here -- public housing for 500,000 people, other housing subsidy programs for hundreds of thousands more, rent regulation for another 2 million people, welfare, Medicaid, food stamps, etc., etc. -- don't seem to be doing any good?  What is the next set of coercive government programs you are proposing that is supposedly going to work, when the previous dozens of programs have failed so disastrously?  And, if you believe that the City's proper role is to welcome those "without means" and to improve their lives with government programs of various sorts, how exactly do you make that work without also attracting a critical mass of the affluent to pay the bills?

So no, none of this is remotely connected to reality.  These are the ravings of people afflicted with some combination of extreme and irrational guilt because of their own prosperity, combined with jealousy for those they think are too wealthy.  Why?  I can't explain it.  But it's the official New York mentality today. 

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7 days ago
"So no, none of this is remotely connected to reality. "
Princeton, NJ or NYC
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Links 8/17: On The Site Of The Angels

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Benjamin Lay was a four-foot-tall Quaker abolitionist who, among other unusual forms of activism, kidnapped a slaveowner’s child to give them a taste of what slaves had to go through.

ProPublica: The Myth Of Drug Expiration Dates. Most drugs (strong exception for tetracyclines) are neither dangerous nor ineffective once expired. The idea of “drug expiration dates” is just bureaucratic boilerplate. It also costs health systems billions of dollars per year. And key quote: “ProPublica has been researching why the U.S. health care system is the most expensive in the world. One answer, broadly, is waste — some of it buried in practices that the medical establishment and the rest of us take for granted. We’ve documented how hospitals often discard pricey new supplies, how nursing homes trash valuable medications after patients pass away or move out, and how drug companies create expensive combinations of cheap drugs. Experts estimate such squandering eats up about $765 billion a year — as much as a quarter of all the country’s health care spending.”

xhxhxhxh: the research on what leads to intrastate conflict and rebellion. No effect for traditional worries like income inequality or ethnic polarization, etc. Mostly just bad economy and slow growth.

Vice: Everyone Hates Neoliberals, So We Talked To Some. What do self-described neoliberals identify as the core of their philosophy? Key quote from Samuel Hammond: “We are free market globalists, and evangelists of the amazing power of trade liberalization to create wealth, eliminate disease, lift hundreds of millions of people from poverty, and end the pre-conditions for war. At the same time, we are more pragmatic and consequentialist than our utopian and deontological libertarian counterparts… We believe free markets and commercial capitalism are the tools of social justice, rather than the enemy.”

Tengrism, the religion of Genghis Khan and other steppe nomads, is making a comeback in Central Asian republics looking for a suitably nationalist alternative to Islam.

Study: “Across four samples (including a nationally representative sample), we find that stronger obsessive-compulsive symptoms are associated with more right-wing ideological preferences, particularly for social issues.” This should probably be considered in context of Haidt’s work on the Purity foundation, and the Germ Theory Of Democracy.

How Class In China Became Politically Incorrect. Key quote: “Research by the University of Sydney’s David Goodman has found that around 84% of today’s elite are direct descendants of the elite from pre-1949. This suggests that six decades of Communism may not have a dramatic impact upon the elites”. Seen on Twitter with the commentary “Darwin beats Marx every time”.

From Rationalist Tumblr: those claims that medical error is the third-leading cause of death, kills 200,000 people every year, etc? Totally exaggerated. And most people interpret it as ‘number of stupid mistakes by doctors’ when it really means more like “the number of bad health outcomes that could be prevented with perfect god-like-omniscient understanding of all patents’ health situation”.

Andrew Gelman takes on James Heckman; read the comments for some good debate around Perry-Preschool-style interventions.

2016 election margin by district by population. Make sure to spin it around to get the full 3-D effect. This is the first graph I’ve seen that manages to combine two dimensions of space plus two extra variables in a really good instantly-readable way.

72 top researchers and statisticians (SSC readers might recognize Ioannidis, Wagenmakers, Nyhan, & Vazire) sign their names to a paper recommending the threshold for statistical significance be raised from p = 0.05 to p = 0.005 to decrease false positives and improve replicability. Some pushback from other statisticians involved in the replicability movement including Timothy Bates and (preemptively) Daniel Lakens. Both groups agree that it’s a hackish solution that ignores all the important subtleties around the question, but disagree on whether having something easy is at least better than nothing.

US Court Grants Journals Millions Of Dollars In Damages From Sci-Hub. It sure would be a shame if this caused a Streisand Effect where many more people became aware of the existence of Sci-Hub, a free and easy-to-use source for almost all otherwise-paywalled scientific papers, which by the way depends on reader donations to stay online.

Related study: Sci-Hub Provides Access To Nearly All Scholarly Literature. “As of March 2017, we find that Sci-Hub’s database contains 68.9% of all 81.6 million scholarly articles, which rises to 85.2% for those published in closed access journals….we estimate that over a six-month period in 2015–2016, Sci-Hub provided access for 99.3% of valid incoming requests. Hence, the scope of this resource suggests the subscription publishing model is becoming unsustainable.”

The Intercept: US Lawmakers Seek To Criminally Outlaw Support For Boycott Campaign Against Israel vs. Volokh Conspiracy: Israel Anti-Boycott Does Not Violate Free Speech. Some people on Rationalist Tumblr explained this to me: the bill says that Americans can’t join foreign anti-Israel boycotts, but doesn’t prevent them from starting their own, including ones that are exactly like the foreign ones and can’t be distinguished from them in any way. The bill’s proponents say that the only thing it does is prevent foreign countries from demanding American companies boycott Israel as a precondition to doing business there. I think the opposing argument is mostly that laws often get overapplied, and this one seems more overapplicable than most.

Machine Learning Applied To Initial Romantic Attraction: “Crucially [machine learning techniques] were unable to predict relationship variance using any combination of traits and preferences reported beforehand.” See also my previous post on this topic.

Study by Amir Sariaslan and others: after adjusting for unobserved familial risk factors, no link between poverty and crime.

Edge conversation on various things with Rory Sutherland. Starts with why art prices are so much more responsive to fame than architecture prices (a Picasso might cost a thousand times more than a less painter’s work; a Frank Lloyd Wright house costs 1-3% more than a house built by a nobody) and only gets better from there.

Hypermagical Ultraomnipotence: Why the tradeoffs constraining human cognition do not limit artificial superintelligences.

I was really excited about an upcoming depression treatment called NSI-189 that seemed to do everything right and had the potential to revolutionize the field. Well, it just failed its clinical trial.

First genetically-engineered human embryos in the US. Found it was possible to safely correct a defective gene without damaging the rest of the genome (and here’s the paper). The embryos were destroyed and not carried to term. Any kid born with a correctable genetic disorder after today is going to have one heck of a legitimate grievance against our philosophical establishment.

Freddie deBoer: Bernie Sanders Is A Socialist In Name Only. I really like this piece, and I was going to write it if nobody else did. Most of the policies being mooted by the supposedly socialist left today – Medicare-for-all, better social safety nets, et cetera – are well within the bounds of neoliberalism – ie private property and capitalist economies should exist, but the state should help poor people. “Socialism” should be reserved for systems that end private property and nationalize practically everything. I’m worried that people will use the success of neoliberal systems in eg Sweden to justify socialism, and then, socialism having been justified, promote actual-dictionary-definition socialism. To a first approximation, Sweden is an example of capitalists proving socialism isn’t necessary; Venezuela is an example of socialism actually happening.

Did you know: the first recorded evidence of Sanskrit comes from Syria, not India.

American Runners Are Getting Slower. Definitely see the r/slatestarcodex comment thread. A good example of ruling out a lot of possible confounding factors for a seemingly bizarre result – but I find the argument that the best athletes are moving into other sports more convincing than the article’s own nutritional theory.

Retailer apologizes after accidentally selling product saying “MY FAVORITE COLOR IS HITLER”.

Remember how everyone thought that, if we legalized euthanasia, it would be used as a tool to kill marginalized and oppressed people who couldn’t say no to it? Data after a year of California’s right-to-die law finds it’s disproportionately used by college-educated white men and concludes that Death Is A Social Privilege.

What jobs have the highest and lowest divorce rates? (conditional on being married in the first place). Key finding: everything math- and computer-related has much lower divorce rates than everything else.

Widespread Selection Of Positive Selection In Common Risk Alleles Associated With Autism Spectrum Disorder. This is pretty complicated, but I think what it’s saying is that in general, having autism risk genes increases your intelligence up until the point when you actually have autism, when you become vulnerable to all of the normal autism-related-cognitive-deficits. But this is probably very heterogenous across risk genes and other risk factors.

Israel working to shut down Al-Jazeera out of concerns about “encouraging terrorism”; pretty good example of how anything less than free-speech-absolutism can be circumvented by a sufficiently urgent-sounding plea. [EDIT: But see here]

Facebook shuts down an experimental language AI project, and the media goes crazy.Everyone on every side of the AI risk debate, from Eliezer Yudkowsky to Yann LeCun, wants to make it clear they think this is stupid and it has nothing to do with the position of any reasonable person.

An academic study into horseshoe theory? Authoritarianism and Affective Polarization: A New View on the Origins of Partisan Extremism finds that “strong Republicans and Democrats are psychologically similar, at least with respect to authoritarianism…these findings support a view of mass polarization as nonsubstantive and group-centric, not driven by competing ideological values or clashing psychological worldviews.” Okay, but you still need some explanation of how people choose which group to be in, right?

Single Dose Testosterone Administration Impairs Cognitive Reflection In Men. Note that “single dose testosterone” is very different from “having lots of testosterone chronically”, “being fetally exposed to testosterone”, “being genetically male”, and five million other things it would be easy to confuse this with.

The Hyderabad office of India’s Department of Fisheries.

British Medical Journal Global Health: new data available after the US invasion of Iraq conclusively determines that the claim that US sanctions starved thousands of Iraqi children was a lie deliberately spread by Saddam Hussein.

Congress passes “right to try” bill allowing terminally ill people to access not-yet-FDA-approved medications. Someone in the comments noted that there’s already a procedure for terminally ill individuals to appeal to the FDA to do this, and FDA approves 99% of such requests already. So not only is this mostly a symbolic victory, but one worries that the 1% of requests that aren’t approved might be pretty bad ideas. [EDIT: But see here]

j9461701 on the subreddit posts about the extreme male brain theory of autism, finding it mostly unconvincing. I mostly agree, though it’s important to remember that hormone differences can have varying and seemingly paradoxical effects depending on what level of the various metabolic processes they come in at.

In response to my question about why prediction markets aren’t used more, Daniel Reeves links me to a study of his offering a pretty simple response: yeah, they’re better than other things, but not much better, and they’re a lot more annoying to use.

Paper on empathy (via Rolf Degen): people with born with a condition that makes them unable to feel pain feel like other people are just weaklings who exaggerate their problems. Classify under “metaphors for life”.

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8 days ago
"Sweden is an example of capitalists proving socialism isn’t necessary; Venezuela is an example of socialism actually happening."
Princeton, NJ or NYC
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Contra Grant On Exaggerated Differences

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An article by Adam Grant called Differences Between Men And Women Are Vastly Exaggerated is going viral, thanks in part to a share by Facebook exec Sheryl Sandberg. It’s a response to an email by a Google employee saying that he thought Google’s low female representation wasn’t a result of sexism, but a result of men and women having different interests long before either gender thinks about joining Google. Grant says that gender differences are small and irrelevant to the current issue. I disagree.

Grant writes:

It’s always precarious to make claims about how one half of the population differs from the other half—especially on something as complicated as technical skills and interests. But I think it’s a travesty when discussions about data devolve into name-calling and threats. As a social scientist, I prefer to look at the evidence.

The gold standard is a meta-analysis: a study of studies, correcting for biases in particular samples and measures. Here’s what meta-analyses tell us about gender differences:

When it comes to abilities, attitudes, and actions, sex differences are few and small.

Across 128 domains of the mind and behavior, “78% of gender differences are small or close to zero.” A recent addition to that list is leadership, where men feel more confident but women are rated as more competent.

There are only a handful of areas with large sex differences: men are physically stronger and more physically aggressive, masturbate more, and are more positive on casual sex. So you can make a case for having more men than women… if you’re fielding a sports team or collecting semen.

The meta-analysis Grant cites is Hyde’s, available here. I’ve looked into it before, and I don’t think it shows what he wants it to show.

Suppose I wanted to convince you that men and women had physically identical bodies. I run studies on things like number of arms, number of kidneys, size of the pancreas, caliber of the aorta, whether the brain is in the head or the chest, et cetera. 90% of these come back identical – in fact, the only ones that don’t are a few outliers like “breast size” or “number of penises”. I conclude that men and women are mostly physically similar. I can even make a statistic like “men and women are physically the same in 78% of traits”.

Then I go back to the person who says women have larger breasts and men are more likely to have penises, and I say “Ha, actually studies prove men and women are mostly physically identical! I sure showed you, you sexist!”

I worry that Hyde’s analysis plays the same trick. She does a wonderful job finding that men and women have minimal differences in eg “likelihood of smiling when not being observed”, “interpersonal leadership style”, et cetera. But if you ask the man on the street “Are men and women different?”, he’s likely to say something like “Yeah, men are more aggressive and women are more sensitive”. And in fact, Hyde found that men were indeed definitely more aggressive, and women indeed definitely more sensitive. But throw in a hundred other effects nobody cares about like “likelihood of smiling when not observed”, and you can report that “78% of gender differences are small or zero”.

Hyde found moderate or large gender differences in (and here I’m paraphrasing very scientific-sounding constructs into more understandable terms) aggressiveness, horniness, language abilities, mechanical abilities, visuospatial skills, mechanical ability, tendermindness, assertiveness, comfort with body, various physical abilities, and computer skills.

Perhaps some peeople might think that finding moderate-to-large-differences in mechanical abilities, computer skills, etc supports the idea that gender differences might play a role in gender balance in the tech industry. But because Hyde’s meta-analysis drowns all of this out with stuff about smiling-when-not-observed, Grant is able to make it sound like this proves his point.

It’s actually worse than this, because Grant misreports the study findings in various ways. For example, he states that the sex differences in physical aggression and physical strength are “large”. The study very specifically says the opposite of this. Its three different numbers for physical aggression (from three different studies) are 0.4, 0.59, and 0.6, and it sets a cutoff for “large” effects at 0.66.

On the other hand, Grant fails to report an effect that actually is large: mechanical reasoning ability (in the paper as Feingold 1998 DAT mechanical reasoning). There is a large gender difference on this, d = 0.76.

And although Hyde doesn’t look into it in her meta-analysis, multiple other meta-analyses, like this one, find a large effect size (d = 1.18) for thing-oriented vs. people-oriented interest, the very claim that the argument that Grant is trying to argue against centers around.

So Grant tries to argue against large thing-oriented vs. people-oriented differences by citing a meta-analysis that doesn’t look into them at all. He then misreports the findings of that meta-analysis, exaggerating effects that fit his thesis and failing to report the ones that don’t. Finally, he cites a “summary statistic” that averages the variation we’re looking for out by combining it with a bunch of noise, and claims the noise proves his point even though the variation is as big as ever.


Grant claims that there are no sex differences in mathematical ability, then goes on to claim that the sex differences in mathematical ability are culturally determined. I’m not really sure what to do with this. Anyway:

Girls do as well as boys—or slightly better—in math in elementary, but boys have an edge by high school. Male advantages are more likely to exist in countries that lack gender equity in school enrollment, women in research jobs, and women in parliament—and that have stereotypes associating science with males.

Since Grant and I agree that there is no gender difference in ability, then we should probably redirect ourselves back to the original question: why is there a gender difference in tech-industry-representation? Here his theory that this reflects “countries that lack gender equity in school enrollment” and “stereotypes associating science with males” fails.

Galpin investigated the percent of women in computer classes all around the world. Her number of 26% for the US is slightly higher than I usually hear, probably because it’s older (the percent women in computing has actually gone down over time!). The least sexist countries I can think of – Sweden, New Zealand, Canada, etc – all have somewhere around the same number (30%, 20%, and 24%, respectively). The most sexist countries do extremely well on this metric! The highest numbers on the chart are all from non-Western, non-First-World countries that do middling-to-poor on the Gender Development Index: Thailand with 55%, Guyana with 54%, Malaysia with 51%, Iran with 41%, Zimbabwe with 41%, and Mexico with 39%. Needless to say, Zimbabwe is not exactly famous for its deep commitment to gender equality.

Why is this? It’s a very common and well-replicated finding that the more progressive and gender-equal a country, the larger gender differences in personality of the sort Hyde found become. I agree this is a very strange finding, but it’s definitely true. See eg Journal of Personality and Social Psychology, Sex Differences In Big Five Personality Traits Across 55 Cultures:

Previous research suggested that sex differences in personality traits are larger in prosperous, healthy, and egalitarian cultures in which women have more opportunities equal with those of men. In this article, the authors report cross-cultural findings in which this unintuitive result was replicated across samples from 55 nations (n = 17,637).

In case you’re wondering, the countries with the highest gender differences in personality are France, Netherlands, and the Czech Republic. The countries with the lowest sex differences are Indonesia, Fiji, and the Congo.

I conclude that whatever gender-equality-stereotype-related differences Grant has found in the nonexistent math ability difference between men and women, they are more than swamped by the large opposite effects in gender differences in personality. This meshes with what I’ve been saying all along: outside a few exceptions that don’t matter for the current discussion, it’s not about ability, it’s about interest.


We know that interests are highly malleable. Female students become significantly more interested in science careers after having a teacher who discusses the problem of underrepresentation. And at Harvey Mudd College, computer science majors were around 10% women a decade ago. Today they’re 55%.

I highly recommend Freddie deBoer’s Why Selection Bias Is The Most Powerful Force In Education. If an educational program shows amazing results, and there’s any possible way it’s selection bias, it’s selection bias.

I looked into Harvey Mudd’s STEM admission numbers, and, sure enough, they admits women at 2.5x the rate as men. So, yeah, it’s selection bias.

I don’t blame them. All they have to do is cultivate a reputation as a place to go if you’re a woman interested in computer science, attract lots of female CS applicants, then make sure to admit all the CS-interested female applicants they get. In exchange, they get constant glowing praise from every newspaper in the country (1, 2,
3, 4, 5, 6, 7, 8, 9, 10, etc, etc, etc).

How would we know this was selection bias if we couldn’t just look at the numbers? The graph that Grant himself cites just above this statement shows that, over the same ten year period, percent women CS graduates has declined nationwide. This has corresponded with such a massive push to get more women in tech that…well, that a college which succeeds will get constant glowing praise from every newspaper in the country even when they admit they’re using selection bias. Do you think no one else has tried? Every college diversity office in the country is working overtime to try to get more women into tech, there are women in tech scholarships, women in tech conferences, women in tech prizes – and, over the period that’s happened, Grant’s own graph shows the percent of women in tech going down.

(I don’t understand why it’s going down, but my guess is a combination of constant messaging that there are no women in tech making women think it isn’t for them, plus the effect from society getting more gender-equitable that we described in Part II – ie we’re now less like Zimbabwe, and so we can’t expect our gender ratios to be as good as theirs are).

Look. If I recruit only gingers, and I admit only gingers, I can get a 100% ginger CS program. That doesn’t mean I’ve proven that gingers are really more interested in CS than everyone else, and it was just discrimination holding them back. It means I’ve done what every single private school and college does anyway, all the time – finagle with admissions to make myself look good.


Back to Grant:

4. There are sex differences in interests, but they’re not biologically determined.

The data on occupational interests do reveal strong male preferences for working with things and strong female preferences for working with people. But they also reveal that men and women are equally interested in working with data.

So why are there so many more male than female engineers? Because women have systematically been discouraged from working with computers. Look at trends in college majors: since the 1980s, the proportion of female majors has gone up in science and medicine and law, but down in computer science.

Before we discuss this, a quick step back.

In the year 1850, women were locked out of almost every major field, with a few exceptions like nursing and teaching. The average man of the day would have been equally confident that women were unfit for law, unfit for medicine, unfit for mathematics, unfit for linguistics, unfit for engineering, unfit for journalism, unfit for psychology, and unfit for biology. He would have had various sexist justifications – women shouldn’t be in law because it’s too competitive and high-pressure; women shouldn’t be in medicine because they’re fragile and will faint at the sight of blood; et cetera.

As the feminist movement gradually took hold, women conquered one of these fields after another. 51% of law students are now female. So are 49.8% of medical students, 45% of math majors, 60% of linguistics majors, 60% of journalism majors, 75% of psychology majors, and 60% of biology postdocs. Yet for some reason, engineering remains only about 20% female.

And everyone says “Aha! I bet it’s because of negative stereotypes!”

This makes no sense. There were negative stereotypes about everything! Somebody has to explain why the equal and greater negative stereotypes against women in law, medicine, etc were completely powerless, yet for some reason the negative stereotypes in engineering were the ones that took hold and prevented women from succeeding there.

And if your answer is just going to be that apparently the negative stereotypes in engineering were stronger than the negative stereotypes about everything else, why would that be? Put yourself in the shoes of our Victorian sexist, trying to maintain his male privilege. He thinks to himself “Well, I suppose I could tolerate women doctors saving my life. And if I had to, I would accept women going into math and learning the secrets of the Universe itself. I’m even sort of okay with women going into journalism and crafting the narratives that shape our world. But women building bridges? NO MERE FEMALE COULD EVER DO SUCH A THING!” Really? This is the best explanation the world can come up with? Doesn’t anyone have at least a little bit of curiousity about this?

(and I don’t think it’s just coincidence – ie I don’t think it’s just that a bunch of head engineers happened to be really sexist, and a bunch of head doctors happened to be really non-sexist. The same patterns apply through pretty much every First World country, and if it were just a matter of personalities you would expect them to differ from place to place.)

Whenever I ask this question, I get something like “engineering and computer science are two of the highest-paying, highest-status jobs, so of course men would try to keep women out of them, in order to maintain their supremacy”. But I notice that doctors and lawyers are also pretty high-paying, high-status jobs, and that nothing of the sort happened there. And that when people aren’t using engineering/programming’s high status to justify their beliefs about gender stereotypes in it, they’re ruthlessly making fun of engineers and programmers, whether it’s watching Big Bang Theory or reading Dilbert or just going on about “pocket protectors”.

Meanwhile, men make up only 10% of nurses, only 20% of new veterinarians, only 25% of new psychologists, about 25% of new paediatricians, about 26% of forensic scientists, about 28% of medical managers, and 42% of new biologists.

Note that many of these imbalances are even more lopsided than the imbalance favoring men in technology, and that many of these jobs earn much more than the average programmer. For example, the average computer programmer only makes about $80,000; the average veterinarian makes about $88,000, and the average pediatrician makes a whopping $170,000.

As long as you’re comparing some poor woman janitor to a male programmer making $80,000, you can talk about how it’s clearly sexism against women getting the good jobs. But once you take off the blinders and try to look at an even slightly bigger picture, you start wondering why veterinarians, who make even more money than that, are even more lopsidedly female than programmers are male. And then you start thinking that maybe you need some framework more sophisticated than the simple sexism theory in order to predict who’s doing all of these different jobs. And once you have that framework, maybe the sexism theory isn’t necessary any longer, and you can throw it out, and use the same theory to predict why women dominate veterinary medicine and psychology, why men dominate engineering and computer science, and why none of this has any relation at all to what fields that some sexist in the 1850s wanted to keep women out of.

So let’s look deeper into what prevents women from entering these STEM fields.

Does it happen at the college level? About 20% of high school students taking AP Computer Science are women. The ratio of women graduating from college with computer science degrees is exactly what you would expect from the ratio of women who showed interest in it in high school (the numbers are even lower in Britain, where 8% of high school computer students are girls. So differences exist before the college level, and nothing that happens at the college level – no discriminatory professors, no sexist classmates – change the numbers at all.

Does it happen at the high school level? There’s not a lot of obvious room for discrimination – AP classes are voluntary; students who want to go into them do, and students who don’t want to go into them don’t. There are no prerequisites except basic mathematical competency or other open-access courses. It seems like of the people who voluntarily choose to take AP classes that nobody can stop them from going into, 80% are men and 20% are women, which exactly matches the ratio of each gender that eventually get tech company jobs.

Rather than go through every step individually, I’ll skip to the punch and point out that the same pattern repeats in middle school, elementary school, and about as young as anybody has ever bothered checking. So something produces these differences very early on? What might that be?

Might young women be avoiding computers because they’ve absorbed stereotypes telling them that they’re not smart enough, or that they’re “only for boys”? No. As per Shashaani 1997, “[undergraduate] females strongly agreed with the statement ‘females have as much ability as males when learning to use computers’, and strongly disagreed with the statement ‘studying about computers is more important for men than for women’. On a scale of 1-5, where 5 represents complete certainty in gender equality in computer skills, and 1 completely certainty in inequality, the average woman chooses 4.2; the average male 4.03. This seems to have been true since the very beginning of the age of personal computers: Smith 1986 finds that “there were no significant differences between males and females in their attitudes of efficacy or sense of confidence in ability to use the computer, contrary to expectation…females [showed] stronger beliefs in equity of ability and competencies in use of the computer.” This is a very consistent result and you can find other studies corroborating it in the bibliographies of both papers.

Might girls be worried not by stereotypes about computers themselves, but by stereotypes that girls are bad at math and so can’t succeed in the math-heavy world of computer science? No. About 45% of college math majors are women, compared to (again) only 20% of computer science majors. Undergraduate mathematics itself more-or-less shows gender parity. This can’t be an explanation for the computer results.

Might sexist parents be buying computers for their sons but not their daughters, giving boys a leg up in learning computer skills? In the 80s and 90s, everybody was certain that this was the cause of the gap. Newspapers would tell lurid (and entirely hypothetical) stories of girls sitting down to use a computer when suddenly a boy would show up, push her away, and demand it all to himself. But move forward a few decades and now young girls are more likely to own computers than young boys – with zero little change in the high school computer interest numbers. So that isn’t it either.

So if it happens before middle school, and it’s not stereotypes, what might it be?

One subgroup of women does not display these gender differences at any age. These are women with congenital adrenal hyperplasia, a condition that gives them a more typically-male hormone balance. For a good review, see Gendered Occupational Interests: Prenatal Androgen Effects on Psychological Orientation to Things Versus People. They find that:

Consistent with hormone effects on interests, females with CAH are considerably more interested than are females without CAH in male-typed toys, leisure activities, and occupations, from childhood through adulthood (reviewed in Blakemore et al., 2009; Cohen-Bendahan et al., 2005); adult females with CAH also engage more in male-typed occupations than do females without CAH (Frisén et al., 2009). Male-typed interests of females with CAH are associated with degree of androgen exposure, which can be inferred from genotype or disease characteristics (Berenbaum et al., 2000; Meyer-Bahlburg et al., 2006; Nordenström et al., 2002). Interests of males with CAH are similar to those of males without CAH because both are exposed to high (sex-typical) prenatal androgens and are reared as boys.

Females with CAH do not provide a perfect test of androgen effects on gendered characteristics because they differ from females without CAH in other ways; most notably they have masculinized genitalia that might affect their socialization. But, there is no evidence that parents treat girls with CAH in a more masculine or less feminine way than they treat girls without CAH (Nordenström et al., 2002; Pasterski et al., 2005). Further, some findings from females with CAH have been confirmed in typical individuals whose postnatal behavior has been associated with prenatal hormone levels measured in amniotic fluid. Amniotic testosterone levels were found to correlate positively with parent-reported male-typed play in girls and boys at ages 6 to 10 years (Auyeung et al., 2009).

The psychological mechanism through which androgen affects interests has not been well-investigated, but there is some consensus that sex differences in interests reflect an orientation toward people versus things (Diekman et al., 2010) or similar constructs, such as organic versus inorganic objects (Benbow et al., 2000). The Things-People distinction is, in fact, the major conceptual dimension underlying the measurement of the most widely-used model of occupational interests (Holland, 1973; Prediger, 1982); it has also been used to represent leisure interests (Kerby and Ragan, 2002) and personality (Lippa, 1998).

In their own study, they compare 125 such women and find a Things-People effect size of -0.75 – that is, the difference between CAH women and unaffected women is more than half the difference between men and unaffected women. They write:

The results support the hypothesis that sex differences in occupational interests are due, in part, to prenatal androgen influences on differential orientation to objects versus people. Compared to unaffected females, females with CAH reported more interest in occupations related to Things versus People, and relative positioning on this interest dimension was substantially related to amount of prenatal androgen exposure.

What is this “object vs. people” distinction?

It’s pretty relevant. Meta-analyses have shown a very large (d = 1.18) difference in healthy men and women (ie without CAH) in this domain. It’s traditionally summarized as “men are more interested in things and women are more interested in people”. I would flesh out “things” to include both physical objects like machines as well as complex abstract systems; I’d also add in another finding from those same studies that men are more risk-taking and like danger. And I would flesh out “people” to include communities, talking, helping, children, and animals.

So this theory predicts that men will be more likely to choose jobs with objects, machines, systems, and danger; women will be more likely to choose jobs with people, talking, helping, children, and animals.

Somebody armed with this theory could pretty well pretty well predict that women would do well in medicine and law, since both of them involve people, talking, and helping. They would predict that women would dominate veterinary medicine (animals, helping), psychology (people, talking, helping, sometimes children), and education (people, children, helping). Of all the hard sciences, they might expect women to prefer biology (animals). And they might expect men to do best in engineering (objects, machines, abstract systems, sometimes danger) and computer science (machines, abstract systems).

I mentioned that about 50% of medical students were female, but this masks a lot of variation. There are wide differences in doctor gender by medical specialty. For example:

A privilege-based theory fails – there’s not much of a tendency for women to be restricted to less prestigious and lower-paying fields – Ob/Gyn (mostly female) is extremely lucrative, and internal medicine (mostly male) is pretty low-paying for a medical job.

But the people/thing theory above does extremely well! Ob/Gyn is babies, Pediatrics is babies/children, Psychiatry is people/talking (and of course women are disproportionately child psychiatrists), and family medicine is people/talking/babies/children.

Meanwhile, Radiology is machines and no patient contact, Anaesthesiology is also machines and no patient contact, Emergency Medicine is danger, and Surgery is machines, danger, and no patient contact.

Here’s another fun thing you can do with this theory: understand why women are so well represented in college math classes. Women are around 20% of CS majors, physics majors, engineering majors, etc – but almost half of math majors! This should be shocking. Aren’t we constantly told that women are bombarded with stereotypes about math being for men? Isn’t the archetypal example of children learning gender roles that Barbie doll that said “Math is hard, let’s go shopping?” And yet women’s representation in undergraduate math classes is really good – about 45%.

I was totally confused by this for a while until a commenter directed me to the data on what people actually do with math degrees. The answer is mostly: they become math teachers. They work in elementary schools and high schools, with people.

Then all those future math teachers leave for the schools after undergrad, and so math grad school ends up with much the same male-tilted gender balance as CS, physics, and engineering grad school.

This seems to me like the clearest proof that women being underrepresented in CS/physics/etc is just about different interests. It’s not that they can’t do the work – all those future math teachers do just as well in their math majors as everyone else. It’s not that stereotypes of what girls can and can’t do are making them afraid to try – whatever stereotypes there are about women and math haven’t dulled future math teachers’ willingness to do math majors one iota. And it’s not even about colleges being discriminatory and hostile – or at least however discriminatory and hostile they are it doesn’t drive away those future math teachers. It’s just that women are more interested in some jobs, and men are more interested in others. Figure out a way to make math people-oriented, and women flock to it. If there were as many elementary school computer science teachers as there are math teachers, gender balance would equalize without any other effort.

I’m not familiar with any gender breakdown of legal specialties, but I will bet you that family law, child-related law, and various prosocial helping-communities law are disproportionately female, and patent law, technology law, and law working with scary dangerous criminals are disproportionately male. And so on for most other fields.

This theory gives everyone what they want. It explains the data about women in tech. It explains the time course around women in tech. It explains other jobs like veterinary medicine where women dominate. It explains which medical subspecialties women will be dominant or underrepresented in. It doesn’t claim that women are “worse than men” or “biologically inferior” at anything. It doesn’t say that no woman will ever be interested in things, or no man ever interested in people. It doesn’t say even that women in tech don’t face a lot of extra harassment (any domain with more men than women will see more potential perpetrators concentrating their harassment concentrated on fewer potential victims, which will result in each woman being more harassed).

It just says that sometimes, in a population-based way that doesn’t necessarily apply to any given woman or any given man, women and men will have some different interests. Which should be pretty obvious to anyone who’s spent more than a few minutes with men or women.


Why am I writing this?

Grant’s piece was in response to a person at Google sending out a memo claiming some of this stuff. Here is a pretty typical response that a Googler sent to that memo – I’ve blocked the name so this person doesn’t get harassed over it, but if you doubt this is real I can direct you to the original:

A lot of people without connections to the tech industry don’t realize how bad it’s gotten. This is how bad. It would be pointless trying to do anything about this person in particular. This is the climate.

Silicon Valley was supposed to be better than this. It was supposed to be the life of the mind, where people who were interested in the mysteries of computation and cognition could get together and make the world better for everybody. Now it’s degenerated into this giant hatefest of everybody writing long screeds calling everyone else Nazis and demanding violence against them. Where if someone disagrees with the consensus, it’s just taken as a matter of course that we need to hunt them down, deny them of the cloak of anonymity, fire them, and blacklist them so they can never get a job again. Where the idea that we shouldn’t be a surveillance society where we carefully watch our coworkers for signs of sexism so we can report them to the authorities is exactly the sort of thing you get reported to the authorities if people see you saying.

On the Twitter debate on this, someone mentioned that people felt afraid to share their thoughts anymore. An official, blue-checkmarked Woman In Tech activist responded with (note the 500+ likes):

This is the world we’ve built. Where making people live in fear is a feature, not a bug.

And: it can get worse. If you only read one link, let it be this one about the young adult publishing industry A sample quote:

One author and former diversity advocate described why she no longer takes part: “I have never seen social interaction this fucked up,” she wrote in an email. “And I’ve been in prison.”

Many members of YA Book Twitter have become culture cops, monitoring their peers across multiple platforms for violations. The result is a jumble of dogpiling and dragging, subtweeting and screenshotting, vote-brigading and flagging wars, with accusations of white supremacy on one side and charges of thought-policing moral authoritarianism on the other. Representatives of both factions say they’ve received threats or had to shut down their accounts owing to harassment, and all expressed fear of being targeted by influential community members — even when they were ostensibly on the same side. “If anyone found out I was talking to you,” Mimi told me, “I would be blackballed.”

Dramatic as that sounds, it’s worth noting that my attempts to report this piece were met with intense pushback. Sinyard politely declined my request for an interview in what seemed like a routine exchange, but then announced on Twitter that our interaction had “scared” her, leading to backlash from community members who insisted that the as-yet-unwritten story would endanger her life. Rumors quickly spread that I had threatened or harassed Sinyard; several influential authors instructed their followers not to speak to me; and one librarian and member of the Newbery Award committee tweeted at Vulture nearly a dozen times accusing them of enabling “a washed-up YA author” engaged in “a personalized crusade” against the entire publishing community (disclosure: while freelance culture writing makes up the bulk of my work, I published a pair of young adult novels in 2012 and 2014.) With one exception, all my sources insisted on anonymity, citing fear of professional damage and abuse.

None of this comes as a surprise to the folks concerned by the current state of the discourse, who describe being harassed for dissenting from or even questioning the community’s dynamics. One prominent children’s-book agent told me, “None of us are willing to comment publicly for fear of being targeted and labeled racist or bigoted. But if children’s-book publishing is no longer allowed to feature an unlikable character, who grows as a person over the course of the story, then we’re going to have a pretty boring business.”

Another agent, via email, said that while being tarred as problematic may not kill an author’s career — “It’s likely made the rounds as gossip, but I don’t know it’s impacting acquisitions or agents offering representation” — the potential for reputational damage is real: “No one wants to be called a racist, or sexist, or homophobic. That stink doesn’t wash off.”

Authors seem acutely aware of that fact, and are tailoring their online presence — and in some cases, their writing itself — accordingly. One New York Times best-selling author told me, “I’m afraid. I’m afraid for my career. I’m afraid for offending people that I have no intention of offending. I just feel unsafe, to say much on Twitter. So I don’t.” She also scrapped a work in progress that featured a POC character, citing a sense shared by many publishing insiders that to write outside one’s own identity as a white author simply isn’t worth the inevitable backlash. “I was told, do not write that,” she said. “I was told, ‘Spare yourself.’

Another author recalled being instructed by her publisher to stay silent when her work was targeted, an experience that she says resulted in professional ostracization. “I never once responded or tried to defend my book,” she wrote in a Twitter DM. Her publisher “did feel I was being abused, but felt we couldn’t do anything about it.”

Parts of tech are already this bad. For the rest of you: it’s what you have to look forward to.

It doesn’t have to be this way. Nobody has any real policy disagreements. Everyone can just agree that men and women are equal, that they both have the same rights, that nobody should face harassment or discrimination. We can relax the Permanent State Of Emergency around too few women in tech, and admit that women have the right to go into whatever field they want, and that if they want to go off and be 80% of veterinarians and 74% of forensic scientists, those careers seem good too. We can appreciate the contributions of existing women in tech, make sure the door is open for any new ones who want to join, and start treating each other as human beings again. Your co-worker could just be your co-worker, not a potential Nazi to be assaulted or a potential Stalinist who’s going to rat on you. Your project manager could just be your project manager, not the person tasked with monitoring you for signs of evil to be rooted out. Your female co-worker could just be your female co-worker, not a Strong Grrl Coder Who Has Overcome Adversity And Is A Symbol Of Everything Good In The World. Your male co-worker could just be your male co-worker, not a Tool Of The Patriarchy Who Is Keeping Everyone More Talented Down. I promise there are industries like this. Medicine is like this! Loads of things are like this! This could be you.

Adam Grant seems like a good person. He is superficially doing everything right. He’s not demanding people feel afraid, or saying that everyone who disagrees with him is a fascist. He’s just trying to argue the science.

But I think he’s very wrong about the science. I think Hyde’s article is a gimmick which buries very real differences under a heap of meaningless similarities. I think that it’s inappropriate to cite it to respond to claims of specific differences that it didn’t investigate. I think that claims of a gender-equitable-society-effect in a different domain are inappropriate given the clear opposite effect in the domain being talked about it. I think it’s wrong to privilege likely-selection-biased evidence from a single college over all the evidence from the country as a whole. I think it’s wrong to suppose unique stereotypes in tech and engineering domains with no theory of how they got there, when there are non-stereotype-based theories that better explain the evidence. And I think it’s wrong to ignore all the studies about congenital adrenal hyperplasia.

And I think that, in being wrong about the science, he’s (probably unintentionally) giving aid and comfort to the people who have admitted that turning tech into a climate of constant fear and violence is the end goal.

Grant is one of the few people doing the virtuous thing and trying to debate this without calling for other people’s deaths. I’m trying to do the virtuous thing and respond to him. But I worry that lots of people on Grant’s side aren’t as virtuous as he is, and I don’t know how to protect anybody from that except by begging people to please look at the science and try to get it right.

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8 days ago
"This is the world we’ve built. Where making people live in fear is a feature, not a bug."
Princeton, NJ or NYC
4 days ago
I keep referring to it as a vaccination issue. It's like the vaccines against certain forms of fascism only last maybe a century or half-century and apparently we're due for another dose somehow. Fascists *should* be scared to promote fascism publicly and the bug is right now enough of that vaccines from the last go around have worn off that fascists think they have free reign right now.
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3 public comments
7 days ago
OK, the "manifesto" had a valid point about statistical gender differences being possible. I am still not convinced this is biological vs socialized; I am still not impressed with the far more prominent arguments based on misogyny and racism; and I think hand-waving away those problems to focus on the one point that could have been reasonable -- had the other nine pages not been written -- is just a liiiiiitttle disingenuous.
8 days ago
Whenever I read SSC, I feel like I see another example of the smart person paradox. If you are smart and articulate, you can come up with a plausible justification for anything and argue other people to a standstill. But this means that other people no longer function as a check on your own cognition. So you start drifting off from reality in whatever direction your pre-existing biases take you.

It is perfectly reasonable to worry about how our society is increasingly uses norms for enforcement of purity. And it is perfectly reasonable to find a particular academic study unconvincing. But the pattern here is that over and over SSC censures purity-enforcement from some quarters and ignores it from other quarters.

The difference is that while SSC is ostensibly complaining about purity enforcement, that is not his actual concern. If he was, then it wouldn't matter whether he believed Grant was right on the science or wrong. When you only care about purity enforcement against 'your side', then complaints about purity enforcement simply become a way to game the refs in order to win ideological victories.

And I think this is why so many of his recent arguments about purity fall apart. There is a big difference between 'what I believe' and 'the truth'. Always. It is the difference between the map and the terrain. Between the model and the universe. The truth is out there, but beliefs are inside of us.

So if we are going to define the limits of acceptable discourse, we cannot say 'Joe should not be shunned because what he says is true.' You need to be able to say 'Joe should not be shunned even though what he says is false.' You need to be able to defend Joe even when you are not on his team.

The ref needs to care about the rules of the game more than about who wins. And if SSC wants to make effective arguments against purity-enforcement then he needs to care more about that than about his other ideological commitments.
8 days ago
men vs women in CS - the diff in numbers is natural to hormonal balance
i remember reading about trans who described cognitive changes coming with hormonal treatment

Was there a Housing Price Bubble? Revisited

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In 2005, I thought housing prices were rising above the fundamentals and I said so. In 2008, as the fall in housing prices was well under way, I wrote a blog post and later a NYTimes op-ed saying that the housing price bubble was not nearly as big as people thought. I wrote:

I think that housing prices went beyond the fundamentals sometime around 2004…but 2004 levels are still well above long run trend.

…Prices will probably drop some more but personally I don’t expect to ever again see index values around 110.  Do you?  If we don’t see the massive drop back to “normal” levels then the run up in prices should be described as a shift to a new equilibrium…[with some overshooting, rather than as a bubble.]

To put it mildly, not everyone agreed with my argument. I certainly got the timing wrong–I didn’t think the recession would be as long or as deep as it was. Nevertheless, some people are coming round to my point of view. Karl Smith, for example, has a new post Was There Ever a Bubble in Housing Prices? which concludes more or less, as I did nearly ten years earlier, that the answer is no. What happened was greater liquidity which made housing prices gyrate more like stock prices but “the fundamental driver isn’t irrational bubble behavior. It is competition over a scarce resource.”

Let’s go back to the Shiller graph, now updated to 2017. Over the entire 20th century real home prices averaged an index value of about 110 (and were quite close to this value over the the entire 1950-1997 period). Over the entire 20th century, housing prices never once roce above 131, the 1989 peak. But beginning around 2000 house prices seemed to reach for an entirely new equilibrium. In fact, even given the financial crisis, prices since 2000 fell below the 20th century peak for only a few months in late 2011. Real prices today are now back to 2004 levels and rising. As I predicted in 2008, prices never returned to their long-run 20th century levels.

Now one might argue that there is still a bubble or perhaps another bubble in housing prices. But the United States does not look anomalous compared to other countries. In fact, in many other countries prices have risen more than in the United States. Here is the Economist’s Global Price Index of real house prices for a variety of countries. (Do note that some countries not shown, such as Germany, haven’t seen big increases in prices.) Are all these countries experiencing bubbles? Or has the equilibrium changed?

Understanding why the equilibrium has changed is a fundamental issue that I don’t think we yet have a good handle on. My view, is that it’s a combination of expected long-run lower interest rates, greater liquidity, and supply constraints on land. Lower interest rates, for example, mean that durable assets increase sharply in price, all the more so if the rates are expected to stay low. Combine this with greater liquidity (see Smith’s post) and supply restrictions and you can explain most of what is going on in the United States. What I don’t know is if the same explanations work worldwide and can the same factors also be used to explain why land prices haven’t risen in Germany, Japan or Switzerland?

Hat tip: Nathaniel Bechhofer.

The post Was there a Housing Price Bubble? Revisited appeared first on Marginal REVOLUTION.

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12 days ago
This article definitely needs a fundamental underpinning. rent or price to income, for instance.
Princeton, NJ or NYC
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Tories vs the 21st century

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It’s become a cliché that the Tories want to return to the 1950s, before the age of mass migration and our entanglement with the EU. These, however, are not the only examples of Tories discomfort with the modern world. Tom Welsh says the Tory party is threatened by the large number of university graduates, and Amber Rudd seems befuddled by the internet.

This poses the question: why are the Tories so unhappy with the 21st century?

It hasn’t always been so. Cameron and Osborne, despite being lamentably incompetent, at least seemed comfortable in today’s world – and not just financially. And whilst Thatcher spoke of Victorian values, her project was also one of modernizing the economy, at least by her own lights. Toryism has not always been a nostalgic yearning for the past.

In fact, to we relics of the 1980s, there’s something especially paradoxical about the ascendancy of reaction among Tories. I remember Cold Warriors celebrating Karl Popper’s vision of an open society: Thatcher called The Open Society and its Enemies a “marvellous book.” In some respects, though, we now have such an open society: migration; gender fluidity; less deference; and peer-to-peer communication which bypasses traditional hierarchies. And many Tories hate it.

Why? Here are two theories.

First, the 21st century hasn’t delivered what the Tories hoped. They had hoped that the defeat of trades unions, privatization, cuts to top taxes, deregulation and fiscal austerity would unleash a dynamic, productive economy. It hasn’t.

This means we need to rethink the relationship between markets, hierarchies and the state – which means, of course, rethinking not just social democracy but Toryism too. May’s talk of the need for an industrial strategy was a dim recognition of this. But the Tories (perhaps temporarily, perhaps not) lack the intellectual resources for this task. Thatcher could invoke Friedman, Hayek, Popper and the architects of public choice theory. Who has May got?

I suspect one reason for the popularity of Brexit on the right is that, having vanquished unions and red tape, the EU is pretty much the only scapegoat they have left for the UK’s disappointing economic performance.

Secondly, and perhaps relatedly, the Tory base is breaking up.

One aspect of this is that the always uneasy coalition between business and social conservatives looks less tenable today than ever: the Brexit supported by old reactionaries is against the interest of finance and much of business. Today's Tories thus have a more precarious client base.

A second aspect is that the decline of property ownership and degradation of erstwhile good jobs has eroded one source of support for the Tories. In the 80s, young urban professionals (yuppies) were Thatcherites. Their equivalents today are Corbynistas.

I know I might well be guilty of wishful thinking in saying this. But it could be that the Tories are so unhappy with the 21st century simply because it offers them nothing but the refutation of their beliefs and decline in their power.  

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14 days ago
funny, its the 'progressives' who seem uncomfortable with the 21st century over here. Maybe if you split it into cultural vs. economic you get more useful distinctions.
Princeton, NJ or NYC
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