Avec le temps

26 Feb, 2021 at 17:04 | Posted in Varia | Leave a comment


Quel chef d’oeuvre! Cette tellement triste, belle et émouvante chanson, touche le plus profond de mon âme.

Dis, quand reviendras-tu?

26 Feb, 2021 at 13:49 | Posted in Varia | Leave a comment


Models and laws in economics

25 Feb, 2021 at 23:51 | Posted in Economics | Leave a comment

Great lecture on how to do — and not to do — economics, delivered by Robert Skidelsky.

Fighting neoliberalism with Keynes and Minsky

25 Feb, 2021 at 18:36 | Posted in Economics | Leave a comment

Covid-19 — la situation en Suède

24 Feb, 2021 at 21:56 | Posted in Politics & Society | Leave a comment


Why economists understand less today than they did a century ago

24 Feb, 2021 at 18:14 | Posted in Economics | Leave a comment

The leap of generalization

24 Feb, 2021 at 16:45 | Posted in Statistics & Econometrics | Leave a comment

Statistician Andrew Gelman has an interesting blogpost up on what inference in science really means:

gelmanI like Don Rubin’s take on this, which is that if you want to go from association to causation, state very clearly what the assumptions are for this step to work. The clear statement of these assumptions can be helpful in moving forward …

Another way to say this is that all inference is about generalizing from sample to population, to predicting the outcomes of hypothetical interventions on new cases. You can’t escape the leap of generalization. Even a perfectly clean randomized experiment is typically of interest only to the extent that it generalizes to new people not included in the original study.

I agree — but that’s also why we so often fail (even when having the best intentions) when it comes to making generalizations in social sciences.

What strikes me again and again when taking part of the results of randomized experiments is that they really are very similar to theoretical models. They all have the same basic problem — they are built on rather artificial conditions and have difficulties with the ‘trade-off’ between internal and external validity. The more artificial conditions, the more internal validity, but also less external validity. The more we rig experiments/models to avoid the ‘confounding factors,’ the less the conditions are reminiscent of the real ‘target system.’ The nodal issue is basically about how scientists using different isolation strategies in different ‘nomological machines’ attempt to learn about causal relationships. I doubt the generalizability of the (randomized or not) experiment strategy because the probability is high that causal mechanisms are different in different contexts and that lack of homogeneity/stability/invariance don’t give us warranted export licenses to the ‘real’ societies.

Evidence-based theories and policies are highly valued nowadays. Randomization is supposed to best control for bias from unknown confounders. The received opinion — including Rubin and Gelman — is that evidence based on randomized experiments therefore is the best.

More and more economists have also lately come to advocate randomization as the principal method for ensuring being able to make valid causal inferences. Especially when it comes to questions of causality, randomization is nowadays considered some kind of “gold standard”. Everything has to be evidence-based, and the evidence has to come from randomized experiments.

But just as econometrics, randomization is basically a deductive method. Given  the assumptions (such as manipulability, transitivity, Reichenbach probability principles, separability, additivity, linearity, etc., etc.)  these methods deliver deductive inferences. The problem, of course, is that we will never completely know when the assumptions are right. [And although randomization may contribute to controlling for confounding, it does not guarantee it, since genuine ramdomness presupposes infinite experimentation and we know all real experimentation is finite. And even if randomization may help to establish average causal effects, it says nothing of individual effects unless homogeneity is added to the list of assumptions.] Real target systems are seldom epistemically isomorphic to our axiomatic-deductive models/systems, and even if they were, we still have to argue for the external validity of  the conclusions reached from within these epistemically convenient models/systems. Causal evidence generated by randomization procedures may be valid in ‘closed’ models, but what we usually are interested in, is causal evidence in the real target system we happen to live in.

Many advocates of randomization want  to have deductively automated answers to  fundamental causal questions. But to apply ‘thin’ methods we have to have ‘thick’ background knowledge of  what’s going on in the real world, and not in (ideally controlled) experiments. Conclusions  can only be as certain as their premises — and that also goes for methods based on randomized experiments.

So yours truly agrees with Gelman that “all inference is about generalizing from sample to population.” But I don’t think randomized experiments — ideal or not — take us very far on that road. Randomized experiments in social sciences are far from being the ‘gold standard’ they so often are depicted as.

Agni Parthene

24 Feb, 2021 at 15:39 | Posted in Varia | Leave a comment

Frank Hahn on the value of equilibrium economics

22 Feb, 2021 at 10:16 | Posted in Economics | Leave a comment

Frank-HahnIt cannot be denied that there is something scandalous in the spectacle of so many people refining the analyses of economic states which they give no reason to suppose will ever, or have ever, come about. It probably is also dangerous. Equilibrium economics … is easily convertible into an apologia for existing economic arrangements and it is frequently so converted.

Frank Hahn

Keynes on the methodology of econometrics

21 Feb, 2021 at 20:39 | Posted in Statistics & Econometrics | Leave a comment

Machine Learning or Econometrics? | by Dr. Dataman | Analytics Vidhya |  Medium There is first of all the central question of methodology — the logic of applying the method of multiple correlation to unanalysed economic material, which we know to be non-homogeneous through time. If we are dealing with the action of numerically measurable, independent forces, adequately analysed so that we were dealing with independent atomic factors and between them completely comprehensive, acting with fluctuating relative strength on material constant and homogeneous through time, we might be able to use the method of multiple correlation with some confidence for disentangling the laws of their action … In fact we know that every one of these conditions is far from being satisfied by the economic material under investigation.

Letter from John Maynard Keynes to Royall Tyler (1938)

On the irrelevance of mainstream economics

20 Feb, 2021 at 12:06 | Posted in Economics | Leave a comment

There is something about the way mainstream economists construct their models nowadays that obviously doesn’t sit right.

One might have hoped that humbled by the manifest failure of its theoretical pretences during the latest economic-financial crises, the one-sided, almost religious, insistence on axiomatic-deductivist modelling as the only scientific activity worthy of pursuing in economics would give way to methodological pluralism based on ontological considerations rather than formalistic tractability. But — empirical evidence still only plays a minor role in mainstream economic theory, where models largely function as a substitute for empirical evidence.

Image result for the nature lawsonThe dominant ideology in the economics academy, I am maintaining, is precisely the extraordinarily wide-spread and long-lasting belief that mathematical modelling is somehow neutral at the level of content or form, but an essential method for science, underpinning any proper or serious economics …

The scandal of modern economics is not that it gets so many things wrong, but that it is so largely irrelevant. However in being irrelevant … the mainstream modelling orientation cannot but serve to deflect criticism from the nature of status quo at the level of the economy and thereby work to sustain it … In truth, few people take any mainstream analysis seriously, except in economics faculties’ promotion exercises.

If macroeconomic models — no matter of what ilk — build on microfoundational assumptions of representative actors, rational expectations, market clearing, and equilibrium, and we know that real people and markets cannot be expected to obey these assumptions, the warrants for supposing that conclusions or hypotheses of causally relevant mechanisms or regularities can be bridged, are obviously non-justifiable. Incompatibility between actual behaviour and the behaviour in macroeconomic models building on representative actors and rational expectations microfoundations is not a symptom of ‘irrationality.’ It rather shows the futility of trying to represent real-world target systems with models flagrantly at odds with reality.

A gadget is just a gadget – and no matter how many brilliantly silly mathematical models you come up with, they do not help us working with the fundamental issues of modern economies. The mainstream economics project is — mostly because of its irrelevance — seriously harmful to most people, but also seriously harmless for those who benefit from the present status quo of our societies.

Ekonomi – vetenskap eller gissningslek?

19 Feb, 2021 at 11:15 | Posted in Economics | Leave a comment

Image result for arne anka baksmällan Är nationalekonomi vetenskapligt baserad kunskap? Kan man förutspå hur enskilda individer eller hela samhällen kommer att agera ekonomiskt? Till exempel om miljonbonusar gör toppchefer mer lojala mot de företag som anställt dom? Kan ekonomiska analytiker verkligen se in i framtiden och förutspå kommande kriser? Eller handlar ekonomernas prognoser mer om en kvalificerad gissningslek?

Yours truly, Tore Ellingsen, och Daniel Waldenström ger sina svar i det här avsnittet av P1:s Vetandets värld.

Economics — where does it lead us?

19 Feb, 2021 at 09:51 | Posted in Economics | 2 Comments

Image result for ariel rubinstein The issue of interpreting economic theory is, in my opinion, the most serious problem now facing economic theorists. The feeling among many of us can be summarized as follows. Economic theory should deal with the real world. It is not a branch of abstract mathematics even though it utilizes mathematical tools. Since it is about the real world, people expect the theory to prove useful in achieving practical goals. But economic theory has not delivered the goods. Predictions from economic theory are not nearly as accurate as those offered by the natural sciences, and the link between economic theory and practical problems … is tenuous at best. Economic theory lacks a consensus as to its purpose and interpretation. Again and again, we find ourselves asking the question “where does it lead?”

Ariel Rubinstein

Adorno on pop culture

19 Feb, 2021 at 09:39 | Posted in Politics & Society | 1 Comment

Image result for adorno pop cultureWhen Adorno issued his own analyses of pop culture, though, he went off the beam. He was too irritated by the new Olympus of celebrities—and, even more, by the enthusiasm they inspired in younger intellectuals—to give a measured view. In the wake of “The Work of Art,” Adorno published two essays, “On Jazz,” and “On the Fetish Character of Music and the Regression of Listening,” that ignored the particulars of pop sounds and instead resorted to crude generalizations. Notoriously, Adorno compares jitterbugging to “St. Vitus’ dance or the reflexes of mutilated animals.” He shows no sympathy for the African-American experience, which was finding a new platform through jazz and popular song. The writing is polemical, and not remotely dialectical.

Alex Ross / The New Yorker

Manufacturing strategic ignorance

19 Feb, 2021 at 00:34 | Posted in Theory of Science & Methodology | Leave a comment


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