Är hög statsskuld — verkligen — problemet?

17 Apr, 2021 at 10:49 | Posted in Economics | Leave a comment

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När depressionen drabbade 1930-talets industrivärld visade sig den ekonomiska teorin inte vara till någon större hjälp att komma ur situationen. Den engelske nationalekonomen John Maynard Keynes såg behovet av att utveckla en ny teori som på bröt mot den etablerade sanningen. I The General Theory of Employment, Interest and Money (1936) presenterade han sitt alternativ.

Vad som behövs nu är upplyst handling grundad på relevant och realistisk ekonomisk teori av det slag som Keynes står för.

Den överhängande faran är att vi inte får fart på konsumtion och kreditgivning. Förtroende och effektiv efterfrågan måste återupprättas.

Ett av de grundläggande feltänken i dagens diskussion om statsskuld och budgetunderskott är att man inte skiljer på skuld och skuld. Även om det på makroplanet av nödvändighet är så att skulder och tillgångar balanserar varandra, så är det inte oväsentligt vem som har tillgångarna och vem som har skulderna.

Länge har man varit motvillig att öka de offentliga skulderna eftersom ekonomiska kriser i mångt och mycket fortfarande uppfattas som förorsakad av för mycket skulder. Men det är här fördelningen av skulder kommer in. Om staten i ett läge med risk för skulddeflation och likviditetsfällor ‘lånar’ pengar för att bygga ut järnvägar, skola och hälsovård, så är ju de samhälleliga kostnaderna för detta minimala eftersom resurserna annars legat oanvända. När hjulen väl börjar snurra kan både de offentliga och de privata skulderna betalas av. Och även om detta inte skulle uppnås fullt ut så förbättras det ekonomiska läget därför att låntagare med dåliga balansräkningar ersätts med de som har bättre.

I stället för att ”värna om statsfinanserna” bör man se till att värna om samhällets framtid. Problemet med en statsskuld i en situation med nästintill negativa räntor inte är att den är för stor, utan för liten.

Econometrics — formal modelling that has failed miserably

16 Apr, 2021 at 14:23 | Posted in Statistics & Econometrics | Leave a comment

An ongoing concern is that excessive focus on formal modeling and statistics can lead to neglect of practical issues and to overconfidence in formal results … Analysis interpretation depends on contextual judgments about how reality is to be mapped onto the model, and how the formal analysis results are to be mapped back into reality. But overconfidence in formal outputs is only to be expected when much labor has gone into deductive reasoning. First, there is a need to feel the labor was justified, and one way to do so is to believe the formal deduction produced important conclusions. Second, there seems to be a pervasive human aversion to uncertainty, and one way to reduce feelings of uncertainty is to invest faith in deduction as a sufficient guide to truth. Unfortunately, such faith is as logically unjustified as any religious creed, since a deduction produces certainty about the real world only when its assumptions about the real world are certain …

What should we do with econometrics? | LARS P. SYLLUnfortunately, assumption uncertainty reduces the status of deductions and statistical computations to exercises in hypothetical reasoning – they provide best-case scenarios of what we could infer from specific data (which are assumed to have only specific, known problems). Even more unfortunate, however, is that this exercise is deceptive to the extent it ignores or misrepresents available information, and makes hidden assumptions that are unsupported by data …

Despite assumption uncertainties, modelers often express only the uncertainties derived within their modeling assumptions, sometimes to disastrous consequences. Econometrics supplies dramatic cautionary examples in which complex modeling has failed miserably in important applications …

Much time should be spent explaining the full details of what statistical models and algorithms actually assume, emphasizing the extremely hypothetical nature of their outputs relative to a complete (and thus nonidentified) causal model for the data-generating mechanisms. Teaching should especially emphasize how formal ‘‘causal inferences’’ are being driven by the assumptions of randomized (‘‘ignorable’’) system inputs and random observational selection that justify the ‘‘causal’’ label.

Sander Greenland

Yes, indeed, econometrics fails miserably over and over again. One reason why it does — besides those discussed by Greenland — is that the error term in the regression models used are thought of as representing the effect of the variables that were omitted from the models. The error term is somehow thought to be a ‘cover-all’ term representing omitted content in the model and necessary to include to ‘save’ the assumed deterministic relation between the other random variables included in the model. Error terms are usually assumed to be orthogonal (uncorrelated) to the explanatory variables. But since they are unobservable, they are also impossible to empirically test. And without justification of the orthogonality assumption, there is as a rule nothing to ensure identifiability.

Without sound justification of the assumptions made, the formal models used in econometric analysis is of questionable value. Failing to take unmodelled uncertainty (not stochastic risk) into serious consideration has made most econonometricians ridiculously overconfident in the reach of the (causal) inferences they make.

Bernard Madoff — la plus grande pyramide de Ponzi de l’histoire

16 Apr, 2021 at 10:59 | Posted in Economics | Leave a comment

L’auteur du plus grand scandale financier du XXe siècle s’est éteint, mercredi 14 avril, à 82 ans. Il était parvenu à extorquer des fortunes à ses clients tout en jouant sur la pusillanimité des régulateurs.

A Bernie Madoff Type Ponzi Scheme Right Here in Orange County | by Ronald  Larson | LinkedInBernard Madoff avait développé à partir des années 1960 une société de courtage devenue, au fil des ans, l’une des plus importantes et dynamiques de la Bourse de New York. Mais il avait créé en parallèle une société d’investissement destinée à faire prospérer la fortune de clients choisis : stars du cinéma, des lettres, et même de la finance. Avec une promesse irrésistible : un rendement moyen continu de 15 % par an sur une très longue période. De 1990 à 2008, en dépit des aléas des marchés, aucune année négative n’a troublé l’horizon. Comment ? Mystère bien gardé.

Les vieux financiers savent que, quand on vous promet à la fois la sécurité d’un bon du Trésor et le rendement exceptionnel de la Bourse, c’est qu’il y a anguille sous roche. Et l’anguille était en l’occurrence une gigantesque pyramide de Ponzi, où l’argent des nouveaux investisseurs finançait la rétribution des clients en cours.

Certains, pourtant, se sont inquiétés de la montée en puissance d’une machine aussi spectaculaire. A trois reprises, entre 2001 et 2005, le financier Harry Markopolos a alerté la SEC. Aucune enquête n’a été menée, en dépit d’indices confondants. De grandes banques ont fermé les yeux. Tout le monde était content, l’eau était claire, alors pourquoi remuer la vase ? Il a fallu attendre la crise de 2008 et la demande de retrait de fonds des clients pour s’apercevoir qu’ils avaient disparu.

Philippe Escande / Le Monde

Stephanie Kelton läxar upp Sveriges finansminister

15 Apr, 2021 at 22:48 | Posted in Economics | 2 Comments

Underskottsmyten – verbal förlagEn av USA:s mest uppmärksammade och omdebatterade nationalekonomer, Stephanie Kelton, kritiserar nu finansminister Magdalena Andersson. Enligt Kelton hade regeringen i vårbudgeten kunnat välja att låna ännu mer för att få fart på ekonomin.

När finansministern på torsdagen presenterade vårbudgeten pratade hon åter igen om att regeringen har sparat i ladorna och därför kan satsa nu under pandemin. Hon har också sagt att de lånade pengarna måste betalas tillbaka och ladorna fyllas igen. Men det här är ett helt felaktigt sätt att resonera och Sverige kan göra mycket mer, säger hon till SVT.

– Det är en självpåtagen restriktion, som förhindrar det ekonomiska välmåendet. Du håller dig själv gisslan, säger Stephanie Kelton.

SvT Nyheter

Yours truly har under ett par års tid nu frågat sig varför vi i det här landet har en regering som inte vågar satsa kraftfullt på en offensiv finanspolitik och låna mer. Inte minst mot bakgrund av de historiskt låga räntorna är det ett gyllene tillfälle att satsa på investeringar inom infrastruktur, vård, skola och välfärd.

Tyvärr verkar det som om Magdalena Andersson har rejäla kunskapsluckor. Lite ‘functional finance’ och MMT kanske inte skulle skada. Eller varför inte ta och läsa Keltons nyligen till svenska översatta bok?

Ett lands statsskuld är sällan en orsak till ekonomisk kris, utan snarare ett symtom på en kris som sannolikt blir värre om inte underskotten i de offentliga finan­serna får öka.

Den ­svenska utlandsskulden är historiskt låg. Statsskulden ligger idag på lite över 25 procent av BNP. Med tanke på de stora utmaningar som Sverige står inför i coronavirusets kölvatten är fortsatt tal om “ansvar” för statsbudgeten minst sagt oansvarigt. I stället för att prata om “sparande i ladorna” och att ”värna om statsfinanserna” bör en ansvarsfull rege­ringen se till att värna om samhällets framtid. Det är kontraproduktivt att föra en ekonomisk politik med syfte att minska statsskulden. Det minst sagt bedrövligt när en regering inte insett att problemet med en statsskuld i en situation med nästintill negativa räntor inte är att den är för stor, utan för liten.

Att staten nu under coronaåret 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. Och behöver vi mer för att hålla igång de ekonomiska hjulen är det bara att “trycka” nya.

Vad många politiker och mediala så kallade experter inte verkar (vilja) förstå är 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. Statliga skulder är inte som privata skulder. En stats skulder är väsentligen en skuld till den själv, till dess medborgare.

När regeringen för lite drygt ett år sedan bestämde sig för att skjuta till nya miljarder och låta statsskulden öka för att få fart på ekonomin under och efter coronaepidemin, trodde nog en del att vi stod inför ett paradigmskifte. Tyvärr visar det sig nu, som så många gånger förut — när väl den värsta krisen är över, är det ‘business as usual’ och Göran Perssons mantra ”den som är satt i skuld är icke fri” dammas av igen.

Men en statsskuld är varken bra eller dålig. Den ska vara ett medel att uppnå två övergripande makroekonomiska mål — full sysselsättning och prisstabilitet. Vad som är ‘heligt’ är inte att ha en balanserad budget eller att hålla nere statsskulden. Om idén om ‘sunda’ statsfinanser leder till ökad arbetslöshet och instabila priser borde det vara självklart att den överges. ‘Sunda’ statsfinanser är osunt.

Debunking the trickle-down myth

15 Apr, 2021 at 15:09 | Posted in Economics | Leave a comment

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What we see happen in the US and many other countries is deeply disturbing. The rising inequality is outrageous — not the least since it has to a large extent to do with income and wealth increasingly being concentrated in the hands of a very small and privileged elite.

Societies where we allow the inequality of incomes and wealth to increase without bounds, sooner or later implode. The cement that keeps us together erodes and in the end we are only left with people dipped in the ice cold water of egoism and greed.

The biggest problem in science

15 Apr, 2021 at 08:24 | Posted in Statistics & Econometrics | Leave a comment

null-hypothesis1 In 2016, Vox sent out a survey to more than 200 scientists, asking, “If you could change one thing about how science works today, what would it be and why?” One of the clear themes in the responses: The institutions of science need to get better at rewarding failure.

One young scientist told us, “I feel torn between asking questions that I know will lead to statistical significance and asking questions that matter.”

The biggest problem in science isn’t statistical significance. It’s the culture. She felt torn because young scientists need publications to get jobs. Under the status quo, in order to get publications, you need statistically significant results. Statistical significance alone didn’t lead to the replication crisis. The institutions of science incentivized the behaviors that allowed it to fester.

Brian Resnick

ad11As shown over and over again when significance tests are applied, people have a tendency to read ‘not disconfirmed’ as ‘probably confirmed.’ Standard scientific methodology tells us that when there is only say a 5 % probability that pure sampling error could account for the observed difference between the data and the null hypothesis, it would be more ‘reasonable’ to conclude that we have a case of disconfirmation. Especially if we perform many independent tests of our hypothesis and they all give about the same 5 % result as our reported one, I guess most researchers would count the hypothesis as even more disconfirmed.

We should never forget that the underlying parameters we use when performing significance tests are model constructions. Our p-values mean nothing if the model is wrong. And most importantly — statistical significance tests DO NOT validate models!

statistical-models-sdl609573791-1-42fd0In journal articles a typical regression equation will have an intercept and several explanatory variables. The regression output will usually include an F-test, with p – 1 degrees of freedom in the numerator and n – p in the denominator. The null hypothesis will not be stated. The missing null hypothesis is that all the coefficients vanish, except the intercept.

If F is significant, that is often thought to validate the model. Mistake. The F-test takes the model as given. Significance only means this: if the model is right and the coefficients are 0, it is very unlikely to get such a big F-statistic. Logically, there are three possibilities on the table:
i) An unlikely event occurred.
ii) Or the model is right and some of the coefficients differ from 0.
iii) Or the model is wrong.
So?

Identity politics is bullshit

15 Apr, 2021 at 08:11 | Posted in Politics & Society | 1 Comment

Identität ist alles. Ich. Meine Werte und meine Rechte. Das, was (zu) mir gehört. Was ich bin oder sein will. Wovon ich überzeugt bin, weil ich es einfach weiß. Wofür ich anerkannt und entschädigt werden muss. altIdentität ist eine riesige Sprechblase, die immer größer wird, je mehr Leute sich am Spiel beteiligen: Identität ist Heimat ist Hautfarbe ist Geschlecht ist sexuelle Orientierung ist Kultur ist Herkunft ist Familie ist Nation ist Tradition ist Integration. Was ist Identität? Die Antwort kann nur tautologisch sein (“Identität ist Identität”). Identität ist, wie der italienische Literaturwissenschaftler Daniele Giglioli konstatiert, entsprechend ihrer lateinischen Wortwurzel idem “die Permanenz desselben”. Identität ist auch etwas, das Immanuel Kant ens rationis nannte, einen “leeren Begriff ohne Gegenstand” …

Nicht Identitäten fordern Anerkennung von anderen, sondern konkrete Menschen. Nicht über Identitäten kann und soll man streiten, sondern darüber, welche Ansprüche berechtigt sind und welche nicht, welche Lebensformen mit anderen kollidieren, was im Zusammenleben “geht” und was nicht. Es sollte darum gehen, wie Menschen in all ihrer Unterschiedlichkeit miteinander zurechtkommen. Was wir brauchen, das ist eine Sensibilität für Situationen und Kontexte, die Bereitschaft zu lernen und zu experimentieren.

“Identität” aber ist Bullshit. Wir sollten den nutzlosen Identitätsbegriff also entsorgen. Theoretiker wie Praktikerinnen sollten nach pragmatistischer Art neue Begriffe finden, die sich als konkret zweckmäßig erweisen, politisch und gesellschaftlich, im Zusammenleben der Menschen – und nicht bloß als Bälle in einem Sprachspiel, das am Ende höchstens dem Distinktionsgewinn einiger Intellektueller dient.

Rebekka Reinhard & Thomas Vašek / Die Zeit

Barfuß Am Klavier (personal)

13 Apr, 2021 at 11:50 | Posted in Economics | 1 Comment


jag på einstein-berlin1988
Yours truly. Café Einstein, Berlin 1988. Photo by Bengt Nilsson.

Filtering nonsense economics

13 Apr, 2021 at 09:30 | Posted in Economics | 4 Comments

Study claims that the presence of bad smells make people more opposed to  gay marriageFollowing the greatest economic depression since the 1930s, Robert Solow in 2010 gave a prepared statement on “Building a Science of Economics for the Real World” for a hearing in the U. S. Congress. According to Solow modern macroeconomics has not only failed at solving present economic and financial problems, but is “bound” to fail. Building microfounded macromodels on “assuming the economy populated by a representative agent” — consisting of “one single combination worker-owner-consumer-everything-else who plans ahead carefully and lives forever” — do not pass the smell test: does this really make sense? Solow surmised that a thoughtful person “faced with the thought that economic policy was being pursued on this basis, might reasonably wonder what planet he or she is on.”

Conclusion: an economic theory or model that doesn’t pass the real world smell-test is just silly nonsense that doesn’t deserve our attention and therefore belongs in the dustbin.

Microfounded macroeconomic DSGE models immediately come to mind.

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 I tried to show in my paper Rational expectations — a fallacious foundation for macroeconomics in a non-ergodic world — there is really no support for that 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 replace macroeconomic models building on representative actors and rational expectations-microfoundations with more realist and relevant macroeconomic thinking.

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.

Whereas some theoretical models can be immensely useful in developing intuitions, in essence a theoretical model is nothing more than an argument that a set of conclusions follows from a given set of assumptions. Being logically correct may earn a place for a theoretical model on the bookshelf, but when a theoretical model is taken off the shelf and applied to the real world, it is important to question whether the model’s assumptions are in accord with what we know about the world. Is the story behind the model one that captures what is important or is it a fiction that has little connection to what we see in practice? Have important factors been omitted? Are economic agents assumed to be doing things that we have serious doubts they are able to do? These questions and others like them allow us to filter out models that are ill suited to give us genuine insights. To be taken seriously models should pass through the real world filter.

Paul Pfleiderer

Pfleiderer’s perspective may be applied to many of the issues involved when modelling complex and dynamic economic phenomena. Let me take just one example — simplicity.

When it comes to modelling I do see the point often emphatically made for simplicity among economists and econometricians — but only as long as it doesn’t impinge on our truth-seeking. “Simple” macroeconom(etr)ic models may of course be an informative heuristic tool for research. But if practitioners of modern macroeconom(etr)ics do not investigate and make an effort of providing a justification for the credibility of the simplicity-assumptions on which they erect their building, it will not fullfil its tasks. Maintaining that economics is a science in the “true knowledge” business, I remain a skeptic of the pretences and aspirations of  “simple” macroeconom(etr)ic models and theories. So far, I can’t really see that e. g. “simple” microfounded models have yielded very much in terms of realistic and relevant economic knowledge.

All empirical sciences use simplifying or unrealistic assumptions in their modelling activities. That is not the issue – as long as the assumptions made are not unrealistic in the wrong way or for the wrong reasons.

But models do not only face theory. They also have to look to the world. Being able to model a “credible world,” a world that somehow could be considered real or similar to the real world, is not the same as investigating the real world. Even though — as Pfleiderer acknowledges — all theories are false, since they simplify, they may still possibly serve our pursuit of truth. But then they cannot be unrealistic or false in any way. The falsehood or unrealisticness has to be qualified.

Explanation, understanding and prediction of real world phenomena, relations and mechanisms therefore cannot be grounded on simpliciter assuming simplicity. If we cannot show that the mechanisms or causes we isolate and handle in our models are stable, in the sense that what when we export them from are models to our target systems they do not change from one situation to another, then they – considered “simple” or not – only hold under ceteris paribus conditions and a fortiori are of limited value for our understanding, explanation and prediction of our real world target system.

The obvious ontological shortcoming of a basically epistemic – rather than ontological – approach, is that “similarity” or “resemblance” tout court do not guarantee that the correspondence between model and target is interesting, relevant, revealing or somehow adequate in terms of mechanisms, causal powers, capacities or tendencies. No matter how many convoluted refinements of concepts made in the model, if the simplifications made do not result in models similar to reality in the appropriate respects (such as structure, isomorphism etc), the surrogate system becomes a substitute system that does not bridge to the world but rather misses its target.

Constructing simple macroeconomic models somehow seen as “successively approximating” macroeconomic reality, is a rather unimpressive attempt at legitimising using fictitious idealisations for reasons more to do with model tractability than with a genuine interest of understanding and explaining features of real economies. Many of the model assumptions standardly made by neoclassical macroeconomics – simplicity being one of them – are restrictive rather than harmless and could a fortiori anyway not in any sensible meaning be considered approximations at all.

If economists aren’t able to show that the mechanisms or causes that they isolate and handle in their “simple” models are stable in the sense that they do not change when exported to their “target systems”, they do only hold under ceteris paribus conditions and are a fortiori of limited value to our understanding, explanations or predictions of real economic systems.

That Newton’s theory in most regards is simpler than Einstein’s is of no avail. Today Einstein has replaced Newton. The ultimate arbiter of the scientific value of models cannot be simplicity.

As scientists we have to get our priorities right. Ontological under-labouring has to precede epistemology.

Oft gefragt (personal)

10 Apr, 2021 at 12:14 | Posted in Varia | Leave a comment

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Zu Hause bist immer nur du
Zu Hause bist immer nur du
Du hast mich abgeholt und hingebracht
Bist mitten in der Nacht wegen mir aufgewacht
Ich hab in letzter Zeit so oft daran gedacht
Hab keine Heimat, ich hab nur dich
Du bist zu Hause für immer und mich

In loving memory of my mother, Lisbeth.

Although it is thirty-two years since she passed away, not a single day goes by without her in my mind.

Those whom the gods love die young.

Lisbetwp-1590939903265382057111.jpgBut in dreams,
I can hear your name.
And in dreams,
We will meet again.

When the seas and mountains fall
And we come to end of days,
In the dark I hear a call
Calling me there
I will go there
And back again.

Tony Lawson and the nature of heterodox economics

9 Apr, 2021 at 18:17 | Posted in Economics | 4 Comments

Lawson believes that there is a ‘coherent core’ of heterodox economists who employ methods that are consistent with the social ontology they implicitly advance. However, Lawson also acknowledges that many also use mathematical modelling, a method that presupposes a social ontology that is in severe tension with it. Therefore, I repeat, Lawson proposes that heterodox economists in fact exist in two groups, those who use methods consistent with the social ontology they are committed to, and those who do not. But all are heterodox economists.

Lawson’s hope is that by making the kind of social ontology presupposed by mathematical modelling clear, heterodox economists will increasingly review the legitimacy of the modelling approach. However, Lawson still considers those who make such a methodological mistake to be heterodox economists. For they still, he argues, are committed to the social ontology he defends and always reveal it in some way in their analyses or pronouncements …

Professor Tony Lawson on Economics & Social Ontology in Economics: past,  present and future. An interview project on Vimeo In recent years, Lawson has been increasingly frustrated by the continued use of mathematical modelling by heterodox economists, as well as by movements towards its increased usage. An argument made by such heterodox economists is that the problem identified by Lawson lies not with mathematical modelling per se but with the sort of mathematical methods used. They argue that poor mathematical modelling has been the problem and that better, more complex, models will be able to capture the reality of human existence.

Lawson clearly regards that methodological argument to be mistaken. For, as stated above, he finds that even complex mathematical models presuppose a closed system. However, he maintains that the social reality that such researchers reveal themselves to implicitly accept is at least quite similar to that which he defends. Their concern with being realistic, for one, speaks volumes. Therefore, these researchers should, he believes, still be distinguished from the mainstream …

Lawson does not argue for excluding mathematical models. Rather, as with all other methods, they should only be applied in conditions in which their use is appropriate, though admittedly Lawson does, as an empirical matter, assess the occurrence of the latter to be relatively rare. His stance is not anti-mathematical method but anti-mismatch of method and context of application … What Lawson does argue for regarding practice is an explicit, systematic and sustained ontological awareness, which he believes can only improve the methodological choices of heterodox economists.

Yannick Slade-Caffarel

If scientific progress in economics lies in our ability to tell ‘better and better stories’ one would, of course, expect economics journals being filled with articles supporting the stories with empirical evidence confirming the predictions. However, the journals still show a striking and embarrassing paucity of empirical studies that (try to) substantiate these predictive claims. Equally amazing is how little one has to say about the relationship between the model and real-world target systems. It is as though explicit discussion, argumentation and justification on the subject aren’t considered to be required.

In mathematics, the deductive-axiomatic method has worked just fine. But science is not mathematics. Conflating those two domains of knowledge has been one of the most fundamental mistakes made in modern — and as Lawson argues, both in mainstream and heterodox — economics. Applying it to real-world open systems immediately proves it to be excessively narrow and hopelessly irrelevant. Both the confirmatory and explanatory ilk of hypothetico-deductive reasoning fails since there is no way you can relevantly analyse confirmation or explanation as a purely logical relation between hypothesis and evidence or between law-like rules and explananda. In science, we argue and try to substantiate our beliefs and hypotheses with reliable evidence. Propositional and predicate deductive logic, on the other hand, is not about reliability, but the validity of the conclusions given that the premises are true.

Reasoning in economics

9 Apr, 2021 at 10:22 | Posted in Economics | 3 Comments

Reasoning: Amazon.co.uk: Scriven, Michael: 9780070558823: BooksReasoning is the process whereby we get from old truths to new truths, from the known to the unknown, from the accepted to the debatable … If the reasoning starts on firm ground, and if it is itself sound, then it will lead to a conclusion which we must accept, though previously, perhaps, we had not thought we should. And those are the conditions that a good argument must meet; true premises and a good inference. If either of those conditions is not met, you can’t say whether you’ve got a true conclusion or not.

Mainstream economic theory today is in the story-telling business whereby economic theorists create make-believe analogue models of the target system – usually conceived as the real economic system. This modeling activity is considered useful and essential. Since fully-fledged experiments on a societal scale as a rule are prohibitively expensive, ethically indefensible or unmanageable, economic theorists have to substitute experimenting with something else. To understand and explain relations between different entities in the real economy the predominant strategy is to build models and make things happen in these ‘analogue-economy models’ rather than engineering things happening in real economies.

Mainstream economics has since long given up on the real world and contents itself with proving things about thought up worlds. Empirical evidence only plays a minor role in economic theory, where models largely function as a substitute for empirical evidence. The one-sided, almost religious, insistence on axiomatic-deductivist modeling as the only scientific activity worthy of pursuing in economics, is a scientific cul-de-sac. To have valid evidence is not enough. What economics needs is sound evidence — evidence based on arguments that are valid in form and with premises that are true.

Avoiding logical inconsistencies is crucial in all science. But it is not enough. Just as important is avoiding factual inconsistencies. And without showing — or at least presented with a warranted argument — that the assumptions and premises of their models are in fact true, mainstream economists aren’t really reasoning, but only playing games. Formalistic deductive ‘Glasperlenspiel’ can be very impressive and seductive. But in the realm of science it ought to be considered of little or no value to simply make claims about the model and lose sight of reality.

Dune Mosse

9 Apr, 2021 at 09:55 | Posted in Economics | Leave a comment

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Un viaggio in fondo ai tuoi occhi “dai d’illusi smammai” /

Un viaggio in fondo ai tuoi occhi solcherò / Dune Mosse …

Dentro una lacrima / E verso il sole / Voglio gridare amore  /

Uuh, non ne posso più  / Vieni t’imploderò /

A rallentatore, e … / E nell’immenso morirò!

Questa canzone è un’opera d’arte. Musica d’altissimo livello. Meravigliosa!

Im Netz der Verschwörung

7 Apr, 2021 at 17:47 | Posted in Politics & Society | Leave a comment

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Statistical power (student stuff)

7 Apr, 2021 at 16:59 | Posted in Statistics & Econometrics | Leave a comment

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