Geoffrey Harcourt (1931-2021)

7 Dec, 2021 at 20:57 | Posted in Economics | 1 Comment

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A great scholar has passed away.

R.I.P.

Monnaie d’hier, monnaie de demain

5 Dec, 2021 at 10:48 | Posted in Economics | Comments Off on Monnaie d’hier, monnaie de demain

Bitcoin consumes 'more electricity than Argentina' - BBC NewsEnfin, pour ce qui est de la dangereuse privatisation de la monnaie qui adviendrait avec les cryptomonnaies, demandons-nous si la monnaie légale est le bien public qu’elle prétend être. C’est à son accaparement par le secteur bancaire et financier qu’entendent répondre des innovations financières comme les cryptomonnaies ou les monnaies complémentaires, aussi différents soient leurs projets sous-jacents.

Alors, plutôt que de reprocher aux crypto-actifs ce qui peut l’être tout autant à la monnaie légale, interrogeons-nous sur les raisons de leur développement, sur le projet de société qui les sous-tendent. De quelle société voulons-nous donc ? Quelles monnaies seraient propres à porter les transformations dont nous avons besoin ? Si la cryptomonnaie n’est pas forcément la monnaie de la sociéte de demain, la monnaie bancaire est celle de la société d’hier.

Jézabel Couppey-Soubeyran / Le Monde

Does it take a theory to beat a theory?

4 Dec, 2021 at 15:55 | Posted in Economics | 4 Comments

George Stigler quote: Theories are not rejected by cirsumstantial evidence: it  takes a...If the substantive theories and methods you use, given their ontological presuppositions, are appropriate to the nature of those aspects of social reality you are addressing, then fine. The only methodological ‘dictum’ I support is tailor methods to the nature of the phenomena you are addressing. Certainly, I would offer no ontological critique. Specifically, if the five sets of properties you list do characterise the phenomena you address, and your methods do not carry ontological presuppositions that are so different as to be contradictory (for example that require of the phenomena that you are addressing that they take the form of isolated atoms [causal factors that have the same independent, invariable effect no matter what the context or anything else that is going on]) then fine. It remains the case though that almost all methods of mathematical modelling employed in modern economics (not matter how simple of complex, linear or non-linear, stochastic or dynamic, simulative, predictionist or otherwise) do carry such presuppositions. Where/if bits of reality so conform to a system of isolated atoms then limited use of such methods might be fine. Of course, you suggest, indeed, that this is your approach. The mainstream of modern economics (and let us face it the only coherent account of the modern mainstream is a reliance, indeed dogmatic insistence on, methods of mathematical modelling) determines its methods a prior independently of the natures of the material that are to be addressed. That’s different. And it’s no wonder that the project results in little insight …

I believe you have often explicitly written that “it takes a theory to beat a theory”, and you see that as a challenge to people like Lars and myself to engage in substantive economics. I do not think it is. Yes, it takes a theory to beat a theory, but the theories being contrasted must be comparable. The continuing problems of modern economics do not reduce to this particular mathematical model or that particular model but the whole modelling emphasis. The commonality of all such modelling is the widespread commitment to deductivist forms of reasoning/explanation that, to be relevant, presupposes a social reality composed largely of closed systems of isolated atoms. This is the ontological theory of the modern mainstream whether recognised or not. It is this theory to which we must apply your dictum ‘it takes a theory to beat a theory’. And that, or so I claim and argue, is precisely what critical realism (CR) does. Thereafter very many (often competing) theories of substantive phenomena can be constructed all of which draw on CR (just as many substantive economic modelling exercises abound). If CR is correct then almost all modelling exercises will be irrelevant (so CR is efficacious), whereas those underpinned by CR will be merely more of less correct or false. It is not up to Lars and myself to produce these accounts (even though I have produced some). I would claim that figures as diverse as Marx, Keynes, Veblen, and Hayek have all in their own ways both criticised deductivism (as vulgar economics, pseudo-science, neoclassical economics and scientism, respectively) and its ontology, and produced (very different) substantive accounts consistent (I argue) with CR.

This of course feeds into the reason that Lars, and also myself, are almost always negative in referring to the mainstream. From the perspective we adopt, it is simply a huge error to adopt unthinkingly – and especially to insist that we all do so — methods that carry ontological presuppositions that rarely if ever hold in the social realm. So, a largely critical orientation to the mainstream (as here understood) is surely warranted. But I myself can be and am very positive towards anything more relevant.

Tony Lawson / RWER Blog

Poor economics

3 Dec, 2021 at 10:12 | Posted in Economics | Comments Off on Poor economics

Few volumes in contemporary economics have been more lauded, and have summarised a zeitgeist, as much as Abhijit Banerjee and Esther Duflo’s Poor Economics …

buThe implicit premise of the book is that interventions that work in one place can be expected to work in another. This presumes not only that the results of such “micro” interventions are substantially independent of the “macro” context, but also that a focus on such interventions, as opposed to those which reshape that context, is sufficient to address poverty. These premises of “separability” and “sufficiency”, although non-trivial, go largely undiscussed by the authors. The causal relations at work in relation to individuals or households cannot be understood in atomic isolation …

Not surprisingly, one consequence of the approach to development economics championed by the authors is that the questions asked by the discipline have become much smaller. The authors’ position appears to be that this is quite all right, since the small questions are in fact large in importance. It is not easy to accept this, however. The larger questions once asked within the discipline … have been pushed to the background in favour of such questions as whether bed-nets dipped in insecticide should be distributed free of charge or not, or whether two schoolteachers in the classroom are much better than one …

One may argue, in fact, that the style of metropolitan development economics celebrated in this book leads not so much to increasing rigour as to rigor mortis, by severely limiting the questions that can be asked and shoring up a practical philosophy that is quiescent in relation to many important questions that cannot readily be analysed using the authors’ favoured method. These include questions related to the structure and dynamics of markets, governmental institutions, macroeconomic policies, the workings of social classes, castes, and networks, and so forth. Although such questions can only be approached through other methods, they are not the less important for that.

Sanjay Reddy

Most ‘randomistas’ — like Duflo and Banerjee — argue that since random or as-if random assignment in natural experiments obviates the need for controlling potential confounders, this kind of “simple and transparent” design-based research method is preferable to more traditional multivariate regression analysis where the controlling only comes in ex post via statistical modelling.

The point of making a randomized experiment is often said to be that it ‘ensures’ that any correlation between a supposed cause and effect indicates a causal relation. This is believed to hold since randomization (allegedly) ensures that a supposed causal variable does not correlate with other variables that may influence the effect.

The problem with that simplistic view on randomization is that the claims made are exaggerated and sometimes even false:

• Even if you manage to do the assignment to treatment and control groups ideally random, the sample selection certainly is — except in extremely rare cases — not random. Even if we make a proper randomized assignment, if we apply the results to a biased sample, there is always the risk that the experimental findings will not apply. What works ‘there,’ does not work ‘here.’ Randomization hence does not ‘guarantee ‘ or ‘ensure’ making the right causal claim. Although randomization may help us rule out certain possible causal claims, randomization per se does not guarantee anything!

• Even if both sampling and assignment are made in an ideal random way, performing standard randomized experiments only give you averages. The problem here is that although we may get an estimate of the ‘true’ average causal effect, this may ‘mask’ important heterogeneous effects of a causal nature. Although we get the right answer of the average causal effect being 0, those who are ‘treated’  may have causal effects equal to -100 and those ‘not treated’ may have causal effects equal to 100. Contemplating being treated or not, most people would probably be interested in knowing about this underlying heterogeneity and would not consider the average effect particularly enlightening.

• There is almost always a trade-off between bias and precision. In real-world settings, a little bias often does not overtrump greater precision. And — most importantly — in case we have a population with sizeable heterogeneity, the average treatment effect of the sample may differ substantially from the average treatment effect in the population. If so, the value of any extrapolating inferences made from trial samples to other populations is highly questionable.

• Since most real-world experiments and trials build on performing a single randomization, what would happen if you kept on randomizing forever, does not help you to ‘ensure’ or ‘guarantee’ that you do not make false causal conclusions in the one particular randomized experiment you actually do perform. It is indeed difficult to see why thinking about what you know you will never do, would make you happy about what you actually do.

• And then there is also the problem that ‘Nature’ may not always supply us with the random experiments we are most interested in. If we are interested in X, why should we study Y only because design dictates that? Method should never be prioritized over substance!

Randomization is not a panacea. It is not the best method for all questions and circumstances. Proponents of randomization make claims about its ability to deliver causal knowledge that is simply wrong. There are good reasons to be sceptical of the now popular — and ill-informed — view that randomization is the only valid and the best method on the market. It is not.

‘Vår ekonomi’ — nationalekonomisk lärobok med stora brister

1 Dec, 2021 at 17:25 | Posted in Economics | 2 Comments

Varje höst håller your truly sedan fler år tillbaka en introduktionskurs i nationalekonomi för blivande gymnasielärare. Förutom några av mina egna böcker, står även Klas Eklunds Vår ekonomi på litteraturlistan.

Vår ekonomi - 9789144140858 | StudentlitteraturVår ekonomi kom år 2020 ut i sin femtonde upplaga. Imponerande och i sig ett bevis på bokens många förtjänster, inte minst de pedagogiska.

Men tyvärr har boken också — fortfarande — några riktigt stora brister. Framför allt när det gäller metodologiska och monetära frågor.

Nationalekonomi är en vetenskap som i hög grad bygger på användandet av modeller. Eklund presenterar modellanvändandet som ”en sorts förenklade beskrivningar av verkligheten” med vars hjälp ekonomen kan ”göra tanke- och räkneexperiment och testa sina hypoteser”. Om dessa modeller ska fungera och ge överblickbara resultat

måste de göras enklare än den komplicerade verkligheten … Ekonomerna brukar följaktligen, då de konstruerar sina modeller, införa en rad förenklande antaganden för att göra modellerna så klara och entydiga som möjligt … Självklart är sådana antaganden orealistiska … Ändå är ett visst mått av modellbyggeri nödvändigt … Verklighetens komplexitet och svårigheten att utföra kontrollerade experiment gör det därmed ofrånkomligt att den som vill sätta sig in i samhällsekonomin måste vara beredd att lära sig ett visst ’teoretiskt’ och ’abstrakt’ tänkande.

Den enkla utbuds- och efterfrågemodellen har i sin mer sofistikerade form

utgjort kärnan i den nationalekonomiska teorin under hela det senaste århundradet. Orsaken är inte att den exakt skulle avspegla verkligheten, utan att den på ett enkelt och slagkraftigt sätt leder fram till klara slutsatser, som på en rad olika sätt kan tillämpas vid analysen av ekonomiska problem.

Eklund medger att verkligheten inte ser ut som de ekonomiska modellerna, men att dessa har ett berättigande som ett slags referens- och utgångspunkt utifrån vilken den ekonomiska analysen kan visa ”vilka hinder som ligger i vägen för människor och företag att följa de grundläggande beslutsregler” som beskrivs i dessa modeller. Modellerna ska ses som ”analytiska hjälpmedel, vilka hjälper till att abstrahera fram väsentliga grunddrag i hur olika ekonomiska mekanismer fungerar”.

Redan i inledningskapitlen av boken introduceras den gängse mainstreamteorins utbuds- och erfterfrågemodell, där ett av kärnantagandena är att företagens kortsiktiga utbudskurva utgörs av den del av marginalkostnadskurvan som överstiger den genomsnittliga rörliga kostnaden. Hur det fortfarande är möjligt år 2020 påstå något sådant som vet redan sedan Richard Lesters forskning på 1930-talet har noll med verkliga företags utbudskurvor att göra är hårresande. Faktaresistensen är monumental och ur ett vetenskapligt perspektiv sett fullständigt obegriplig. I vilken annan vetenskap som helst utanför nationalekonomin hade en lärobok som så flagrant presenterar modeller och teorier utan den minsta förankring i verkligheten snabbt försvunnit ur kurskatalogerna.

Det är intressant hur Eklund ofta i förbigående nämner en rad problem men sedan snabbt går förbi dem. Om nu inte modellen avspeglar verkligheten, hur kan vi då ha glädje av den? Är ”enkelhet” och förmågan att leda till ”klara slutsatser” den mest relevanta aspekten att lägga på modellen? Hur kan vi vara säkra på att det är de ”väsentliga” grunddragen som modellen abstraherar fram? Och så vidare. Det finns något förrädiskt i denna undanglidande framställning, därför att den ger sken av att kvalificera bruket av modeller inom nationalekonomin, men egentligen vid närmre analys inte alls gör det. Problemen omnämns och sedan går man glatt vidare som om de inte fanns.

Tyvärr är det inte mycket bättre ställt med Eklunds framställning av de penningteoretiska frågorna.

Bilden Eklund ger av bankerna är att de i stort sett fungerar som “finansiella intermediärer” i en ekonomi där penningmängden bestäms exogent av centralbanken.

Så här resonerade mainstream (neoklassiska) ekonomer i stort sett fram till 1980-talet. Men mycket har hänt på penningteorins område sedan dess. Inte minst den nya så kallade Modern Monetary Theory (MMT) har sedan dess gjort upp med mycket av de gamla förlegade och helt verklighetsfrämmande inslagen i den gängse neoklassiska monetära teorin. Idag vet vi att pengar i moderna kreditekonomier i grunden är en “endogen” företeelse och väsentligen något som centralbanken inte alls kan styra på det sätt man trodde förr. Den gamla monetaristiska fixidén om pengar som något exogent givet är stendöd.

På sätt och vis är det extra märkligt att detta är en så påtagligt svag del i Eklunds bok, mot bakgrund av att han i flera år arbetat som centralt placerad bankekonom och borde veta bättre. Men kanske är det som John Kenneth Galbraith en gång utryckte det, att “studiet av pengar, mer än någon annan del av nationalekonomin, är ett studium där komplexitet används för att dölja eller undvika sanning, snarare än att avslöja den” …

Dessa brister visar också att även om Eklund på ett pedagogiskt och lättillgängligt sätt lyckas presentera grundstenarna i det neoklassiska modellbygget, så så saknas boken igenom en kritisk diskussion om hur dessa ‘Walt Disney’ modeller förhåller sig till verkligheten och hur de eventuellt skulle kunna hjälpa oss förstå nutida ekonomier. Ofta blir framställningen lite av logiken “anta att människor är gröna och kommer från Mars”. Visst kan vi göra det, men vad är vitsen? Förenklande antaganden är en sak, men rena fantasier hör inte hemma i en vetenskap. Precis som alla andra modeller och teorier måste de av Eklund presenterde mainstreammodellerna konfronteras med empiriska observationer för att vi ska kunna avgöra om de är adekvata representationer av verkligheten. Nästan unantagslöst visar det sig då att den modellmetodologi och monetära teori Eklund bygger sin framställning på fallerar påtagligt.

Mainstream economics — a harmful fantasy

1 Dec, 2021 at 16:25 | Posted in Economics | Comments Off on Mainstream economics — a harmful fantasy

The New Economics: A Manifesto: Keen, Steve: 9781509545285: Public Policy:  Amazon CanadaAnyone who accepts the Neoclassical definition of ‘rational’ has, to some significant degree, lost touch with reality. So, I was expecting an ‘irrational’ reaction from this young zealot to my talk …

He tried to engage me in further debate after the session, and shouted ‘But we have to make some simplifying assumptions!’ at me as I left the seminar room. My riposte, cast over my receding shoulder, was ‘Mate, you have to learn the difference between a simplifying assumption and a fantasy’.

Many mainstream economists working in the field of economic theory think that their task is to give us analytical truths. That is great — from a mathematical and formal logical point of view. In science, however, it is rather uninteresting and totally uninformative! The framework of the analysis is too narrow. Even if economic theory gives us ‘logical’ truths, that is not what we are looking for as scientists. We are interested in finding truths that give us new information and knowledge of the world in which we live.

Scientific theories are theories that ‘refer’ to the real-world, where axioms and definitions do not take us very far. To be of interest for an economist or social scientist that wants to understand, explain, or predict real-world phenomena, the pure theory has to be ‘interpreted’ — it has to be ‘applied’ theory. 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 unjustified 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.

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.

The nature of money

1 Dec, 2021 at 14:40 | Posted in Economics | 3 Comments

Money is a component of the community’s accounting system, formed by way of allocating some kind of thing to a money position … In short, a community’s money is identifiable as that kind of thing which is everywhere enabled to serve as a general means of payment, the latter property being its nominal essence or function; and money’s nature or real essence is the set of rights and obligations (of participants of the monetary community) in virtue of which the money so formed is enabled and oriented to serving this function.

What is money? Why do we use money? - Market Business NewsOf course, an occupant of the money position will usually be sought that is regarded as appropriate in some sense. The point, though, is that once a kind of thing is in place, then whether it is appropriate in some relevant sense or not, a money is formed. What kind of item might be sought to occupy the position? Basically, one that is expected to result in a money that flows easily and continually throughout a community …

Money, in short, is constituted and operates in much the same sort of manner as any other social phenomenon qua positioned item and community component … And as with these other items, in the case of money too, the adequacy of any instance of it to serve its associated function will depend on the nature of the particular kind of thing used to form it, that occupies the relevant (in this case the money) position.

Tony Lawson

Rational expectations — the triumph of ideology over science

29 Nov, 2021 at 11:46 | Posted in Economics | 7 Comments

Senate Banking Subcommittee On Financial Institutions Hearing With Stiglitz For more than 20 years, economists were enthralled by so-called “rational expectations” models which assumed that all participants have the same (if not perfect) information and act perfectly rationally, that markets are perfectly efficient, that unemployment never exists (except when caused by greedy unions or government minimum wages), and where there is never any credit rationing.

That such models prevailed, especially in America’s graduate schools, despite evidence to the contrary, bears testimony to a triumph of ideology over science. Unfortunately, students of these graduate programmes now act as policymakers in many countries, and are trying to implement programmes based on the ideas that have come to be called market fundamentalism … Good science recognises its limitations, but the prophets of rational expectations have usually shown no such modesty.

Joseph Stiglitz

Those who want to build macroeconomics on microfoundations usually maintain that the only robust policies and institutions are those based on rational expectations and representative actors. As yours truly has tried to show in On the use and misuse of theories and models in economics there is really no support for this conviction at all. On the contrary. If we want to have anything of interest to say on real economies, financial crisis and the decisions and choices real people make, it is high time to place macroeconomic models building on representative actors and rational expectations microfoundations in the dustbin of pseudo-science.

For if this microfounded macroeconomics has nothing to say about the real world and the economic problems out there, why should we care about it? The final court of appeal for macroeconomic models is the real world, and as long as no convincing justification is put forward for how the inferential bridging de facto is made, macroeconomic modelbuilding is little more than hand-waving that give us a rather little warrant for making inductive inferences from models to real world target systems. If substantive questions about the real world are being posed, it is the formalistic-mathematical representations utilized to analyze them that have to match reality, not the other way around.

The real macroeconomic challenge is to accept uncertainty and still try to explain why economic transactions take place — instead of simply conjuring the problem away by assuming rational expectations and treating uncertainty as if it was possible to reduce it to stochastic risk. That is scientific cheating. And it has been going on for too long now.

The Sonnenschein-Mantel-Debreu Theorem

25 Nov, 2021 at 09:50 | Posted in Economics | Comments Off on The Sonnenschein-Mantel-Debreu Theorem

SMD theory means that assumptions guaranteeing good behavior at the microeconomic level do not carry over to the aggregate level or to qualitative features of the equilibrium. It has been difficult to make progress on the elaborations of general equilibrium theory that were put forth in Arrow and Hahn 1971 …

24958274Fifteen years after General Competitive Analysis, Arrow (1986) stated that the hypothesis of rationality had few implications at the aggregate level. Kirman (1989) held that general equilibrium theory could not generate falsifiable propositions, given that almost any set of data seemed consistent with the theory. These views are widely shared. Bliss (1993, 227) wrote that the “near emptiness of general equilibrium theory is a theorem of the theory.” Mas-Colell, Michael Whinston, and Jerry Green (1995) titled a section of their graduate microeconomics textbook “Anything Goes: The Sonnenschein-Mantel-Debreu Theorem.”

S. Abu Turab Rizvi

And so what? Why should we care about Sonnenschein-Mantel-Debreu?

Because  Sonnenschein-Mantel-Debreu ultimately explains why New Classical, Real Business Cycles, Dynamic Stochastic General Equilibrium (DSGE) and New ‘Keynesian’ microfounded macromodels are such bad substitutes for real macroeconomic analysis!

These models try to describe and analyze complex and heterogeneous real economies with a single rational-expectations-robot-imitation-representative-agent. That is, with something that has absolutely nothing to do with reality. And — worse still — something that is not even amenable to the kind of general equilibrium analysis that they are thought to give a foundation for, since Hugo Sonnenschein (1972),​ Rolf Mantel (1976) and Gerard Debreu (1974) unequivocally showed that there did not exist any condition by which assumptions on individuals would guarantee neither stability nor uniqueness of the equilibrium​ solution. A century and a half after Léon Walras founded neoclassical general equilibrium theory, modern mainstream economics hasn’t been able to show that markets move economies to equilibria. This if anything shows that the whole Bourbaki-Debreu project of axiomatizing​ economics was nothing but a delusion.

You enquire whether or not Walras was supposing that exchanges actually take place at the prices originally proposed when the prices are not equilibrium prices. The footnote which you quote convinces me that he assuredly supposed that they did not take place except at the equilibrium prices … All the same, I shall hope to convince you some day that Walras’ theory and all the others along those lines are little better than nonsense!

Letter from J. M. Keynes to N. Georgescu-Roegen, December 9, 1934

Opting for cloned representative agents that are all identical is of course not a real solution to the fallacy of composition that the Sonnenschein-Mantel-Debreu theorem points to. Representative agent models are — as I have argued at length in my On the use and misuse of theories and models in mainstream economics — rather an evasion whereby issues of distribution, coordination, heterogeneity are swept under the rug.

Of course, most macroeconomists know that to use a representative agent is a flagrantly illegitimate method of ignoring real aggregation issues. They keep on with their business, nevertheless, just because it significantly simplifies what they are doing. It reminds not so little of the drunkard who has lost his keys in some dark place and deliberately chooses to look for them under a neighbouring street light just because it is easier to see there …

Economy Studies: A Guide to Rethinking Economics Education

23 Nov, 2021 at 18:04 | Posted in Economics | Comments Off on Economy Studies: A Guide to Rethinking Economics Education

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La théorie du ruissellement 

20 Nov, 2021 at 13:35 | Posted in Economics | Comments Off on La théorie du ruissellement 

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Study proves trickle-down didn't trickle | PoliticsNC

What killed macroeconomics?

19 Nov, 2021 at 16:44 | Posted in Economics | 17 Comments

The COVID-19 pandemic impelled governments to fall back on “fiscal Keynesianism,” because there was no way that just increasing the quantity of money could lead to the reopening of businesses that were prevented by law from doing so. Fiscal Keynesianism in the big lockdown meant issuing Treasury payments to people prevented from working.risk vs uncertainty

But now that the economy has reopened, the practical rationale for monetary and fiscal expansion has disappeared. Mainstream financial commentators believe the economy will bounce back as if nothing had happened. After all, economies fall into foxholes no more often than individuals normally do. So, the time has come to tighten both monetary and fiscal policy, because continued expansion of either or both will lead only to a “surge in inflation.” We can all breathe a sigh of relief; the trauma is over, and normal life without unemployment will resume.

Monetary policy works in theory but not in practice; fiscal policy works in practice but not in theory. Fiscal Keynesianism is still a policy in search of a theory. Acemoglu, Laibson, and List supply a piece of the missing theory when they note that shocks are “hard to predict.” Keynes would have said they are impossible to predict, which is why he rejected the standard view that economies are cyclically stable in the absence of shocks (which is as useless as saying that leaves don’t flutter in the absence of wind).

The supply and demand models that first-year economics students are taught can illuminate the equilibrium path of the hairdressing industry but not of the economy as a whole. Macroeconomics is the child of uncertainty. Unless economists recognize the existence of inescapable uncertainty, there can be no macroeconomic theory, only prudential responses to emergencies.

Robert Skidelsky

Modern macroeconomics — Dynamic Stochastic General Equilibrium, New Synthesis, New Classical and New ‘Keynesian’ — still follows an ‘as if’ logic of denying the existence of genuine uncertainty and treat variables as if drawn from a known ‘data-generating process’ with known probability distribution that unfolds over time and on which we therefore have access to heaps of historical time-series. If we do not assume that we know the ‘data-generating process’ — if we do not have the ‘true’ model — the whole edifice collapses. And of course, it has to. Who really honestly believes that we have access to this mythical Holy Grail, the data-generating process?

Modern macroeconomics obviously did not anticipate the enormity of the problems that unregulated ‘efficient’ financial markets created. Why? Because it builds on the myth of us knowing the ‘data-generating process’ and that we can describe the variables of our evolving economies as drawn from an urn containing stochastic probability functions with known means and variances.

This is like saying that you are going on a holiday-trip and that you know that the chance the weather being sunny is at least 30​% and that this is enough for you to decide on bringing along your sunglasses or not. You are supposed to be able to calculate the expected utility based on the given probability of sunny weather and make a simple decision of either-or. Uncertainty is reduced to risk.

But as Keynes convincingly argued in his monumental Treatise on Probability (1921), this is not always possible. Often we simply do not know. According to one model the chance of sunny weather is perhaps somewhere around 10% and according to another — equally good — model the chance is perhaps somewhere around 40%. We cannot put exact numbers on these assessments. We cannot calculate means and variances. There are no given probability distributions that we can appeal to.

In the end,​ this is what it all boils down to. We all know that many activities, relations, processes and events are of the Keynesian uncertainty-type. The data do not unequivocally single out one decision as the only ‘rational’ one. Neither the economist, nor the deciding individual, can fully pre-specify how people will decide when facing uncertainties and ambiguities that are ontological facts of the way the world works.

Some macroeconomists, however, still want to be able to use their hammer. So they decide to pretend that the world looks like a nail, and pretend that uncertainty can be reduced to risk. So they construct their mathematical models on that assumption. The result: financial crises and economic havoc.

How much better — how much bigger chance that we do not lull us into the comforting thought that we know everything and that everything is measurable and we have everything under control — if instead, we could just admit that we often simply do not know, and that we have to live with that uncertainty as well as it goes.

Fooling people into believing that one can cope with an unknown economic future in a way similar to playing at the roulette wheels, is a sure recipe for only one thing — economic catastrophe.

More than economists

18 Nov, 2021 at 16:17 | Posted in Economics | 2 Comments

Veblen, Keynes, and Hirschman were more than economists because they practiced their economics from a standpoint outside the profession, using it to criticize not only the assumption of rational self-interest, but also the consequences of economists’ indifference to “preferences.” Veblen’s standpoint was explicitly religious; he was still of a believing generation. Keynes, too, was an ethicist. G.E. Moore’s Principia Ethica remained what he called his “religion under the surface.” Hirschman wanted a “moral social science” that would be continually sensitive to the ethical content of its analysis …

Prof. Lord Robert Skidelsky (C. 1953-58), OB of the Month, July 2012 - Old  Brightonians - The Alumni of Brighton CollegeThese three economists’ frequently mocking style was their way of establishing their distance from their profession. Their irony was not ornamental but actually shaped the substance of their arguments. This style limited their impact on economics, but made them highly influential outside it, because critics of economics sensed something transgressive about them.

Systematic thinkers close a subject, leaving their followers with “normal” science to fill up the learned journals. Fertile ones open up their disciplines to critical scrutiny, for which they rarely get credit.

Robert Skidelsky

Rethinking economics

15 Nov, 2021 at 17:53 | Posted in Economics | 7 Comments

marquesThe incorporation of new information makes sense only if the future is to be similar to the past. Any kind of empirical test, whatever form it adopts, will not make sense, however, if the world is uncertain because in such a world induction does not work. Past experience is not a useful guide to guess the future in these conditions (it only serves when the future, somehow, is already implicit in the present) … I believe the only way to use past experience is to assume that the world is repetitive. In a non-repetitive world in which relevant novelties unexpectedly arise testing is irrelevant …

Conceiving economic processes like sequences of events in which uncertainty reigns, where consequently there are “no laws”, nor “invariants” or “mechanisms” to discover, the kind of learning that experiments or last experience provide is of no use for the future, because it eliminates innovation and creativity and does not take into account the arboreal character and the open-ended nature of the economic process … However, as said before, we can gather precise information, restricted in space and time (data). But, what is the purpose of obtaining this sort of information if uncertainty about future events prevails? … The problem is that taking uncertainty seriously puts in question the relevance the data obtained by means of testing or experimentation has for future situations.

Marqués’ book is a serious challenge to much of mainstream economic thinking and its methodological and philosophical underpinnings. A must-read for anyone interested in the foundations of economic theory, showing how far-reaching the effects of taking Keynes’ concept of genuine uncertainty really are.

treatprobScience according to Keynes should help us penetrate to “the true process of causation lying behind current events” and disclose “the causal forces behind the apparent facts.” Models can never be more than a starting point in that endeavour. He further argued that it was inadmissible to project history on the future. Consequently, we cannot presuppose that what has worked before, will continue to do so in the future. That statistical models can get hold of correlations between different ‘variables’ is not enough. If they cannot help us get at the causal structure that generated the data, they are not really ‘identified.’

How strange then that economics textbooks do not even touch upon these aspects of scientific methodology that seems to be so fundamental and important for anyone trying to understand how we learn and orient ourselves in an uncertain world! An educated guess on why this is a fact would be that Keynes’ concepts are not possible to squeeze into a single calculable numerical ‘probability.’ In the quest for quantities one puts a blind eye to qualities and looks the other way and hopempeople will forget about Keynes’ fundamental insight

Robert Lucas once wrote — in Studies in Business-Cycle Theory — that “in cases of uncertainty, economic reasoning will be of no value.”  Now, if that was true, it would put us in a tough dilemma. If we have to consider — as Lucas — uncertainty incompatible with economics being a science, and we actually know for sure that there are several and deeply important situations in real-world contexts where we — both epistemologically and ontologically — face genuine uncertainty, well, then we actually would have to choose between reality and science.

That can’t be right. We all know we do not know very much about the future. We all know the future harbours lots of unknown unknowns. Those are ontological facts we just have to accept — and still go for both reality and science, in developing a realist and relevant economic science.

Making sense of economics

9 Nov, 2021 at 10:31 | Posted in Economics | Comments Off on Making sense of economics

The Assumptions Economists Make eBook : Schlefer, Jonathan: Kindle Store -  Amazon.comRobert Lucas, one of the most creative model-builders, tells a story about his undergraduate encounter with Gregor Mendel’s model of genetic inheritance. He liked the Mendelian model—“you could work out predictions that would surprise you”—though not the lab work breeding fruit flies to test it. (Economists are not big on mucking around in the real world.) Over the weekend, he enjoyed writing a paper comparing the model’s predictions with the class’s experimental results. When a friend returned from a weekend away without having written the required paper, Lucas agreed to let the friend borrow from his. The friend remarked that Lucas had forgotten to discuss how “crossing-over” could explain the substantial discrepancies between the model and experimental results. “Crossing-over is b—s—,” Lucas told his friend, a “label for our ignorance.” He kept his paper’s focus on the unadorned Mendelian model, and added a section arguing that experimental errors could explain the discrepancies. His friend instead appended a section on crossing-over. His friend got an A. Lucas got a C-minus, with a comment: “This is a good report, but you forgot about crossing-over.” Crossing-over is actually a fact; it occurs when a portion of one parent gene is incorporated in the other parent gene. But Lucas’s anecdote brilliantly illustrates the powerful temptation to model-builders—across the ideological spectrum—of ignoring inconvenient facts that don’t fit their models.

Economics may be an informative tool for research. But if its practitioners do not investigate and make an effort of providing a justification for the credibility of the assumptions on which they erect their building, it will not fulfil its task. There is a gap between its aspirations and its accomplishments, and without more supportive evidence to substantiate its claims, critics will continue to consider its ultimate arguments as a mixture of rather unhelpful metaphors and metaphysics.

The marginal return on its ever higher technical sophistication in no way makes up for the lack of serious under-labouring of its deeper philosophical and methodological foundations.

A rigorous application of economic methods really presupposes that the phenomena of our real-world economies are ruled by stable causal relations. Unfortunately, real-world social systems are usually not governed by stable causal relations and mechanisms. The kinds of ‘laws’ and relations that economics has established, are laws and relations about entities in models that usually presuppose causal mechanisms being invariant, atomistic and additive. But — when causal mechanisms operate in the real world they only do it in ever-changing and unstable combinations where the whole is more than a mechanical sum of parts. If economic regularities obtain they do it as a rule only because we engineered them for that purpose. Outside man-made ‘nomological machines’ they are rare, or even non-existent.

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