J. Bradford DeLong's Blog, page 382

On Twitter: Author: Don't mind me: The real me is just lo...

On Twitter: Author: Don't mind me: The real me is just locked in a room receiving incomprehensible messages and then sending out replies constructed via a rule book that I do not understand. There is no real intelligence at home in here...

@dsquaredigest: The first of those two.

@NewYorker: Where does the mind end and the world begin? Is the mind locked inside its skull, sealed in with skin, or does it expand outward, merging with things and places and other minds that it thinks with? http://nyer.cm/IKb7eMF

The "Let's Be Agnostic About Race Science" Clowns Are in My Twitter Timeline Again...

Over on Twitter: 1500 generations since radiation from the Horn of Africa is not very many, n'est-ce pas? A genetic difference that gives you a���huge���extra 0.1% chance of surviving to reproduce will take a gene's frequency from 1% to 5% of the population in that time.

Melanin and vitamin D, lactose tolerance and herding, sickle cell and malaria���all things with an order-of-magnitude bigger than 0.1% differential? Certainly yes. Other things like "general intelligence"? Almost certainly no. I don't see how you can do the math and still claim otherwise.

And so I don't see how those who claim otherwise���or even claim "agnosticism" about whether it is likely that there are "important" differences between "races"���have done the arithmetic.

Can't do the arithmetic?

Haven't done the arithmetic?

Reject the arithmetic because they want to justify some form of racial privilege?

I don't really care.

As @ezraklein just wrote: "[such] race science... is not 'forbidden knowledge'... [but rather] America���s most ancient justification for bigotry and racial inequality..." As Charles Manski wrote back in 2011: "Decompos[ing] cross-sectional variation in observed outcomes into unobservable genetic and environmental components", no. "Measur[ing] specific genes and us[ing] them as observed covariates when predicting outcomes", quite possibly.

Should-Read: It is time for Sherry Turtle to 'fess up t...

Should-Read: It is time for Sherry Turtle to 'fess up that she was wrong about the sociological impact of high-tech. The very change in its name should have clued her in: from "computer technology" to "information technology" to "information and computer technology���ICT". It is not isolating each of us in their own virtual world in which they do not encounter humans. It is, rather, making us hyper-social���with big costs as we have (so far) failed to develop effective enough ways to manage hypersociality, but also very big benefits: Kevin Drum: In Defense of Smartphones: "Sherry Turkle is an MIT professor who thinks social media is decimating face-to-face contact...

...Claude Fischer is a Berkeley professor who thinks social media has done nothing of the sort.... And again in 2015, responding to an essay by Turkle in the New York Times which suggested that conversation is dying as people escape into their smartphones:

There may well be something to this assertion. But we want some systematic, reliable evidence that Americans converse less in person than before, attend to one another less, and suffer more as a consequence. It is hard to find such evidence. Much of the ���data��� in Turkle���s essay (and I presume the new book) is anecdotal: As in Alone Together, the documentation is mainly people here and there, especially unhappy people, with whom she talks. These reports may all be totally truthful and still the thesis be wrong. Fifty years ago, Turkle might have well have heard similar grousing about people eating together silently, or burying their noses in the newspaper, or, heaven knows, turning away to watch the always-on TV set. In addition, Turkle cherry picks studies...

I don���t think there���s any doubt that social networks and ubiquitous smartphones are changing the way we relate with each other.... So far... Fischer has the better of the argument...

Should-Read: Good conservative ideas become liberal ideas...

Should-Read: Good conservative ideas become liberal ideas. The only conservative ideals left are those that are not good. Some of them are not good, but because they are plutocratic the plutocrats like them, and they often pass. Some of them are not good, but because they are fascist the fascists like them, and they often pass. The others? Conservatives run from them: consider the conservative flight from RomneyCare. Why do conservatives run from them? Because once they become attractive to liberals they no longer serve as identity markers, and identity markers are primary: Mike Konczal: Why Are There No Good Conservative Critiques of Trump���s Unified Government?: "We aren���t just seeing the chaos of... Trump...

...We are also seeing that the Republicans ultimately don���t have the ability to pass the agenda that they spent the past eight years, and really the past several decades, arguing for. This is a different implosion.... If they can���t ultimately move their ideas to the point where their own intellectuals can find interesting things to say about their failures, that means we should understand their whole project to be far weaker than they admit.... An agenda has clearly passed���tax cuts for the rich, stuffing the judiciary and administration with deregulators, and actions against civil rights and towards more punitive immigration enforcement.... The actors who matter are the business interests and the base.... The mediating conservative infrastructure simply doesn���t matter much, either as actors or chroniclers. For all the talk about brilliant policy minds on the Right who want to reform the state, the real brilliance and energy in their agenda is in not investigating Equifax, giving corporations tax cuts for fissuring their workforce, unleashing ICE and dismantling the Civil Rights Division of the Department of Justice.

At best, the Right���s policy voices are all ideas and no consequences. More likely, they form a kind of entertainment industry that only is consequential to the extent it channels business interests or mass resentment. My understanding is that some of the analysis of what has gone wrong is being done in quiet rooms, led by the money people and the lobbyists. But if all the real analysis is done in private, and its goals are only to boost a balance sheet or channel talk radio, why should we read conservatives?...

Explication, Language, and Mathematics in Economics: Thinking Like an Economist

A great deal of stuff relevant to teaching, reading, and doing economics. Also highly relevant to: Brad DeLong: Optional Teaching Topic: How to Think Like an Economist... (Provided, That Is, You Wish to...) (Pre-Class? Mid-Class?):

Tim Taylor: Some Thoughts About Economic Exposition in Math and Words: "[Paul Romer's] notion that math is 'both more precise and more opaque' than words is an insight worth keeping...

...It reminded me of an earlier set of rules from the great economist Alfred Marshall, who... wrote in 1906 letter to Alfred Bowley (reprinted in A.C. Pigou (ed.), Memorials of Alfred Marshall,��1925 edition, quotation on p. 427):��

But I know I had a growing feeling in the later years of my work at the subject that a good mathematical theorem dealing with economic hypotheses was very unlikely to be good economics; and I went more and more��on the rules:

Use mathematics as a shorthand language; rather than as an engine of inquiry.

Keep to them till you have done.

Translate into English.

Then illustrate by examples that are important in real life.

Burn the mathematics.

If you can't succeed in 4, burn 3.

This last I did often.... Mathematics used in a Fellowship thesis by a man who is not a mathematician by nature���and I have come across a good deal of that���seems to me an unmixed evil. And I think you should do all you can to prevent people from using Mathematics in cases in which the English language is as short as the Mathematical...

Paul Romer adds some rules of his own...

The test is whether math adds to or detracts from clarity and precision. A writer can use either the words of everyday language or the symbols from math to make assertions that are clear and precise; or opaque and vague.
The deep problem is intent, not ability or skill.
Writers who want to make predictions use words and math to be clear and precise. Writers who want to make excuses use words and math to be opaque and vague.
Compared to words, math and code tend to be both more precise and more opaque...

I might quibble a bit with his rule #2, because my sense is that many of those who fail to communicate clearly, whether in math or in words, either have simply not put the time and effort into doing so, or lack the ability/skill to do so...

Dani Rodrik... includes the following...

Make your model simple enough to isolate specific causes and how they wor...
But not so simple that it leaves out key interactions among causes...
Unrealistic assumptions are OK...
Unrealistic critical assumptions are not OK...
Do not criticize an economist���s model because of its assumptions...
Ask how the results would change if certain problematic assumptions were more realistic...
Analysis requires simplicity...
Beware of incoherence that passes itself off as complexity...
Do not let math scare you...
Economists use math not because they are smart, but because they are not smart enough.

And, of course, John Maynard Keynes: John Maynard Keynes (1924): What Is the Excellence of an Economist?: "The study of economics does not seem to require...

...any specialised gifts of an unusually high order. Is it not, intellectually regarded, a very easy subject compared with the higher branches of philosophy and pure science? Yet good, or even competent, economists are the rarest of birds. An easy subject, at which very few excel! The paradox finds its explanation, perhaps, in that the master-economist must possess a rare combination of gifts. He must reach a high standard in several different directions and must combine talents not often found together. He must be mathematician, historian, statesman, philosopher���in some degree. He must understand symbols and speak in words. He must contemplate the particular in terms of the general, and touch abstract and concrete in the same flight of thought. He must study the present in the light of the past for the purposes of the future. No part of man's nature or his institutions must lie entirely outside his regard. He must be purposeful and disinterested in a simultaneous mood; as aloof and incorruptible as an artist, yet sometimes as near the earth as a politician...

Tim Taylor (2018): Some Thoughts About Economic Exposition in Math and Words
Dani Rodrik (2017): The Economics Debate, again and again

Larry Elliott (2017): Heretics welcome! Economics needs a new Reformation: "Neoclassical economics has become an unquestioned belief system and treats those challenging the creed as dangerous..."

Brad DeLong (2016): What Is the Excellence of an Economist?
Brad DeLong (2015): Richard Thaler Misbehaves���or, Rather, Behaves
Paul Romer (2015): Mathiness in the Theory of Economic Growth
John Maynard Keynes (1924): What Is the Excellence of an Economist?
Alfred Marshall (1906): Letter to Alfred Bowley





Brad DeLong: Optional Teaching Topic: How to Think Like an Economist... (Provided, That Is, You Wish to...) (Pre-Class? Mid-Class?)

Brad DeLong (2017): How to Think Like an Economist (If, That Is, You Wish to...)
Brad DeLong: How to Think Like an Economist���Lecture:

Expectational Weirdness: 1929: The Great Crash and the Great Depression
A Behavioral Relationship: The Production Function
An Equilibrium Condition: The Balanced-Growth Capital-Output Ratio
Thinking Like an Economist Slides

Brad DeLong (2016): A Few Scattered Notes, Observations, and Examples of Graphs and Diagrams in Teaching and Doing Economics:

Edgeworth Boxes and Production Possibility Frontiers
Paul Krugman (2016): In Defense of Funny Diagrams
J.M. Keynes (1924): Alfred Marshall, 1842-1924
John Maynard Keynes (1938): Letter to Roy Harrod: "Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world..."







Brad DeLong (2015): Noah Smith, Paul Romer, "Mathiness", and Baking the Politics into the Microfoundations...:

Brad DeLong (2015): The Theory of Growth and Inequality: Piketty, Zucman, Krusell, Smith, and "Mathiness": It is Krusell and Smith (2014) that suffers from "mathiness"--people not in control of their models deploying algebra untethered to the real world in a manner that approaches gibberish...
Brad DeLong (2014): Department of "Huh?!"--I Don't Understand More and More of Piketty's Critics: Per Krusell and Tony Smith: As time passes, it seems to me that a larger and larger fraction of Piketty's critics are making arguments that really make no sense at all--that I really do not understand how people can believe them, or why anybody would think that anybody else would believe them. Today we have Per Krusell and Tony Smith assuming that the economy-wide capital depreciation rate �� is not 0.03 or 0.05 but 0.1--and it does make a huge difference...
Noah Smith (2015): Noahpinion: Paul Romer on mathiness
Brad DeLong (2015): Oddities in the Rhetoric of Economics: Paul Romer Confronts the "Adversarial Method" in the Presentation of Economic Theory
Paul Romer (2016): The Trouble with Macroeconomics

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Live from the Orange-Haired Baboon Cage: Wikipedia: Unite...

Live from the Orange-Haired Baboon Cage: Wikipedia: United States House of Representatives Elections, 2016:

Majority party: Paul Ryan: 49.9%

Minority party: Nancy Pelosi: 47.3%

Live from the Orange-Haired Baboon Cage: Atlantic editor ...

Live from the Orange-Haired Baboon Cage: Atlantic editor Jeffrey Goldberg was well past his sell-by date and rotten to the core the day he started: Scott Lemieux: It's Just A Question Of What Your Red Lines Are: "Elite opinion editors talk a good game about 'diversity'...

...but in fact their opinion pages are generally not very diverse.... As Yglesias says, ���the opinion elite ideal is to have an ideologically diverse group of people all of whom voted for either Clinton or Rubio in the primaries then Clinton in the general, but regard her as a profoundly flawed politician and one of the worst nominees of all time.��� I would add that the ideal hire should also be convinced that since she would have no problem being paid six figures to write 1,600 words a week until she���s 70, people who tar roofs in Phoenix for a living also shouldn���t get Social Security until they���re 70.

There are clearly red lines; it���s a question of what they are. Goldberg thinks that supporting Trump is essentially disqualifying, but not advocating that a quarter of the women in America be executed, or flagrant racism. OK. (Do I think that Goldberg would hire someone who was as much an anti-Israel extremist as Williamson is an anti-abortion extremist? I do not)...

Should-Read: I think I have an answer to Charles Manski's...

Should-Read: I think I have an answer to Charles Manski's question "why does heritability research persist?" It persists because it is well-funded. It is well-funded because it makes some people feel better. It makes some people feel better because it can be read to reinforce white supremacy: Charles F. Manski (2011): Genes, Eyeglasses, and Social Policy: "Suppose that nearsightedness derives entirely from the presence of a particular allele of a specific gene...

...Suppose that this gene is observable, taking the value g = 0 if a person has the allele for nearsightedness and g = 1 if he has the one that yields normal sight. Let the outcome of interest be effective quality of sight, where ���effective��� means sight when augmented by eyeglasses, should they be available. A person has effective normal sight either if he has the allele for normal sight or if eyeglasses are available. A person is effectively nearsighted if that person has the allele for nearsightedness and eyeglasses are unavailable. Now suppose that the entire population lacks eyeglasses. Then the heritability of effective quality of sight is one. What does this imply about the usefulness of distributing eyeglasses as a treatment for nearsightedness?

Nothing, of course.

The policy question of interest concerns effective quality of sight in a conjectured environment where eyeglasses are available. However, the available data only reveal what happens when eyeglasses are unavailable.

Why Does Heritability Research Persist?... Given that it was widely recognized more than 30 years ago that heritability research is irrelevant to policy, I find it both remarkable and disheartening that some have continued to assert its relevance subsequently. For example, Herrnstein and Murray did so in The Bell Curve, referring to (p. 109) ���the limits that heritability puts on the ability to manipulate intelligence.��� Research on the heritability of all sorts of outcomes continues to appear regularly today. Recent studies such as the one by Cesarini et al. cited earlier tend not to explicitly refer to policy, but neither do they provide any other articulate interpretation of the heritability statistics they report. The work goes on, but I do not know why...

Should-Read: I am not sure I see the problem here: diagno...

Should-Read: I am not sure I see the problem here: diagnoses are assignments of patients to human-specified categories. You cannot take the human doctors out of the loop here���they are the people who retrospectively assess whether the diagnosis is correct. The potential problems seem to me to still be far down the road���at the point where the ML algorithm starts saying "people with this diagnosis have done better under that treatment regimen" without any ability to explain why: A. Michael Froomkin, Ian R. Kerr, Joelle Pineau: When AIs Outperform Doctors: The Dangers of a Tort-Induced Over-Reliance on Machine Learning and What (Not) to Do About it: "Someday, perhaps soon, diagnostics generated by machine learning (ML) will have demonstrably better success rates than those generated by human doctors...

...What will the dominance of ML diagnostics mean for medical malpractice law, for the future of medical service provision, for the demand for certain kinds of doctors, and���in the longer run���for the quality of medical diagnostics itself?... Effective machine learning could create overwhelming legal and ethical pressure to delegate the diagnostic process to the machine. Ultimately, a similar dynamic might extend to treatment also.... This may result in future decision scenarios that are not easily audited or understood by human doctors....

The article describes salient technical aspects of this scenario particularly as it relates to diagnosis and canvasses various possible technical and legal solutions that would allow us to avoid these unintended consequences of medical malpractice law. Ultimately, we suggest there is a strong case for altering existing medical liability rules in order to avoid a machine-only diagnostic regime. We argue that the appropriate revision to the standard of care requires the maintenance of meaningful participation by physicians in the loop...

Should-Read: If it has not been employment-displacing, ho...

Should-Read: If it has not been employment-displacing, how can it reduce the share of value added received by labor? There must be something strange going on with the counterfactual. But what?: David Autor and Anna Salomons: Is Automation Labor-Displacing? Productivity Growth, Employment, and the Labor Share: "Is automation a labor-displacing force?...

...This possibility is both an age-old concern and at the heart of a new theoretical literature considering how labor immiseration may result from a wave of ���brilliant machines,��� which is in part motivated by declining labor shares in many developed countries. Comprehensive evidence on this labor-displacing channel is at present limited. Using the recent model of Acemoglu and Restrepo (2018b) as an analytical frame, we first outline the various channels through which automation impacts labor ��s share of output. We then turn to empirically estimating the employment and labor share impacts of productivity growth���an omnibus measure of technological change���using data on 28 industries for 18 OECD countries since 1970. Our main findings are that although automation���whether measured by Total Factor Productivity growth or instrumented by foreign patent flows or robot adoption���has not been employment-displacing, it has reduced labor���s share in value-added. We disentangle the channels through which these impacts occur, including: own-industry effects, cross-industry input-output linkages, and final demand effects accruing through the contribution of each industry���s productivity growth to aggregate incomes. Our estimates indicate that the labor share-displacing effects of productivity growth, which were essentially absent in the 1970s, have become more pronounced over time, and are most substantial in the 2000s. This finding is consistent with automation having become in recent decades less labor-augmenting and more labor-displacing...