The full text of the Trump administration’s new travel ban executive order via the Washington Post.
On March 7, 1965, a march by civil rights demonstrators was broken up in Selma, Ala., by state troopers and a sheriff’s posse.
From Diane Ravitch’s blog:
While we’re consumed 24/7 with the Trump/Russia psychodrama, Republicans are quietly, under the cover of darkness and diversion, introducing these new bills in the House:
HR 610 Vouchers for Public Education — (The bill also repeals basic nutrition standards for the national school lunch and breakfast programs)
HR 899 Terminate the Department of Education
HR 785 National Right to Work (aimed at ending unions, including teacher unions)
And there’s more. Much more, including:
–HR 861 Terminate the Environmental Protection Agency
–HJR 69 Repeal Rule Protecting Wildlife
–HR 370 Repeal Affordable Care Act
–HR 354 Defund Planned Parenthood
–HR 83 Mobilizing Against Sanctuary Cities Bill
–HR 147 Criminalizing Abortion (“Prenatal Nondiscrimination Act”)
–HR 808 Sanctions against Iran
Some years ago I read this NBER working paper. (Note – a couple years later a slightly modified version appeared in the American Economic Journal but I will quote from the earlier, non-paywalled version since it is available to everyone.)
Here’s the issue, in a nutshell:
In this paper, we use administrative data from the Houston Independent School District and the Louisiana Department of Education to examine whether the influx of Katrina and Rita students adversely affected the academic performance, attendance and discipline of their new peers.
Later in the paper:
…the arrival of low achieving peers hurts all native students, but this effect is more negative for low achieving natives in elementary and high achieving natives in secondary schools. By contrast, the arrival of high achieving evacuees benefits everyone, though the biggest benefit is for the low achieving natives.
If you missed that, later on the same page they write:
…we find that high achieving evacuees increase native performance and low achieving evacuees reduce native performance.
But it isn’t just performance…
By contrast, the results for discipline and attendance do show that it is enough to have 1 or 2 misbehaving evacuee children to worsen the attendance and behavior of native kids in elementary schools. In middle- and high-schools, only having many undisciplined kids in a classroom worsens native behavior.
And it isn’t just because more kids = less resources:
These results show no statistically significant effect of the fraction of evacuees on class-size in elementary schools. In middle and high-schools there is little evidence that the influx of evacuees significantly increased class-size, except for class-sizes in social studies which shows a marginally significant effect…. The results once again show no statistically significant effect of the influx of evacuees on either operating or instructional expenditures per student. This is likely because the Federal and State Governments seemed to have reimbursed schools and districts almost fully. Also, interviews with principals in Houston, suggested that schools received substantial aid from a number of foundations around the country.
Jumping to the conclusion, just to repeat the findings in case someone is tempted to misread them:
Non-linear models show that high achieving natives are significantly positively affected by high achieving evacuees and significantly negatively impacted by low achieving evacuees. Low achieving natives also generally benefit from high achieving evacuees and are hurt by low achieving evacuees in terms of their own test scores…
Of course, any parent who isn’t blind knows that a big determinant of the quality of his/her kids’ education is the quality of his/her kids’ peers. Still, its a well constructed and well executed paper. I also happen to think this situation makes a fine allegory for immigration.
Here is the abstract from a paper that appeared two years ago in Molecular Psychiatry:
Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics’. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the ‘missing heritability’ gap.
I’ve been doing some reading in the field, and there’s nothing particularly special about this paper. I picked it because the abstract provided a fair summary of where the literature has been for at least a generation now. In fact, I specifically avoided a couple of papers that would have seemed hair-raisingly controversial to people who haven’t looked at the literature.
My point is simple. Cognitive science and genetics are at a place that is very, very different than most people think. And the science is getting better, faster and more precise. I believe it is, in fact, fair to say that we are in the early stages of a revolution in the biological sciences, particularly where it concerns the study of intelligence and other mental traits.
So what is going on? Why does the science seem so alien in 2017 America? To quote no less an authority than Steven Pinker:
Irony: Replicability crisis in psych DOESN’T apply to IQ: huge n’s, replicable results. But people hate the message.
As a complete outside, I wouldn’t dare argue the science with Pinker. Still, his statement is partly wrong. Sure, most people hate the message. But some people love it. The people who love the message love it because they can use it to justify the hatred in their heart. The rest of us hate it because we understand what it implies. If intelligence and other personality traits are largely heritable, people aren’t a blank slate. It casts doubt on many of our cherished myths. More disturbingly, it almost implies people have some sort of destiny, one that wouldn’t be out of place in a Gattaca world, or worse, a Brave New one.
Of course, if something along those lines were the case, it would be useful for the majority of the body politic – say, the center left, the center, and the center right - to develop ideas and policies for how to deal with it in a way that fits our values. Instead, a monopoly on that sort of discussion has been granted to the haters… and you can well imagine the policies they have in mind. For everyone else, such topics are now mostly taboo. They can be discussed in a lab setting, in technical terms, but woe betide anyone, including a biologist who translates them into the vernacular.
But what if it turns out that the actors, attorneys, community activists, educators, HR professionals, journalists and liberal arts professors are wrong? What if the world’s most pre-eminent cognitive researchers, geneticists and neurobiologists know the science better than they do? What if traits like intelligence and behavior are transmitted very much as described in the scientific literature? I know. It sounds nuts. But what if? What would we do then? In such a world, what policies should we set? And how do we ensure that those are the policies that actually do get enacted?
Update. Corrected link to abstract.
by New Deal democrat
The Atlanta Fed’s Macroblog has an interesting article today on whether a “high pressure” low unemployment economy leads to more capital investment. At least based on surveys, they answer in the negative, with companies pulling out the old chestnut of being unable to find qualified help “(at the wage we want to pay”).
But the article reports on one survey only, and does not delve into any long term historical data. So of cuorse I did.
Here’s what I found. Annual data on real private fixed nonresidential data, and U-3 unemployment, can both be found back to 1948.
The first graph compares the YoY% change in investment vs. the YoY% change in the unemployment rate:
There is a high correlation, but there is no apparent leading relationship. In fact they look coincident. At best it appears that investment continues to expand even as the unemployment rate holds steady in mature expansions.
by New Deal democrat
One of my recurring themes is how macroeconomic theory, no matter how elegant mathematically, consistently errs because it fails to take into account basic psychology — i.e., how the human animal actually works.
A big component of this failure is that humans, like other primates and apparently like just about every other social species, are hard-wired to inflict punishment on “winners” from inequitable distributions, even at cost to themselves. For a hilarious example of this, see what happens when an experimenter rewards one monkey with a cucumber while feeding another a delicious grape.
One such failure to take into account elementary psychology was on display in an article a few days ago, wherein Larry Summers, in the course of lambasting the rubes for trying to undermine global trade, concluded:
A strategy of returning to the protectionism of the past and seeking to thwart the growth of other nations is untenable and would likely lead to a downward spiral in the global economy. The right approach is to maintain openness while finding ways to help workers at home who are displaced by technical progress, trade or other challenges.
Dean Baker’s screed, Bill Gates Is Clueless On The Economy, keeps getting recycled, from Beat the Press to Truthout to Real-World Economics Review to The Huffington Post. Dean waves aside the real problem with Gates’s suggestion, which is the difficulty of defining what a robot is, and focuses instead on what seems to him to be the knock-down argument:
Gates is worried that productivity growth is moving along too rapidly and that it will lead to large scale unemployment.
There are two problems with this story: First productivity growth has actually been very slow in recent years. The second problem is that if it were faster, there is no reason it should lead to mass unemployment.
There are two HUGE problem with Dean’s story. First, aggregate productivity growth is a “statistical flimflam,” according to Harry Magdoff, who pioneered productivity measurement in the 1930s. In the 1980s, Magdoff co-authored a Monthly Review article with Paul Sweezy, “The Uses and Abuses of Measuring Productivity,” detailing the methodological problems of aggregate productivity measurement. After discussing “phantom statistics” in the reporting of construction industry productivity, and the technical problems of aggregating productivity statistics, Magdoff and Sweezy explained why “there is no such thing… as a ‘true’ measure of productivity”:
One reason for including this somewhat technical discussion is to drive home the point that there is no such thing as straightforward or “true” measure of productivity. And if this is so even in the realm of commodities where a reasonable, limited, meaning can be given to the concept, what can said about the productivity of service workers? There are of course service jobs that consist of routine, repetitive operations — e.g., in typing pools — where productivity measures may have some meaning. But how would one go about measuring the productivity of a fireman, an undertaker, a teacher, a nurse, a cashier in a supermarket, a short-order cook, a waiter, a receptionist in a lawyer’s office? It is in the very nature of the case that in most services qualitative changes are intertwined with quantitative changes; hence there is no continuity in the “output” from one period to another with which changes in employment can be compared. Moreover, it is typical of many of the service areas that the “output” cannot be separated from the labor engaged in the performance of the service; for that reason too there is no sensible way of comparing changes in output and labor. In other words, the notion of a productivity measure for most service occupations is nonsensical and self-contradictory.
Unfortunately, such considerations of elementary logic have not prevented statisticians and economists from producing a whole array of productivity measures, applicable not only to the private economy (combining commodity-production and services) but in some cases to government as well, useful for ideological and policy-making purposes. And by dint of endless repetition and selective emphasis, these statistical phantoms (to use Business Week’s apt expression) have attained the status of indisputable facts and have entered into the realm of scientific discourse. What is in reality nothing but a crude fetish has thus become one of the most potent weapons in capital’s struggle against labor and in support of an increasingly irrational and destructive social system.
In short, there is no reason that productivity growth should ever be viewed as the enemy of workers. We just need the right set of policies to ensure that they share in the gains.
Leaving aside the benefits and risks of technological advances themselves, Block and Burns chronicled how the concept of productivity growth — and its faux measurement — has been used as a political weapon against workers, unions and collective bargaining. The use of productivity data had initially gained prestige for its role in providing a “rational and objective” basis for wage negotiations, but in the late 1970s, business and political leaders,
…seized on declining rates of productivity growth as proof of the need for national policies to restrain wages and limit the growth of state spending. The decline of productivity growth was attributed to inadequate levels of investment and it was argued that only measures that increased the flow of resources to business and the rich could possibly facilitate adequate levels of new investment. It was simultaneously argued that excessive government regulation was also responsible for the slowing of productivity growth leading to stronger demands for deregulation of the business community. The culmination of these efforts was the Reagan Administration’s dramatic reversals of long standing tax and regulatory policies which were justified as providing solutions to the productivity crisis.
While the productivity concept had initially been elaborated by the WPA’s National Research Project to provide justification for more generous wage settlements and government public works programs, by the late 1970s, it provided a critical justification for getting tough with labor and for dismantling key parts of the American welfare state. The process of institutionalization had resulted in a reversal of the political implications of this particular indicator.