What’s the use of economics?

19 Jul, 2018 at 09:57 | Posted in Economics | 3 Comments

The simple question that was raised during a recent conference … was to what extent has – or should – the teaching of economics be modified in the light of the current economic crisis? The simple answer is that the economics profession is unlikely to change. Why would economists be willing to give up much of their human capital, painstakingly nurtured for over two centuries? For macroeconomists in particular, the reaction has been to suggest that modifications of existing models to take account of ‘frictions’ or ‘imperfections’ will be enough to account for the current evolution of the world economy. The idea is that once students have understood the basics, they can be introduced to these modifications.

However, other economists such as myself feel that we have finally reached the turning point in economics where we have to radically change the way we conceive of and model the economy. The crisis is an opportune occasion to carefully investigate new approaches … Rather than making steady progress towards explaining economic phenomena professional economists have been locked into a narrow vision of the economy. We constantly make more and more sophisticated models within that vision until, as Bob Solow put it, “the uninitiated peasant is left wondering what planet he or she is on” …

Every student in economics is faced with the model of the isolated optimising individual who makes his choices within the constraints imposed by the market … The student then moves on to macroeconomics and is told that the aggregate economy or market behaves just like the average individual she has just studied. She is not told that these general models in fact poorly reflect reality. For the macroeconomist, this is a boon since he can now analyse the aggregate allocations in an economy as though they were the result of the rational choices made by one individual. The student may find this even more difficult to swallow when she is aware that peoples’ preferences, choices and forecasts are often influenced by those of the other participants in the economy. Students take a long time to accept the idea that the economy’s choices can be assimilated to those of one individual.

Alan Kirman What’s the use of economics?

An economic theory that does not go beyond proving theorems and conditional ‘if-then’ statements — and do not make assertions and put forward hypotheses about real-world individuals and institutions — is of little consequence for anyone wanting to use theories to better understand, explain or predict real-world phenomena.

Building theories and models on patently ridiculous assumptions we know people never conform to, does not deliver real science. Real and reasonable people have no reason to believe in ‘as-if’ models of ‘rational’ robot-imitations acting and deciding in a Walt Disney-world characterised by ‘common knowledge,’ ‘full information,’ ‘rational expectations,’ zero transaction costs, given stochastic probability distributions, risk-reduced genuine uncertainty, and other laughable nonsense assumptions of the same ilk. Science fiction is not science.

For decades now, economics students have been complaining about the way economics is taught. Their complaints are justified. Force-feeding young and open-minded people with unverified and useless autistic mainstream theories and models cannot be the right way to develop a relevant and realist economic science.

Much work done in mainstream theoretical economics is devoid of any explanatory interest. And not only that. Seen from a strictly scientific point of view, it has no value at all. It is a waste of time. And as so many have been experiencing in modern times of austerity policies and market fundamentalism — a very harmful waste of time.

La femme qui est dans mon lit

18 Jul, 2018 at 16:19 | Posted in Varia | Comments Off on La femme qui est dans mon lit


The captain of an unconquerable soul

18 Jul, 2018 at 10:39 | Posted in Politics & Society | 1 Comment

A hundred years ago, in July 1918, the unconquerable soul of one of the greatest​ men that have walked this earth was born — Nelson Mandela.

This poem helped him keep​ hope alive for​ 27 years in prison.

Long live his memory.

Il cittadino medio 100 anni fa non credeva ci fosse alcuna possibilità di migliorare le proprie condizioni di vita. Persino in una democrazia come gli Stati Uniti la segregazione razziale e la discriminazione sistematica erano leggi in metà del Paese, e norme nell’altra metà. Ma attraverso sacrifici e leadership incrollabile, e forse soprattutto con il suo esempio morale, Mandela e il movimento che ha guidato hanno finito per significare qualcosa di più grande. È diventato il simbolo delle aspirazioni universali dei diseredati in tutto il mondo.

Barack Obama

Using economics as a propaganda device

17 Jul, 2018 at 17:54 | Posted in Economics | 9 Comments

diesThe most serious deficiency of implicit formal theories is that the verbal language disguises the abstractness of the theory … The consequence of the fallacy of misplaced concreteness is that the theory looks too convincing to its proponents​ … He becomes​ the prisoner of his own logical model and is rendered incapable​ of seeing reality from any other standpoint …

The most widespread example is provided by the neoclassical economists, such as Frank​ Knight, Ludwig von Mises, Henry Simons, and their present-day followers. These people seemed to think they had penetrated to the very essence of rational human action, and that they knew whatever was​ knowable about it … In other words, they believed that their abstract postulates​ were concrete​ descriptions of empirical reality … The followers of these economists, the Buchanans and McCord​ Wrights … are using their implicit​ formal theory as a propaganda device to support the present capitalist social order.

The psychopathy of Ayn Rand

15 Jul, 2018 at 16:53 | Posted in Politics & Society | 6 Comments

Now, I don’t care to discuss the alleged complaints American Indians have against this country. I believe, with good reason, the most unsympathetic Hollywood portrayal of Indians and what they did to the white man. They had no right to a country merely because they were born here and then acted like savages. The white man did not conquer this country …

Since the Indians did not have the concept of property or property rights—they didn’t have a settled society, they had predominantly nomadic tribal “cultures”—they didn’t have rights to the land, and there was no reason for anyone to grant them rights that they had not conceived of and were not using …

What were they fighting for, in opposing the white man on this continent? For their wish to continue a primitive existence; for their “right” to keep part of the earth untouched—to keep everybody out so they could live like animals or cavemen. Any European who brought with him an element of civilization had the right to take over this continent, and it’s great that some of them did. The racist Indians today—those who condemn America—do not respect individual rights.

Ayn Rand,  Address To The Graduating Class Of The United States Military Academy at West Point, 1974

It’s sickening to read this gobsmacking trash. But it’s perhaps even more sickening that people like Alan Greenspan consider Rand some​ kind of intellectual hero.

Alan Greenspan isn’t just a bad economist. He’s a bad person. What else can one think of a person that considers Ayn Rand — with the ugliest psychopathic philosophy the postwar world has produced — one of the great thinkers of the 20th century? A person that even co-edited a book with her — maintaining that unregulated capitalism is a “superlatively moral system”. A person that in his memoirs tries to reduce his admiration for Rand to a youthful indiscretion — but who actually still today can’t be described as anything else than a loyal Randian disciple.

Ayn Rand and her objectivist philosophy have​ more disciples than Greenspan. But as Hilary Putnam rightfully noticed in The Collapse of the Fact/Value Dichotomy (Harvard University Press, 2002) it’s doubtful if it even qualifies as a real philosophy:

It cannot be the case that the only universally valid norm refers solely to discourse. It is, after all, possible for someone to recognize truth-telling as a binding norm while otherwise being guided solely by ‘enlightened egoism.’ (This is, indeed, the way of life that was recommended by the influential if amateurish philosophizer – I cannot call her a philosopher – Ayn Rand.) But such a person can violate the spirit if not the letter of the principle of communicative action at every turn. After all, communicative action is contrasted with manipulation, and as such a person can manipulate people without violating the maxims of ‘sincerity, truth-telling, and saying only what one believes to be rationally warranted.’ Ayn Rand’s capitalist heroes manipulated people all the time (even if she didn’t consider it manipulation) via their control of capital, for example. Indeed, the person who says, ‘do what I want or I’ll shoot you,’ need not be violating any maxim concerned solely with discourse. But it would be a mistake to use such examples as objections to Habermasian ‘discourse ethics.’

In her diary from 1928, Ayn Rand approvingly quotes a statement made by a William Edward Hickman – “What is good for me is right.” Rand is enthusiastic and writes: “The best and strongest expression of a real man’s psychology I have heard.”

Later she models one of her heroes​  – Danny Renahan – after Hickman. Renahan is portrayed as

born with a wonderful, free, light consciousness — [resulting from] the absolute lack of social instinct or herd feeling. He does not understand, because he has no organ for understanding, the necessity, meaning, or importance of other people … Other people do not exist for him and he does not understand why they should.

Who was this  Hickman that so inspired Rand?

Hickman was a notorious bank robber, child kidnapper and mass murderer. One of the most hated and heinous criminals in U. S. history.

How people like Alan Greenspan and Paul Ryan — not to mention all modern day ‘objectivist’ disciples — can consider Ayn Rand “one of the greatest thinkers of the 20th century” is really beyond comprehension. It’s sickening.

The force from above

15 Jul, 2018 at 16:45 | Posted in Varia | Comments Off on The force from above


Interview mit Esther Duflo

14 Jul, 2018 at 09:29 | Posted in Economics | Comments Off on Interview mit Esther Duflo

ZEITmagazin: Ich könnte Ihnen von ähnlichen Absurditäten aus dem deutschen Bildungswesen erzählen.

the-secret-word-is-randomizationDuflo: Und bestimmt nicht nur aus den Schulen. Darum haben wir unsere Methode aus den Entwicklungsländern nach Europa und in die USA exportiert. Viele Länder der EU zum Beispiel bezahlen jungen Arbeitslosen ein Training für Bewerbungsgespräche. Wir haben randomisierte Experimente gemacht: Die Arbeitslosen mit Training finden tatsächlich schneller einen Job – aber nur so lange, wie nicht alle Bewerber an einem Ort das Training bekommen. Wenn das Bewerbungstraining also zum Standardprogramm wird, ist es ganz einfach hinausgeworfenes Geld.

ZEITmagazin: Was sollte man stattdessen tun?

Duflo: Die traurige Antwort ist: Wir haben derzeit keine guten Programme, um Arbeitslosen bei der Jobsuche zu helfen.

ZEITmagazin: Und allein mit Ihren Experimenten lassen sich auch keine finden. Denn zunächst zeigen Ihre Versuche, was alles nicht funktioniert.

Duflo: Trotzdem ist die Methode nützlich. Bevor Sie wirkungsvoll helfen können, müssen Sie erst viele Irrwege gehen. Und dabei versteht man die Zusammenhänge mit der Zeit immer besser. So führt ein Experiment zum nächsten, und am Ende kommt mitunter doch eine hilfreiche Lösung heraus.

Die Zeit

Regression analysis — a case of wishful thinking

13 Jul, 2018 at 18:34 | Posted in Statistics & Econometrics | Comments Off on Regression analysis — a case of wishful thinking

The impossibility of proper specification is true generally in regression analyses across the social sciences, whether we are looking at the factors affecting occupational status, voting behavior, etc. The problem is that as implied by the conditions for regression analyses to yield accurate, unbiased estimates, you need to investigate a phenomenon that has underlying mathematical regularities – and, moreover, you need to know what they are. Neither seems true. I have no reason to believe that the way in which multiple factors affect earnings, student achievement, and GNP have some underlying mathematical regularity across individuals or countries. More likely, each individual or country has a different function, and one that changes over time. Even if there was some constancy, the processes are so complex that we have no idea of what the function looks like.

regressionResearchers recognize that they do not know the true function and seem to treat, usually implicitly, their results as a good-enough approximation. But there is no basis for the belief that the results of what is run in practice is anything close to the underlying phenomenon, even if there is an underlying phenomenon. This just seems to be wishful thinking. Most regression analysis research doesn’t even pay lip service to theoretical regularities. But you can’t just regress anything you want and expect the results to approximate reality. And even when researchers take somewhat seriously the need to have an underlying theoretical framework – as they have, at least to some extent, in the examples of studies of earnings, educational achievement, and GNP that I have used to illustrate my argument – they are so far from the conditions necessary for proper specification that one can have no confidence in the validity of the results.

Steven J. Klees

The theoretical conditions that have to be fulfilled for regression analysis and econometrics to really work are nowhere even closely met in reality. Making outlandish statistical assumptions do not provide a solid ground for doing relevant social science and economics. Although regression analysis and econometrics have become the most used quantitative methods in social sciences and economics today, it’s still a fact that the inferences made from them are — strictly seen — invalid.

In need of medication

13 Jul, 2018 at 13:42 | Posted in Politics & Society | 1 Comment

In Trump-era US, reality sure beats fiction in the worst way possible, day after day.

The main reason why almost all econometric models are wrong

13 Jul, 2018 at 09:33 | Posted in Statistics & Econometrics | 3 Comments

How come that econometrics and statistical regression analyses still have not taken us very far in discovering, understanding, or explaining causation in socio-economic contexts? That is the question yours truly has tried to answer in an article published in the latest issue of World Economic Association Commentaries:

The processes that generate socio-economic data in the real world cannot just be assumed to always be adequately captured by a probability measure. And, so, it cannot be maintained that it even should be mandatory to treat observations and data — whether cross-section, time series or panel data — as events generated by some probability model. The important activities of most economic agents do not usually include throwing dice or spinning roulette-wheels. Data generating processes — at least outside of nomological machines like dice and roulette-wheels — are not self-evidently best modelled with probability measures.

EGOBILD2017When economists and econometricians — often uncritically and without arguments — simply assume that one can apply probability distributions from statistical theory on their own area of research, they are really skating on thin ice. If you cannot show that data satisfies all the conditions of the probabilistic nomological machine, then the statistical inferences made in mainstream economics lack sound foundations.

Statistical — and econometric — patterns should never be seen as anything other than possible clues to follow. Behind observable data, there are real structures and mechanisms operating, things that are — if we really want to understand, explain and (possibly) predict things in the real world — more important to get hold of than to simply correlate and regress observable variables.

Statistics cannot establish the truth value of a fact. Never has. Never will.

Allt — och lite till — du vill veta om kausalitet

12 Jul, 2018 at 18:00 | Posted in Theory of Science & Methodology | 1 Comment

KAUSALITETRolf Sandahls och Gustav Jakob Peterssons Kausalitet: i filosofi, politik och utvärdering är en synnerligen välskriven och läsvärd genomgång av de mest inflytelserika teorierna om kausalitet som används inom vetenskapen idag.

Tag och läs!

I den positivistiska (hypotetisk-deduktiva, deduktiv-nomologiska) förklaringsmodellen avser man med förklaring en underordning eller härledning av specifika fenomen ur universella lagbundenheter. Att förklara en företeelse (explanandum) är detsamma som att deducera fram en beskrivning av den från en uppsättning premisser och universella lagar av typen ”Om A, så B” (explanans). Att förklara innebär helt enkelt att kunna inordna något under en bestämd lagmässighet och ansatsen kallas därför också ibland ”covering law-modellen”. Men teorierna ska inte användas till att förklara specifika enskilda fenomen utan för att förklara de universella lagbundenheterna som ingår i en hypotetisk-deduktiv förklaring. Den positivistiska förklaringsmodellen finns också i en svagare variant. Det är den probabilistiska förklaringsvarianten, enligt vilken att förklara i princip innebär att visa att sannolikheten för en händelse B är mycket stor om händelse A inträffar. I samhällsvetenskaper dominerar denna variant. Ur metodologisk synpunkt gör denna probabilistiska relativisering av den positivistiska förklaringsansatsen ingen större skillnad.

Den ursprungliga tanken bakom den positivistiska förklaringsmodellen var att den skulle (1) ge ett fullständigt klargörande av vad en förklaring är och visa att en förklaring som inte uppfyllde dess krav i själva verket var en pseudoförklaring, (2) ge en metod för testning av förklaringar, och (3) visa att förklaringar i enlighet med modellen var vetenskapens mål. Man kan uppenbarligen på goda grunder ifrågasätta alla anspråken.

En viktig anledning till att denna modell fått sånt genomslag i vetenskapen är att den gav sken av att kunna förklara saker utan att behöva använda ”metafysiska” kausalbegrepp. Många vetenskapsmän ser kausalitet som ett problematiskt begrepp, som man helst ska undvika att använda. Det ska räcka med enkla, observerbara storheter. Problemet är bara att angivandet av dessa storheter och deras eventuella korrelationer inte förklarar något alls. Att fackföreningsrepresentanter ofta uppträder i grå kavajer och arbetsgivarrepresentanter i kritstrecksrandiga kostymer förklarar inte varför ungdomsarbetslösheten i Sverige är så hög idag. Vad som saknas i dessa ”förklaringar” är den nödvändiga adekvans, relevans och det kausala djup varförutan vetenskap riskerar att bli tom science fiction och modellek för lekens egen skull.

Många samhällsvetare tycks vara övertygade om att forskning för att räknas som vetenskap måste tillämpa någon variant av hypotetisk-deduktiv metod. Ur verklighetens komplicerade vimmel av fakta och händelser ska man vaska fram några gemensamma lagbundna korrelationer som kan fungera som förklaringar. Inom delar av samhällsvetenskapen har denna strävan att kunna reducera förklaringar av de samhälleliga fenomen till några få generella principer eller lagar varit en viktig drivkraft. Med hjälp av några få generella antaganden vill man förklara vad hela det makrofenomen som vi kallar ett samhälle utgör. Tyvärr ger man inga riktigt hållbara argument för varför det faktum att en teori kan förklara olika fenomen på ett enhetligt sätt skulle vara ett avgörande skäl för att acceptera eller föredra den. Enhetlighet och adekvans är inte liktydigt.

When I’m 104

12 Jul, 2018 at 15:34 | Posted in Varia | 3 Comments

[h/t Jeanette Meyer]

When I’m 64

12 Jul, 2018 at 15:29 | Posted in Varia | 1 Comment


Hard and soft science — a flawed dichotomy

11 Jul, 2018 at 19:08 | Posted in Theory of Science & Methodology | 1 Comment

The distinctions between hard and soft sciences are part of our culture … But the important distinction is really not between the hard and the soft sciences. Rather, it is between the hard and the easy sciences. Easy-to-do science is what those in physics, chemistry, geology, and some other fields do. Hard-to-do science is what the social scientists do and, in particular, it is what we educational researchers do. In my estimation, we have the hardest-to-do science of them all! We do our science under conditions that physical scientists find intolerable. We face particular problems and must deal with local conditions that limit generalizations and theory building-problems that are different from those faced by the easier-to-do sciences …

Context-MAtters_Blog_Chip_180321_093400Huge context effects cause scientists great trouble in trying to understand school life … A science that must always be sure the myriad particulars are well understood is harder to build than a science that can focus on the regularities of nature across contexts …

Doing science and implementing scientific findings are so difficult in education because humans in schools are embedded in complex and changing networks of social interaction. The participants in those networks have variable power to affect each other from day to day, and the ordinary events of life (a sick child, a messy divorce, a passionate love affair, migraine headaches, hot flashes, a birthday party, alcohol abuse, a new principal, a new child in the classroom, rain that keeps the children from a recess outside the school building) all affect doing science in school settings by limiting the generalizability of educational research findings. Compared to designing bridges and circuits or splitting either atoms or genes, the science to help change schools and classrooms is harder to do because context cannot be controlled.

David Berliner


When applying deductivist thinking to economics, mainstream economists set up their easy-to-do  ‘as if’ models based on a set of tight axiomatic assumptions from which consistent and precise inferences are made. The beauty of this procedure is, of course, that if the axiomatic premises are true, the conclusions necessarily follow. The snag is that if the models are to be real-world relevant, we also have to argue that their precision and rigour still holds when they are applied to real-world situations. They often do not, and one of the main reasons for that is that context matters. When addressing real-world systems, the idealizations and abstractions necessary for the deductivist machinery to work simply do not hold.

If the real world is fuzzy, vague and indeterminate, then why should our models build upon a desire to describe it as precise and predictable? The logic of idealization is a marvellous tool in an easy-to-do science like physics, but a poor guide for action in real-world systems in which concepts and entities are without clear boundaries and continually interact and overlap.

Der Wind hat sich gedreht im Lande

11 Jul, 2018 at 14:29 | Posted in Varia | 4 Comments


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