All Human Beings

26 Feb, 2022 at 16:26 | Posted in Politics & Society | 1 Comment


Ukraine, Kiev - Sweden Abroad

How to make good decisions in a radically uncertain world

26 Feb, 2022 at 09:55 | Posted in Economics | 1 Comment


To understand real-world decisions and unforeseeable changes in behaviour, ergodic probability distributions are of no avail. In a world full of genuine uncertainty — where real historical time rules the roost — the probabilities that ruled the past are not necessarily those that will rule the future.

Time is what prevents everything from happening at once. To simply assume that economic processes are ergodic and concentrate on ensemble averages — and a fortiori in any relevant sense timeless — is not a sensible way for dealing with the kind of genuine uncertainty that permeates open systems such as economies.

When you assume the economic processes to be ergodic, ensemble and time averages are identical. Let me give an example: Assume we have a market with an asset priced at 100 €. Then imagine the price first goes up by 50% and then later falls by 50%. The ensemble average for this asset would be 100 €- because we here envision two parallel universes (markets) where the asset-price falls in one universe (market) with 50% to 50 €, and in another universe (market) it goes up with 50% to 150 €, giving an average of 100 € ((150+50)/2). The time average for this asset would be 75 € – because we here envision one universe (market) where the asset-price first rises by 50% to 150 €, and then falls by 50% to 75 € (0.5*150).

From the ensemble perspective nothing, on average, happens. From the time perspective lots of things, on average, happen.

Assuming ergodicity there would have been no difference at all. What is important with the fact that real social and economic processes are nonergodic is the fact that uncertainty — not risk — rules the roost. That was something both Keynes and Knight basically said in their 1921 books. Thinking about uncertainty in terms of ‘rational expectations’ and ‘ensemble averages’ has had seriously bad repercussions on the financial system.

Knight’s uncertainty concept has an epistemological founding and Keynes’ definitely an ontological founding. Of course, this also has repercussions on the issue of ergodicity in a strict methodological and mathematical-statistical sense. I think Keynes’ view is the most warranted of the two.

The most interesting and far-reaching difference between the epistemological and the ontological view is that if one, as Kay do, subscribes to the former, Knightian view, you open up for the mistaken belief that with better information and greater computer-power we somehow should always be able to calculate probabilities and describe the world as an ergodic universe. As Keynes convincingly argued, that is ontologically just not possible. To Keynes, the source of uncertainty was in the nature of the real — nonergodic — world. It had to do, not only — or primarily — with the epistemological fact of us not knowing the things that today are unknown, but rather with the much deeper and far-reaching ontological fact that there often is no firm basis on which we can form quantifiable probabilities and expectations at all.

Often we do not know because we cannot know.

A day that will live forever in infamy in European history

24 Feb, 2022 at 14:37 | Posted in Politics & Society | 38 Comments

How do you grieve for a nation? I don’t know.

But one thing I do know is that February 24th 2022 is one of the saddest days I and all my brothers and sisters in Ukraine have ever experienced. The verdict of history will be harsh.


Bayes vs classical statistical p-testing

23 Feb, 2022 at 08:10 | Posted in Statistics & Econometrics | 1 Comment


[For more on the RCT referred to in the video, take a look here. Mortality numbers are, of course, important, but so is the fact that among the 241 patients who received the drug, 52 developed severe illness, compared to 43 of 249 patients who did not take the drug … ]

MMT and ‘monetary crankery’

22 Feb, 2022 at 08:03 | Posted in Economics | 4 Comments

MMTists often like to position themselves as the only ones to properly understand the ‘operational realities’ of modern monetary systems. Ironically, many of the claims made by MMTists on this topic are misleading at best. One common rhetorical tactic that I’ve noticed they employ, which often catches their critics out, is to use the term ‘government’ in a way that’s different typically from how it is used in mainstream economics. When they say ‘government’, they tend to include basically any institution that is an agent of the state, including the central bank — hence the ‘government’ here includes consolidating the treasury and the central bank into one entity, effectively ignoring or assuming away any independence the central bank may have.

Upholding Economics

Modern Money Theory by Wray, L. Randall (ebook)Effectively “ignoring or assuming away any independence the central bank may have”? That is strange indeed: Last — just to take one example — I had a look in L. Randall Wray’s Modern Money Theory there were more than fifty pages devoted to “technical details of central bank and treasury coordination” and diverse fiscal operations of the Fed and the Treasury. Guess we have to go looking for ‘bad monetary crankery’ somewhere else …

Vad ‘kontrollera för något’ betyder i regressionsanalys

21 Feb, 2022 at 10:57 | Posted in Statistics & Econometrics | Comments Off on Vad ‘kontrollera för något’ betyder i regressionsanalys


Dynamic and static interpretations of regression coefficients

20 Feb, 2022 at 16:33 | Posted in Statistics & Econometrics | Comments Off on Dynamic and static interpretations of regression coefficients

When econometric and statistical textbooks present simple (and multiple) regression analysis for cross-sectional data, they often do it with regressions like “regress test score (y) on study hours (x)” and get the result

y = constant + slope coefficient*x + error term.

How to Interpret Regression Analysis Results: P-values & Coefficients? –  StatsworkWhen speaking of increases or decreases in x in these interpretations, we have to remember that it is a question of cross-sectional data and ‘increases’ — which means that we are referring to increases in the value of a variable from one unit in the population to another unit in the same population. Strictly seen it is only admissible to give slope coefficients a dynamic interpretation when we are dealing with time-series regression. For cross-sectional data, we should stick to static interpretations and look upon slope coefficients as giving information about what we can expect to happen to the value of the dependent variable when there is a change in the independent variable from one unit to another.

Although it is tempting to say that a change in the independent variable leads to a change in the dependent variable, we should resist that temptation. Students that put a lot of study hours into their daily routine on average achieve higher scores on their tests than other students that study for fewer hours. But — the regressions made do not analyse what happens to individual students as they increase or decrease their study hours.

Why is this important? It is important most of all because interpreting the regression coefficients wrong may give a totally wrong causal view of what is going on in your data. A positive relation between test scores and study hours in a cross-sectional regression does not mean that you as an individual student should expect to get higher test scores by increasing study time.

Never seek to tell thy love

20 Feb, 2022 at 12:07 | Posted in Varia | Comments Off on Never seek to tell thy love


Listening to the choral music on Armonico Consort’s Naked Byrd Two anthology is an unending delight. One of my favorite albums.

Stephen Marglin sur le besoin d’une nouvelle théorie économique

18 Feb, 2022 at 19:01 | Posted in Economics | 1 Comment

Peut-on élaborer une nouvelle théorie économique qui permettra d’influencer les gouvernements actuels et futurs dans le sens du progrès, de la résolution des crises et de la recherche du bien-être collectif ?

The Harvard CrimsonOui, bien entendu, mais cela ne se fera pas en un jour. Nous devrons pour cela commencer par désapprendre les fondements de l’économie traditionnelle – le présupposé de l’individualisme, l’idéologie de l’hyper-rationalité, l’absence de limites. Et Keynes nous rappelle que c’est la partie la plus difficile de la tâche à accomplir. Viendra ensuite la construction d’un cadre de travail qui incorpore la connectivité qui nous relie les uns aux autres, intègre notre dépendance au savoir expérimental et admet l’existence de limites. Et pour ceux d’entre nous qui restent imprégnés des doctrines de la vieille (et de la nouvelle) gauche, ce cadre devra procéder à une reconsidération de la nature de la lutte des classes au XXIe siècle.

Nous ne devons cependant pas sous-estimer les difficultés. Keynes avait peut-être raison quand, à la fin de sa Théorie générale, il soulignait qu’ « on exagère grandement la force des intérêts constitués par rapport à l’empire qu’acquièrent progressivement les idées ». Mais le marché des idées est un marché très éloigné des normes de la concurrence parfaite ! Il accueille à bras ouverts ceux qui sont dotés d’un pouvoir d’achat, tandis que ceux qui remettent en cause le pouvoir de l’argent peinent à se faire entendre. En dehors du 1 % [les plus riches], nous payons tous le prix de cet échec particulier du marché.

Pourtant, comme l’écrivait Albert Camus dans ses Lettres à un ami allemand [Gallimard, 1945] à la fin de 1943, moment grave de l’histoire de la France et du monde, chacun « doit décider s’il est avec les bourreaux ou avec les martyrs, selon sa vocation ». Pour paraphraser Tarfon (Ier siècle après J.-C.), « il ne nous sera peut-être pas accordé de terminer le travail ; mais nous ne pouvons nous dérober à la nécessité de l’entreprendre ».

Le Monde

Warum der Neoliberalismus uns kaputt macht

18 Feb, 2022 at 07:55 | Posted in Politics & Society | Comments Off on Warum der Neoliberalismus uns kaputt macht


Misunderstanding randomization

17 Feb, 2022 at 18:32 | Posted in Statistics & Econometrics | Comments Off on Misunderstanding randomization

Sander Greenland | Jonathan and Karin Fielding School of Public HealthWhile raising worthwhile points, most discussions I see misunderstand randomization in both causal and statistical ways. Notably, randomization can be valuable but does not induce balance in the ordinary English sense of the word, nor does it deal with most problems of real experiments. Furthermore, the use of the word “balance” to describe what randomization actually does invites confusion with the ordinary English meaning of “balance” (as does use of ordinary words like “significance” and “confidence” to describe other technical concepts).

Causally, a controlled experiment is one which the experimenter causally controls the causes of (inputs to) the treatment (studied cause) or the outcome (studied effect) – preferably both. A randomized experiment is one in which the causes of the treatment are fully determined by a known randomizing device (at least within levels of fully measured covariates), so that there is nothing unmeasured that causes both treatment and outcome. Provided the outcome is shielded from any effect of the randomizing device except that through (mediated by) the treatment, the random assignment variable becomes a perfect instrumental variable (IV), and statistical techniques based on such perfect IVs can be justified without recourse to dodgy empirical tests. A similar view can be found in Pearl’s book (Causality, 2nd ed. 2009).

Statistically, a frequentist can use the randomization distribution of A to construct a reference distribution for test statistics under various models (hypotheses) about the treatment effect (usually only a test of a no-effect model is described in this fashion, but most so-called confidence intervals are summaries of tests of models across which the treatment effect but nothing else is varied). This view can be seen in writings by Stephen Senn and James Robins. In parallel a Bayesian can use the distribution to provide prior distributions for counterfactual outcomes under the same variety of models (Cornfield, American Journal of Epidemiology 1976).

Note that none of these descriptions use or need the term “balance”, nor need they make claims that randomization corresponds to no confounding (Greenland and Mansournia, European Journal of Epidemiology 2015). Proper randomization can be said to provide “balance in probability” but for frequentists this property is over a purely hypothetical long run while for Bayesians it is a subjective prior probability induced by the knowing that allocation was random (Cornfield 1976 again). Neither use of “balance” applies to the actual state of observed trial populations, which both theories allow or concede may be arbitrarily out of balance on unmeasured covariates due to “bad luck of the draw” (“random confounding” as per Greenland & Mansournia 2015). By properly merging the randomization distribution (information on allocation) and models for treatment effect, frequentists can deal with this chance element via P-value functions (“confidence distributions”) while Bayesians can deal with it via posterior distributions. Again, neither need invoke “balance” – and I would argue that, to avoid the confusion seen in much literature, they shouldn’t.

None of this should be taken as sanctifying or criticizing randomization; I am simply pointing out that randomization, if done and described precisely, does something valuable – but that is not balance of actual samples (as opposed to hypothetical infinite samples or repetitions, or bets about actual samples). Real randomized studies of humans and their groupings must deal with many other considerations such as selectivity of study subjects (hence lack of generalizability), blinding (masking) of subjects and evaluators, outcome measurement error, nonadherence, drop-out, competing risks, etc. Randomization can help deflect concerns about confounding in probability, but is no panacea, and can increase other concerns such as selectivity of participation.

Sander Greenland

Förväxla inte samhällsekonomi med hushållsekonomi

17 Feb, 2022 at 10:59 | Posted in Economics | 1 Comment

Det er foruroligende, at to tidligere overvismænd, såkaldte ’topøkonomer’ Torben M. Andersen og Michael Svarer uden at ryste på hånden kan konkludere først i Jyllandsposten (20. juni, 2020) og dernæst uændret i Altinget så sent som 15. januar 2021 på følgende måde:

Mindre brug af offentlige ressourcer i dag øger muligheden for større offentligt forbrug i fremtiden, og bidrager således til også at have et stærkt forsvar næste gang, der kommer en økonomisk krise’.

Jesper Jespersen - Images | CristofariphotoDette ræsonnement gælder for en husholdning; men ikke for samfundsøkonomien set under ét, hvori den offentlige sektor udgør en væsentlig del. Her er det netop samspillet og den gensidige afhængighed mellem den private og den offentlige sektor, som er i fokus. Og hvor andre bogholderimæssige sammenhænge end for den private husholdning gælder, hvilket ’topøkonomerne’ om nogen burde være opmærksomme på i deres analyse – for slet ikke at sige anbefalinger …

Men det er desværre ikke den eneste fejl ’husholdningsøkonomerne’ begår. Topøkonomerne skriver i deres kronikker fortsat uden at ryste på hånden:

”Det er farligt for lande med høj gæld è [for det skaber] et pres på renteniveauet”

Underforstået: lande med høj offentlig gæld risikerer, at renten stiger.

Atter et husholdningsøkonomisk fejlræsonnement, der bringer dem endnu et skridt nærmere dumpegrænsen i faget samfundsøkonomi.

Topøkonomerne forveksler nemlig statsgæld med udlandsgæld, hvilket leder til en fatal fejlrepræsentation af, hvilken situation dansk økonomi befinder sig i. Danmark er nemlig i den gunstige position, at landet ikke har nogen udlandsgæld; men tværtimod en betydelig udlandsformue endog på mere end 50 pct. af BNP, hvilket er på niveau med Tyskland. Og ikke nok med det; for denne udlandsformue vokser år for år som et resultat af et solidt overskud på betalingsbalancen over for udlandet. Pengene fosser billedligt talt ind fra udlandet …

Konsekvenserne af en voksende statsgæld fejlvurderes … hvis den bogholderimæssigt modsvarende finansielle formue ikke samtidigt inddrages i analysen. Hvad er modstykket i Japan, Tyskland og Danmark til de store overskud på betalingsbalancen over for udlandet? Hertil er der kun ét bogholderimæssigt svar, hvorom der ikke kan diskuteres, at det må være en national finansiel opsparing. Hvor finansiel opsparing betyder, at der spares mere op, end der foretages reale investeringer (i fremtiden) – altså underinvestering! Disse lande har med andre ord internt et opsparingsoverskud, fordi der investeres mindre, end der spares op, navnlig i den private sektor. Dette opsparingsoverskud er med til at presse renten ned. Men selv ved det historisk lave renteniveau er der et gab mellem opsparing og reale investeringer i den private sektor. Dette gab kan staten med fordel udfylde ved at øge de offentlige investeringer …

Det er vigtigt at forstå, at den samfundsøkonomiske krise primært er forårsaget af, at private husholdninger og virksomheder i Danmark og i udlandet billedligt talt sidder på pengene. Det private forbrug og i stigende grad eksporten er faldet, hvilket har gjort virksomhederne usikre på fremtiden, hvorfor de har annulleret en stribe investeringsprojekter. Den private overopsparing er med andre ord steget markant og har forårsaget den stigende arbejdsløshed. Problemet løses ikke ved, at staten midlertidigt har holdt hånden under den private sektor med en stribe ’hjælpepakker’. Det er en for defensiv strategi, som der med rette advares mod at forlænge.

Jesper Jespersen

Att stater runt om i världen under coronaåren behövt spendera mer för att hålla igång ekonomin innebär inte att den måste spara framöver för att få “balans” i ekonomin. Pengarna tar inte slut. Vad Jespersen i sin artikel så väl belyser är hur många politiker och så kallade experter inte verkar (vilja) förstå att det finns en avgörande skillnad mellan privata och offentliga skulder.

Om en individ försöker spara och dra ner på sina skulder, så kan det mycket väl vara rationellt. Men om alla försöker göra det, blir följden att den aggregerade efterfrågan sjunker och arbetslösheten riskerar ökar.

En enskild individ måste alltid betala sina skulder. Men en stat kan alltid betala tillbaka sina gamla skulder med nya skulder. Staten är inte en individ eller ett hushåll. Statliga skulder är inte som privata skulder. En stats skulder är väsentligen en skuld till den själv, till dess medborgare.

Zemmour, Vichy et les juifs de France

16 Feb, 2022 at 15:28 | Posted in Politics & Society | Comments Off on Zemmour, Vichy et les juifs de France


Do RCTs really control for ‘lack of balance’?

16 Feb, 2022 at 11:14 | Posted in Statistics & Econometrics | 1 Comment

Mike Clarke, the Director of the Cochrane Centre in the UK, for example, states on the Centre’s Web site: ‘In a randomized trial, the only difference between the two groups being compared is that of most interest: the intervention under investigation’.

Evidence-based medicine is broken: why we need data and technology to fix itThis seems clearly to constitute a categorical assertion that by randomizing, all other factors — both known and unknown — are equalized between the experimental and control groups; hence the only remaining difference is exactly that one group has been given the treatment under test, while the other has been given either a placebo or conventional therapy; and hence any observed difference in outcome between the two groups in a randomized trial (but only in a randomized trial) must be the effect of the treatment under test.

Clarke’s claim is repeated many times elsewhere and is widely believed. It is admirably clear and sharp, but it is clearly unsustainable … Clearly the claim taken literally is quite trivially false: the experimental group contains Mrs Brown and not Mr Smith, whereas the control group contains Mr Smith and not Mrs Brown, etc. Some restriction on the range of differences being considered is obviously implicit here; and presumably the real claim is something like that the two groups have the same means and distributions of all the [causally?] relevant factors. Although this sounds like a meaningful claim, I am not sure whether it would remain so under analysis … And certainly, even with respect to a given (finite) list of potentially relevant factors, no one can really believe that it automatically holds in the case of any particular randomized division of the subjects involved in the study. Although many commentators often seem to make the claim … no one seriously thinking about the issues can hold that randomization is a sufficient condition for there to be no difference between the two groups that may turn out to be relevant …

In sum, despite what is often said and written, no one can seriously believe that having randomized is a sufficient condition for a trial result to be reasonably supposed to reflect the true effect of some treatment. Is randomizing a necessary condition for this? That is, is it true that we cannot have real evidence that a treatment is genuinely effective unless it has been validated in a properly randomized trial? Again, some people in medicine sometimes talk as if this were the case, but again no one can seriously believe it. Indeed, as pointed out earlier, modern medicine would be in a terrible state if it were true. As already noted, the overwhelming majority of all treatments regarded as unambiguously effective by modern medicine today — from aspirin for mild headache through diuretics in heart failure and on to many surgical procedures — were never (and now, let us hope, never will be) ‘validated’ in an RCT.

John Worrall

For more on the question of ‘balance’ in randomized experiments, the recent paper by Marco Martinez & David Teira gives some valuable insights.

How to compute causal effects using regression (student stuff)

16 Feb, 2022 at 10:28 | Posted in Statistics & Econometrics | Comments Off on How to compute causal effects using regression (student stuff)


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