Adorno in 60 Minuten

27 Dec, 2021 at 17:21 | Posted in Politics & Society | Leave a comment

.

Lars Jonung och Daniel Waldenström — Sveriges egna Dr Pangloss

24 Dec, 2021 at 14:17 | Posted in Economics | 3 Comments

Sagan om Karl-Bertil Jonssons julaftonNär Karl-Bertil Jonsson i Tage Danielssons klassiska julsaga lägger undan några rika människors julklappar och delar ut dem till fattiga brister han i respekt för den privata äganderätten, skriver Lars Jonung och Daniel Waldenström på DN Debatt idag. Enligt dessa ekonomiprofessorer är det kapitalism och marknadsliberalism som är den ’okände välgöraren’ som gynnat oss alla med “god ekonomisk tillväxt och demokratiska fri- och rättigheter.”

Och detta ankors plask och grodors plums tror dessa herrar att de kan lura i folk. De måste tagit fel på årstiden. Det är inte första april idag. Det är julafton!

Trots att båda herrar vet bättre, nämner de inte med ett ord att Sverige under de senaste fyra decennierna är ett av de länder i världen där ökningstakten i ojämlikhet vad avser rikedom och inkomster varit som störst.

Jag säger som Fabian Månsson: Vet hut! Vet sjufalt hut!

O holy night

24 Dec, 2021 at 08:44 | Posted in Varia | Comments Off on O holy night

.
Jussi Björling — the greatest of them all.

Snön faller och vi med den

23 Dec, 2021 at 13:50 | Posted in Varia | Comments Off on Snön faller och vi med den

.

How scientists manipulate research

23 Dec, 2021 at 11:15 | Posted in Statistics & Econometrics | Comments Off on How scientists manipulate research

All science entails human judgment, and using statistical models doesn’t relieve us of that necessity. Working with misspecified models, the scientific value of significance testing is actually zero — even though you’re making valid statistical inferences! Statistical models and concomitant significance tests are no substitutes for doing real science.

In its standard form, a significance test is not the kind of ‘severe test’ that we are looking for in our search for being able to confirm or disconfirm empirical scientific hypotheses. This is problematic for many reasons, one being that there is a strong tendency to accept the null hypothesis since they can’t be rejected at the standard 5% significance level. In their standard form, significance tests bias against new hypotheses by making it hard to disconfirm the null hypothesis.

And as shown over and over again when it is applied, people have a tendency to read ‘not disconfirmed’ as ‘probably confirmed.’ Standard scientific methodology tells us that when there is only say a 10 % probability that pure sampling error could account for the observed difference between the data and the null hypothesis, it would be more ‘reasonable’ to conclude that we have a case of disconfirmation. Especially if we perform many independent tests of our hypothesis and they all give ​the same 10% result as our reported one, I guess most researchers would count the hypothesis as even more disconfirmed.

Statistics is no substitute for thinking. We should never forget that the underlying parameters we use when performing significance tests are model constructions. Our p-values mean next to nothing if the model is wrong. Statistical​ significance tests do not validate models!

In many social sciences, p-values and null hypothesis significance testing (NHST) is often used to draw far-reaching scientific conclusions — despite the fact that they are as a rule poorly understood and that there exist alternatives that are easier to understand and more informative.

Not the least using confidence intervals (CIs) and effect sizes are to be preferred to the Neyman-Pearson-Fisher mishmash approach that is so often practiced by applied researchers.

Running a Monte Carlo simulation with 100 replications of a fictitious sample having N = 20, confidence intervals of 95%, a normally distributed population with a mean = 10 and a standard deviation of 20, taking two-tailed p-values on a zero null hypothesis, we get varying CIs (since they are based on varying sample standard deviations), but with a minimum of 3.2 and a maximum of 26.1, we still get a clear picture of what would happen in an infinite limit sequence. On the other hand p-values (even though from a purely mathematical-statistical sense more or less equivalent to CIs) vary strongly from sample to sample, and jumping around between a minimum of 0.007 and a maximum of 0.999 doesn’t give you a clue of what will happen in an infinite limit sequence!

Dangerous physics envy in economics

22 Dec, 2021 at 13:40 | Posted in Economics | 5 Comments

Unlike in physics, there are no universal and immutable laws of economics. You can’t will gravity out of existence. But as the recurrence of speculative bubbles shows, you can unleash ‘animal spirits’ so that human behaviour and prices themselves defy economic gravity. Change the social context – in economic parlance, change the incentive structure – and people will alter their behaviour to adapt to the new framework …

Andrew Lo quote: Economists suffer from a deep psychological disorder that  I call...

The apogee of economic ‘scientism’ came in the 1990s … Hindsight has revealed the misplaced hubris of that decade, one during which Greenspan helped to fuel a speculative bubble that nearly destroyed the world economy, and the Soviet Union’s failed reform knocked seven years off its life expectancy. Many economists, Sachs included, defend themselves on the grounds that their advice was not actually taken: bad politics got in the way of good economics.

Given this willful blindness, the current reaction against economists is understandable. In response, a ‘data revolution’ has prompted many economists to do more grunt work with their data, while engaging in public debates about the practicality of their work. Less science, more social. That is a recipe for an economics that might yet redeem the experts.

John Rapley

Sarah Palin — the anti-vax rocket scientist

22 Dec, 2021 at 08:39 | Posted in Politics & Society | 9 Comments

Sarah Palin, rocket scientist, offered her thoughts on the coronavirus vaccine at a far-right conference in Arizona over the weekend. “It will be over my dead body that I’ ll have to get a shot,” she proclaimed.

Sarah Palin Hazed for Not Getting COVID Vaccination: 'I Bet She Is Horse  Dewormed'Unlikely, governor. Phase III trials have shown that the vaccines fail to generate a robust immune response when administered to dead people.

But Palin’s talk of dead bodies is on point. By discouraging vaccination, she and Tucker Carlson and the rest of the anti-science right are quite literally getting people killed. Studies show that those living in the most pro-trump counties in the United States are dying from covid-19 at a rate more than five times higher than in the most antiTrump counties …

Back in September, Palin had boasted on Fox News: “I am one of those White, common-sense conservatives, I believe in science, and I have not taken the shot.” And now she says she won’t take it — unless and until she’s a dead body.

Thanks to Palin and other death-cult leaders, countless Republicans have become exactly that.

Dana Milbank / Washington Post

The Endurance — a legendary story of survival and courage

21 Dec, 2021 at 14:37 | Posted in Varia | Comments Off on The Endurance — a legendary story of survival and courage

In science, courage is to follow the motto of enlightenment and Kant’s dictum — Sapere Aude!  To use your own understanding, having the ​courage to think for yourself and question ‘received opinion,’ authority or orthodoxy.

In our daily lives, courage is a capability to confront fear, as when in front of the powerful and mighty, not to step back, but stand up for one’s right not to be humiliated or abused.

Courage is to do the right thing in spite of danger and fear.

As when Ernest Shackleton and Frank Worsley, in April 1916, aboard the small boat ‘James Caird’, spent 16 days crossing 1,300 km of ocean to reach South Georgia, then trekked across the island to a whaling station, and finally could rescue the remaining men from the crew of ‘Endurance’ left on the Elephant Island. Not a single member of the expedition died.

What we do in life echoes in eternity.

Analytical strategies in mediation analysis

21 Dec, 2021 at 12:01 | Posted in Statistics & Econometrics | Comments Off on Analytical strategies in mediation analysis

5. Example of a Basic Test of Mediation – Dr Martin LeaCase 3: Does cognitive skill (M) mediate the relation between college attendance (Z) and earnings (Y)? Case 3 involves one causal variable — college attendance — and two outcomes — one proximal (cognitive skill) and the other distal (earnings). College attendance is causal because a person may or may not go to college. Cognitive skill is not causal because one cannot be assigned or choose to have high skill; it is instead a “surrogate marker” for earnings. If prior research indicates that cognitive skill (which can be measured early) is a good predictor of later earnings, we may infer the impact of college attendance on earnings even before participants are old enough to work.

Case 3 poses a tough inferential problem even though it entails only one causal variable. To say that cognitive skill accounts for the impact of college attendance on earnings is to dismiss the possibility that college attendance can have a large effect on earnings even for people whose cognitive skill is unaffected by college attendance.

This idea cannot be tested via regression but can be tested through principal stratification … We might classify participants into three principal strata — one for those whose cognitive skill would increase a great deal if they attend college, a second for those whose skill would not increase much even as a result of attending college, and a third for those whose skill would increase even without attending college. If we find that college attendance strongly increases the earnings of persons in the second and third strata, that evidence will falsify the claim that college attendance improves earnings solely by increasing cognitive skill.

But unless we have a crystal ball, we can’t know a priori which stratum to put a person in. Nevertheless, by collecting pretreatment variables that predict college attendance and cognitive skill, we may be able to identify causal effects within each stratum … This approach does not constitute a full mediation analysis, but it does put some strong claims of mediation to an important test.

Stephen Raudenbush & Guanglei Hong

Economics journals — publishing lazy non-scientific work

21 Dec, 2021 at 10:48 | Posted in Economics | Comments Off on Economics journals — publishing lazy non-scientific work

In a new paper, Andrew Chang, an economist at the Federal Reserve and Phillip Li, an economist with the Office of the Comptroller of the Currency, describe their attempt to replicate 67 papers from 13 well-regarded economics journals …

unscientificTheir results? Just under half, 29 out of the remaining 59, of the papers could be qualitatively replicated (that is to say, their general findings held up, even if the authors did not arrive at the exact same quantitative result). For the other half whose results could not be replicated, the most common reason was “missing public data or code” …

H.D. Vinod, an economics professor at Fordham University … noted that … caution could be outweighed by the sheer amount of work it takes to clean up data files in order to make them reproducible.

“It’s human laziness,” he said. “There’s all this work involved in getting the data together” …

Bruce McCullough, said he thought the authors’ definition of what counted as replication – achieving the same qualitative, as opposed to quantitative, results – was far too generous. If a paper’s conclusions are correct, he argues, one should be able to arrive at the same numbers using the same data.

“What these journals produce is not science,” he said. “People should treat the numerical results as if they were produced by a random number generator.”

Anna Louie Sussman

Sail away

20 Dec, 2021 at 09:22 | Posted in Varia | Comments Off on Sail away

.

On the limited applicability of statistical physics to economics

19 Dec, 2021 at 19:20 | Posted in Economics | 1 Comment

Statistical mechanics reasoning may be applicable in the economic and social sciences, but only if adequate consideration is paid to the specific contexts and conditions of its application. This requires attention to “non-mechanical” processes of interaction, inflected by power, culture, institutions etc., and therefore of specific histories which gives rise to these factors …

you shall not pass statistical physics - You shall not pass | Meme GeneratorOutside of very specific cases, statistical physics is more likely to provide useful metaphors and ways of thinking than computational techniques and definite answers. Although statistical mechanical explanation can shed light on particular mechanisms that may be at play (e.g. explaining how distributions are shaped by the differences between the ways in which wages and profits may respectively evolve) these must be interpreted in a specific causal context … In the context of the human sciences, agency – not merely the exercise of individual choice but the shaping of the circumstances of collective life – is the central factor both in determining the properties of a system and in shaping individual choices. The exercise of human agency may bring a social system closer to an “equilibrium” in some circumstances, and disrupt it in others. It is among the specifically social factors that must be taken note of in the dialogue between statistical physics and the social sciences.

Sanjay Reddy

Financial regulations

18 Dec, 2021 at 18:22 | Posted in Economics | 6 Comments

A couple of years ago, former chairman of the Fed, Alan Greenspan, wrote in an article in the Financial Times, re the increased demands for stronger regulation of banks and finance:

Alan Greenspan and Ayn Rand at the White House after Greenspan was sworn in as chairman of Gerald Ford’s Council of Economic Advisers, September 1974Since the devastating Japanese earthquake and, earlier, the global financial tsunami, governments have been pressed to guarantee their populations against virtually all the risks exposed by those extremely low probability events. But should they? Guarantees require the building up of a buffer of idle resources that are not otherwise engaged in the production of goods and services. They are employed only if, and when, the crisis emerges.

The buffer may encompass expensive building materials whose earthquake flexibility is needed for only a minute or two every century, or an extensive stock of vaccines for a feared epidemic that may never occur. Any excess bank equity capital also would constitute a buffer that is not otherwise available to finance productivity-enhancing capital investment.

That is — to say the least — astonishing. Not wanting to take genuine uncertainty or ‘fat tails’ seriously is ominous enough. Is there anything the year 2008 taught us, it is that the ‘tail risks’ are genuinely real and must be included in all financial calculations. But even worse is how someone — who surely ought to have read at least an introductory course in economics — can get the idea that demand for higher capital requirements of banks would be equivalent to building buffers of ‘idle resources.’ The claim is from an economist’s point of view absolute nonsense.

Capital requirements are about how the mix between debt and equity of banks’ balance sheets should look like. It is not a question of something having to be set aside. It is not about liquidity or reserve requirements. Capital requirements are not about pea soup in a jar that we should put on stock to have in a crisis. It’s about how much leverage we should allow banks to have.

Higher capital requirements simply mean that we demand that banks finance a larger portion of their portfolios out of equity and less out of money deposited or loans. There is nothing here about resource use, but about how banks should manage risks. And how they are distributed in an economically efficient manner.

Of course, higher capital requirements mean that banks’ risk-taking decrease. It is precisely because of this the requirements have been instituted. We saw in the recent financial crisis how the ‘systemic risk’ shot up when the banks were found to have taken on too great risks. Financial institutions authorized to operate with high leverage generate negative externalities. Of course, we have to — in the light of the financial crisis — ensure that banks operate under less leverage. Higher capital requirements are one way of achieving this.

Let me illustrate the mechanism.

Suppose a crisis would come and there would be a loss of 1 million USD, and the bank’s own capital is, for example, 5% of the balance sheet, that would force the bank to liquidate assets at a value of 20 million USD to regain the 5% level. Obviously, systems repercussions would be monumental. Higher capital requirements would both reduce the risk of liquidation, and the repercussions would be smaller (20% equity level would, in our example, reduce leverage to 5 million USD).

Suppose the initial balance sheet looks like this:

Loan: 100    Shareholders’ equity: 5
Liabilities: 95

Now if you raise the capital requirement from 5% to 20%, the bank can in principle react in three ways:

A: Assets Liquidation
Loan: 25   Equity: 5
Liabilities: 20

B: Recapitalization
Loan: 100 Shareholders’ equity: 20
Liabilities: 80

C: Assets Expansion
New assets: 12.5
Loans: 100  Shareholders’ equity: 22.5
Liabilities: 90

In both cases B and C it is evident that the higher capital requirements do not mean that the balance sheet must be reduced. Banks can continue to provide the economy with the necessary loans. Some negative effects on the banks’ ability to perform their basic system functions need not occur because one raises the capital requirements.

This is basics. That a former Federal Reserve chairman does not understand this is, to say the least, disheartening.

But maybe that is how it goes when you prefer reading Ayn Rand to Keynes or Minsky …

Telegram — the global bullshit multiplicator

18 Dec, 2021 at 11:21 | Posted in Varia | Comments Off on Telegram — the global bullshit multiplicator

.

Joshua Angrist ‘Nobel Prize’ Lecture 2021

17 Dec, 2021 at 17:14 | Posted in Statistics & Econometrics | Comments Off on Joshua Angrist ‘Nobel Prize’ Lecture 2021

.

« Previous PageNext Page »

Blog at WordPress.com.
Entries and Comments feeds.

%d bloggers like this: