John Maynard Keynes — life, ideas, legacy

12 Jun, 2021 at 11:47 | Posted in Economics | Leave a comment

.

Att tjäna pengar på sjuka — en riktigt sjuk idé

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

För Attendo är affärsidén underbemanningPersonal på Attendos äldreboende Långbroberg i södra Stockholm har larmat om missförhållanden – utan att de känner att de får gehör hos cheferna.

Ett tiotal anställda väljer nu att berätta om:

■ Obemannade avdelningar nattetid, där boende skriker av smärta och det dröjer innan de får hjälp.

■ Blaskig soppa, frysta måltider och ont om frukost, vilket gör att brukare är hungriga och rasar i vikt.

■ Boende som läggs för natten redan vid 16-tiden och får äta middag i sängen.

– Jag kastar mig hellre framför ett tåg än bli gammal om det ska vara så här, säger undersköterskan Maria Norstad Pantén, 60.

Karin Sörbring/Expressen

Många som är verksamma inom skolvärlden eller vårdsektorn har haft svårt att förstå socialdemokratins inställning till privatiseringar och vinstuttag i den mjuka välfärdssektorn. Av någon outgrundlig anledning har ledande socialdemokrater under många år pläderat för att vinster ska vara tillåtna i skolor och vårdföretag. Ofta har argumentet varit att driftsformen inte har någon betydelse. Så är inte fallet. Driftsform och att tillåta vinst i välfärden har visst betydelse. Och den är negativ.

Socialdemokratin är förvisso långt ifrån ensamt om sitt velande. På den andra kanten hörs från Svenskt Näringsliv och landets alla ledarskribenter en jämn ström av krav på ökad kontroll, tuffare granskning och inspektioner.

Men vänta lite nu! Var det inte så att när man på 1990-talet påbörjade systemskiftet inom välfärdssektorn ofta anförde som argument för privatiseringarna att man just skulle slippa den byråkratiska logikens kostnader i form av regelverk, kontroller och uppföljningar? Konkurrensen – denna marknadsfundamentalismens panacé – skulle ju göra driften effektivare och höja verksamheternas kvalitet. Marknadslogiken skulle tvinga bort de ‘byråkratiska’ och tungrodda offentliga verksamheterna och kvar skulle bara finnas de bra företagen som ‘valfriheten’ möjliggjort.

Och nu när den panglossianska privatiseringsvåtdrömmen visar sig vara en mardröm så ska just det som man ville bli av med – regelverk och ‘byråkratisk’ tillsyn och kontroll – vara lösningen?

Man tar sig för pannan – och det av många skäl!

För ska man genomföra de åtgärdspaket som förs fram undrar man ju hur det går med den där effektivitetsvinsten. Kontroller, uppdragsspecifikationer, inspektioner m m kostar ju pengar och hur mycket överskott blir det då av privatiseringarna när dessa kostnader också ska räknas hem i kostnads-intäktsanalysen? Och hur mycket värd är den där ‘valfriheten’ när vi ser hur den gång på gång bara resulterar i verksamhet där vinst genereras genom kostnadsnedskärningar och sänkt kvalitet?

Effektiv resursanvändning kan aldrig vara ett mål i sig. Däremot kan det vara ett nödvändigt medel för att nå uppsatta mål. Välfärdsstatens vara eller icke vara handlar inte bara om ekonomisk effektivitet, utan också om våra föreställningar om ett värdigt liv, rättvisa och lika behandling.

Så grundfrågan är inte om skattefinansierade privata företag ska få göra vinstuttag eller om det krävs hårdare tag i form av kontroll och inspektion. Grundfrågan är om det är marknadens och privatiseringarnas logik som ska styra våra välfärdsinrättningar eller om det ske via demokratins och politikens logik. Grundfrågan handlar om den gemensamma välfärdssektorn ska styras av demokrati och politik eller av marknaden.

Seven lessons we need to learn from the pandemic

10 Jun, 2021 at 09:07 | Posted in Economics | Leave a comment

.

Yours truly on The Top Economics Blogs list

3 Jun, 2021 at 21:47 | Posted in Economics | 2 Comments

New outlook … | LARS P. SYLLMainstream economics has sadly made economics increasingly irrelevant to the understanding of the real world. Trying to contribute in making economics a more realist and relevant science, yours truly launched this blog in March 2011.

Now, ten years later and with millions of page views on it, yours truly is — together with people like e.g. Greg Mankiw and Paul Krugman — ranked on INOMICS’ The Top Economics Blogs list.

I am — of course — truly awed, honoured and delighted.

There are many excellent economics blogs out there … The blogs we’ve listed — in no particular order — are the ones we here at INOMICS turn to when we’re looking for interesting, informative, and occasionally offbeat articles on a wide range of economic topics …

1. Random Observations for Students of Economics

Greg Mankiw uses his blog predominantly to keep in touch with his own students, but it also serves as an excellent source of information on many economics topics to those currently studying …

7. Naked Capitalism

Naked Capitalism is a blog written by several different writers, all of whom have credentials writing and studying economics …

13. Paul Krugman

Paul Krugman, a household name and heavyweight economist in the modern age, writes a regular column for the New York Times on macroeconomics, trade, healthcare, social policy and politics  …

22. Lars P. Syll

Lars Pålsson Syll is a professor at Malmö University in Sweden who focuses on the philosophy and methodology of economics, theories of distributive justice, and critical realist social science. An avowed critic of neoliberalism and market fundamentalism, his blog covers a wide range of topics in English, French, German and Swedish.

INOMICS

Causal inference from observational data

1 Jun, 2021 at 14:23 | Posted in Economics | 1 Comment

nisbettResearchers often determine the individual’s contemporary IQ or IQ earlier in life, socioeconomic status of the family of origin, living circumstances when the individual was a child, number of siblings, whether the family had a library card, educational attainment of the individual, and other variables, and put all of them into a multiple-regression equation predicting adult socioeconomic status or income or social pathology or whatever. Researchers then report the magnitude of the contribution of each of the variables in the regression equation, net of all the others (that is, holding constant all the others). It always turns out that IQ, net of all the other variables, is important to outcomes. But … the independent variables pose a tangle of causality – with some causing others in goodness-knows-what ways and some being caused by unknown variables that have not even been measured. Higher socioeconomic status of parents is related to educational attainment of the child, but higher-socioeconomic-status parents have higher IQs, and this affects both the genes that the child has and the emphasis that the parents are likely to place on education and the quality of the parenting with respect to encouragement of intellectual skills and so on. So statements such as “IQ accounts for X percent of the variation in occupational attainment” are built on the shakiest of statistical foundations. What nature hath joined together, multiple regressions cannot put asunder.

Now, I think this is right as far as it goes, although it would certainly have strengthened Nisbett’s argumentation if he had elaborated more on the methodological question around causality, or at least had given some mathematical-statistical-econometric references. Unfortunately, his alternative approach is not more convincing than regression analysis. As so many other contemporary social scientists today, Nisbett seems to think that randomization solves empirical problems. By randomizing we are getting different ‘populations’ that are homogeneous in regards to all variables except the one we think is a genuine cause. In that way we are supposed being able not having to actually know what all these other factors are.

If you succeed in performing an ideal randomization with different treatment groups and control groups that is attainable. But it presupposes that you really have been able to establish — and not just assume — that the probability of all other causes but the putative have the same probability distribution in the treatment and control groups, and that the probability of assignment to treatment or control groups are independent of all other possible causal variables.

Unfortunately, real experiments and real randomizations seldom or never achieve this. So, yes, we may do without knowing all causes, but it takes ideal experiments and ideal randomizations to do that, not real ones. That means that in practice we do have to have sufficient background knowledge to deduce causal knowledge. Without old knowledge, we can’t get new knowledge — and, ‘no causes in, no causes out.’

On the issue of the shortcomings of multiple regression analysis, no one sums it up better than David Freedman:

Layout 1

Regression models often seem to be used to compensate for problems in measurement, data collection, and study design. By the time the models are deployed, the scientific position is nearly hopeless …

Causal inference from observational data presents many difficulties, especially when underlying mechanisms are poorly understood. There is a natural desire to substitute intellectual capital for labor, and an equally natural preference for system and rigor over methods that seem more haphazard. These are possible explanations for the current popularity of statistical models.

Indeed, far-reaching claims have been made for the superiority of a quantitative template that depends on modeling – by those who manage to ignore the far-reaching assumptions behind the models. However, the assumptions often turn out to be unsupported by the data. If so, the rigor of advanced quantitative methods is a matter of appearance rather than substance.

Elizabeth Warren roasting top bank CEOs

26 May, 2021 at 19:51 | Posted in Economics, Politics & Society | 1 Comment

.

That’s the right spirit, senator! Watching Warren give these baloney talking guys a well-earned lecture on public decency is absolutely fabulous.

Why economic models do not explain

26 May, 2021 at 19:14 | Posted in Economics | 1 Comment

Krugman on models (II) | LARS P. SYLLAnalogue-economy models may picture Galilean thought experiments or they may describe credible worlds. In either case we have a problem in taking lessons from the model to the world. The problem is the venerable one of unrealistic assumptions, exacerbated in economics by the fact that the paucity of economic principles with serious empirical content makes it difficult to do without detailed structural assumptions. But the worry is not just that the assumptions are unrealistic; rather, they are unrealistic in just the wrong way.

Nancy Cartwright

One of the limitations with economics is the restricted possibility to perform experiments, forcing it to mainly rely on observational studies for knowledge of real-world economies.

But still — the idea of performing laboratory experiments holds a firm grip of our wish to discover (causal) relationships between economic ‘variables.’If we only could isolate and manipulate variables in controlled environments, we would probably find ourselves in a situation where we with greater ‘rigour’ and ‘precision’ could describe, predict, or explain economic happenings in terms of ‘structural’ causes, ‘parameter’ values of relevant variables, and economic ‘laws.’

Galileo Galilei’s experiments are often held as exemplary for how to perform experiments to learn something about the real world. Galileo’s heavy balls dropping from the tower of Pisa, confirmed that the distance an object falls is proportional to the square of time and that this law (empirical regularity) of falling bodies could be applicable outside a vacuum tube when e. g. air existence is negligible.

The big problem is to decide or find out exactly for which objects air resistance (and other potentially ‘confounding’ factors) is ‘negligible.’ In the case of heavy balls, air resistance is obviously negligible, but how about feathers or plastic bags?

One possibility is to take the all-encompassing-theory road and find out all about possible disturbing/confounding factors — not only air resistance — influencing the fall and build that into one great model delivering accurate predictions on what happens when the object that falls is not only a heavy ball but feathers and plastic bags. This usually amounts to ultimately state some kind of ceteris paribus interpretation of the ‘law.’

Another road to take would be to concentrate on the negligibility assumption and to specify the domain of applicability to be only heavy compact bodies. The price you have to pay for this is that (1) ‘negligibility’ may be hard to establish in open real-world systems, (2) the generalisation you can make from ‘sample’ to ‘population’ is heavily restricted, and (3) you actually have to use some ‘shoe leather’ and empirically try to find out how large is the ‘reach’ of the ‘law.’

In mainstream economics, one has usually settled for the ‘theoretical’ road (and in case you think the present ‘natural experiments’ hype has changed anything, remember that to mimic real experiments, exceedingly stringent special conditions have to obtain).

In the end, it all boils down to one question — are there any Galilean ‘heavy balls’ to be found in economics, so that we can indisputably establish the existence of economic laws operating in real-world economies?

As far as I can see there some heavy balls out there, but not even one single real economic law.

Economic factors/variables are more like feathers than heavy balls — non-negligible factors (like air resistance and chaotic turbulence) are hard to rule out as having no influence on the object studied.

Galilean experiments are hard to carry out in economics, and the theoretical ‘analogue’ models economists construct and in which they perform their ‘thought-experiments’ build on assumptions that are far away from the kind of idealized conditions under which Galileo performed his experiments. The ‘nomological machines’ that Galileo and other scientists have been able to construct have no real analogues in economics. The stability, autonomy, modularity, and interventional invariance, that we may find between entities in nature, simply are not there in real-world economies. That’s are real-world fact, and contrary to the beliefs of most mainstream economists, they won’t go away simply by applying deductive-axiomatic economic theory with tons of more or less unsubstantiated assumptions.

By this, I do not mean to say that we have to discard all (causal) theories/laws building on modularity, stability, invariance, etc. But we have to acknowledge the fact that outside the systems that possibly fulfil these requirements/assumptions, they are of little substantial value. Running paper and pen experiments on artificial ‘analogue’ model economies is a sure way of ‘establishing’ (causal) economic laws or solving intricate econometric problems of autonomy, identification, invariance and structural stability — in the model world. But they are pure substitutes for the real thing and they don’t have much bearing on what goes on in real-world open social systems. Setting up convenient circumstances for conducting Galilean experiments may tell us a lot about what happens under those kinds of circumstances. But — few, if any, real-world social systems are ‘convenient.’ So most of those systems, theories and models, are irrelevant for letting us know what we really want to know.

To solve, understand, or explain real-world problems you actually have to know something about them — logic, pure mathematics, data simulations or deductive axiomatics don’t take you very far. Most econometrics and economic theories/models are splendid logic machines. But — applying them to the real world is a totally hopeless undertaking! The assumptions one has to make in order to successfully apply these deductive-axiomatic theories/models/machines are devastatingly restrictive and mostly empirically untestable– and hence make their real-world scope ridiculously narrow. To fruitfully analyse real-world phenomena with models and theories you cannot build on patently and known to be ridiculously absurd assumptions. No matter how much you would like the world to entirely consist of heavy balls, the world is not like that. The world also has its fair share of feathers and plastic bags.

The problem articulated by Cartwright is that most of the ‘idealizations’ we find in mainstream economic models are not ‘core’ assumptions, but rather structural ‘auxiliary’ assumptions. Without those supplementary assumptions, the core assumptions deliver next to nothing of interest. So to come up with interesting conclusions you have to rely heavily on those other — ‘structural’ — assumptions.

Whenever model-based causal claims are made, experimentalists quickly find that these claims do not hold under disturbances that were not written into the model. Our own stock example is from auction design – models say that open auctions are supposed to foster better information exchange leading to more efficient allocation. Do they do that in general? Or at least under any real world conditions that we actually know about? Maybe. But we know that introducing the smallest unmodelled detail into the setup, for instance complementarities between different items for sale, unleashes a cascade of interactive effects. Careful mechanism designers do not trust models in the way they would trust genuine Galilean thought experiments. Nor should they.

A. Alexandrova & R. Northcott

In physics, we have theories and centuries of experience and experiments that show how gravity makes bodies move. In economics, we know there is nothing equivalent. So instead mainstream economists necessarily have to load their theories and models with sets of auxiliary structural assumptions to get any results at all int their models.

So why do mainstream economists keep on pursuing this modelling project?

Continue Reading Why economic models do not explain…

Testing causal explanations in economics

26 May, 2021 at 11:14 | Posted in Economics | Leave a comment

Idealisations to the rescue | Opinion | Chemistry WorldThird, explanations fail by question (3.1) [“are the factors cited as possible causes of an event in fact aspects of the situation in which that event occurred?”] where the factors invoked as possible causes are idealisations. No doubt this claim will be considered contentious by some economists, accustomed as they are to explanations based on such dramatic assumptions as rational expectations, single-agent ‘economies’, and two-commodity ‘worlds’. The issue here turns on the distinction between abstraction (passing over or omitting to mention aspects of the causal history) and idealisation (invoking entities that exist only in the realm of ideas, such as most limit types and what Maki (1992) calls ‘theoretical isolations’). This distinction cannot be pursued here, but the general idea is that although every explanation involves abstraction insofar as we can never provide a complete list of the causes of any event, no genuine attempt at causal explanation can invoke as causes theoretical entities that have no existence other than in the minds and discourse of scientific investigators. For such entities cannot be aspects of real economic situations and are therefore ineligible as candidate causes. Explanations that invoke such entities therefore either fail, if offered as causal explanations in the sense I have described, or should be thought of as something other than causal explanations.

Jochen Runde

When it comes to modelling, yours truly does 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 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, yours truly remains a skeptic of the pretences and aspirations of  ‘simple’ macroeconom(etr)ic models and theories building on unwarranted idealisations. So far, I can’t really see that e. g.  microfounded macromodels have yielded very much in terms of realistic and relevant economic knowledge.

All empirical sciences use simplifying or unrealistic assumptions (abstractions) 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 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 the invoked isolations to be warranted. 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 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 the use of idealisations 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 ‘simplifying’ idealisations 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 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 in mainstream macroeconomics are restrictive rather than harmless and could a fortiori anyway not in any sensible meaning be considered approximations at all.

If you — to ‘save’ your theory or model — have to invoke things that do not exist , well, then your theory or model is probably not adequate enough to give the searched for causal explanations.

Functional finance and Ricardian equivalence

25 May, 2021 at 08:30 | Posted in Economics | 6 Comments

According to Abba Lerner, the purpose of public debt is “to achieve a rate of interest which results in the most desirable level of investment.” He also maintained that an application of Functional finance will have a tendency to balance the budget in the long run:

Finally, there is no reason for assuming that, as a result of the continued application of Functional Finance to maintain full employment, the government must always be borrowing more money and increasing the national debt. There are a number of reasons for this.

dec3bb27f72875e4fb4d4b62daebb2fd161b36392c1a0626f00cfd2ece207d84First, full employment can be maintained by printing the money needed for it, and this does not increase the debt at all. It is probably advisable, however, to allow debt and money to increase together in a certain balance, as long as one or the other has to increase.

Second, since one of the greatest deterrents to private investment is the fear that the depression will come before the investment has paid for itself, the guarantee of permanent full employment will make private investment much more attractive, once investors have gotten over their suspicion of the new procedure. The greater private investment will diminish the need for deficit spending.

Third, as the national debt increases, and with it the sum of private wealth, there will be an increasingly yield from taxes on higher incomes and inheritances, even if the tax rates are unchanged. These higher tax payments do not represent reductions of spending by the taxpayers. Therefore the government does not have to use these proceeds to maintain the requisite rate of spending, and can devote them to paying the interest on the national debt.

Fourth, as the national debt increases it acts as a self-equilibrating force, gradually diminishing the further need for its growth and finally reaching an equilibrium level where its tendency to grow comes completely to an end. The greater the national debt the greater is the quantity of private wealth. The reason for this is simply that for every dollar of debt owed by the government there is a private creditor who owns the government obligations (possibly through a corporation in which he has shares), and who regards these obligations as part of his private fortune. The greater the private fortunes the less is the incentive to add to them by saving out of current income …

Fifth, if for any reason the government does not wish to see private property grow too much … it can check this by taxing the rich instead of borrowing from them, in its program of financing government spending to maintain full employment. The rich will not reduce their spending significantly, and thus the effects on the economy, apart from the smaller debt, will be the same as if Money had been borrowed from them.

Abba Lerner

Even if most of today’s mainstream economists do not understand Lerner, there once was one who certainly did:

I recently read an interesting article on deficit budgeting … His argument is impeccable.

John Maynard Keynes CW XXVII:320

According to the Ricardian equivalence hypothesis the public sector basically finances its expenditures through taxes or by issuing bonds, and bonds must sooner or later be repaid by raising taxes in the future.

If the public sector runs extra spending through deficits, taxpayers will according to the hypothesis anticipate that they will have to pay higher taxes in future — and therefore increase their savings and reduce their current consumption to be able to do so, the consequence being that aggregate demand would not be different to what would happen if taxes were raised today.

Robert Barro attempted to give the proposition a firm theoretical foundation in the 1970s.

So let us get the facts straight from the horse’s mouth.

Describing the Ricardian Equivalence in 1989 Barro writes (emphasis added):

Suppose now that households’ demands for goods depend on the expected present value of taxes—that is, each household subtracts its share of this present value from the expected present value of income to determine a net wealth position. Then fiscal policy would affect aggregate consumer demand only if it altered the expected present value of taxes. But the preceding argument was that the present value of taxes would not change as long as the present value of spending did not change. Therefore, the substitution of a budget deficit for current taxes (or any other rearrangement of the timing of taxes) has no impact on the aggregate demand for goods. In this sense, budget deficits and taxation have equivalent effects on the economy — hence the term, “Ricardian equivalence theorem.” To put the equivalence result another way, a decrease in the government’s saving (that is, a current budget deficit) leads to an offsetting increase in desired private saving, and hence to no change in desired national saving.

Since desired national saving does not change, the real interest rate does not have to rise in a closed economy to maintain balance between desired national saving and investment demand. Hence, there is no effect on investment, and no burden of the public debt …

Ricardian equivalence basically means that financing government expenditures through taxes or debts is equivalent since debt financing must be repaid with interest, and agents — equipped with rational expectations — would only increase savings in order to be able to pay the higher taxes in the future, thus leaving total expenditures unchanged.

There is, of course, no reason for us to believe in that fairy-tale. Ricardo himself — mirabile dictu — didn’t believe in Ricardian equivalence. In “Essay on the Funding System” (1820) he wrote:

But the people who paid the taxes never so estimate them, and therefore do not manage their private affairs accordingly. We are too apt to think that the war is burdensome only in proportion to what we are at the moment called to pay for it in taxes, without reflecting on the probable duration of such taxes. It would be difficult to convince a man possessed of £20,000, or any other sum, that a perpetual payment of £50 per annum was equally burdensome with a single tax of £1000.

Vad man ser och hedrar

23 May, 2021 at 10:38 | Posted in Economics, Varia | Leave a comment

Slas får egen park | SvDJan Myrdal var i Paris just då och ville likna August Strindberg så till den grad att han tog in på hotell Orfila och bodde i det rum där hans idol en gång bott.

Själv ville jag inte likna Jan Myrdal.

Stig ‘Slas’ Claesson

Does size matter?

20 May, 2021 at 08:56 | Posted in Economics | 8 Comments

Economic growth has since long interested economists. Not least, the question of which factors are behind high growth rates has been in focus. The factors usually pointed at are mainly economic, social and political variables. In an interesting study from the University of  Helsinki, Tatu Westling has expanded the potential causal variables to also include biological and sexual variables. In  the report Male Organ and Economic Growth: Does Size Matter, he has — based on the “cross-country” data of Mankiw et al (1992), Summers and Heston (1988), Polity IV Project data of political regime types and a new data set on average penis size in 76 non-oil producing countries (www.everyoneweb.com/worldpenissize) — been able to show that the level and growth of GDP per capita between 1960 and 1985 varies with penis size. Replicating Westling’s study — yours truly has used his favourite program Gretl — we obtain the following two charts:


The Solow-based model estimates show that the maximum GDP is achieved with the penis of about 13.5 cm and that the male reproductive organ (OLS without control variables) are negatively correlated with — and able to explain 20% of the variation in — GDP growth.

Even with reservation for problems such as endogeneity and confounders one can not but agree with Westling’s final assessment that “the ‘male organ hypothesis’ is worth pursuing in future research” and that it “clearly seems that the ‘private sector’ deserves more credit for economic development than is typically acknowledged.” Or? …

När penningsystemet inte levererar

16 May, 2021 at 11:41 | Posted in Economics | Comments Off on När penningsystemet inte levererar

Ett ännu tyngre ansvar bär regeringen som trots den lägsta statsskulden på 40 år valt att fortsätta betala av ännu mer. Den offentliga skuldsättningen i Sverige väntas 2021 sjunka under 30 procent av BNP, vilket innebär att regeringen är skyldig enligt lag att förklara för Riksdagen hur det kommer sig att man inte spenderat mera pengar.

250px-Wikip-facepalmRegeringens tvångsmässiga avbetalningar har uppmärksammats i internationell ekonomipress och anklagats för att vara rent vansinne …

När näringslivet inte levererar, Magdalena Andersson betalar av på statsskulden och penningsystemet inte förmår sätta nyskapade pengar i cirkulation i realekonomin tvingas Riksbanken kompensera genom minusränta och kvantitativa lättnader.

Att på detta sätt tvinga Riksbanken skjuta mygg med kanonkulor är inte hållbart i längden. Penningpolitiken har visserligen haft önskad effekt och fått upp inflationen, men skadorna på resten av ekonomin kan bli stora på sikt.

Regeringen sitter på vapen för att bekämpa arbetslöshet och låg inflation med betydligt högre precision. Men då krävs att regeringen slutar gömma sig bakom överskottsmålet samt att näringslivet tar sitt ansvar och gör samhällsnytta i stället för att försöka tjäna maximalt på passivt ägande.

På lång sikt måste hela penningsystemet reformeras. Det är inte hållbart att samtliga pengar skapas genom skuldsättning. När inte staten skuldsätter sig måste den privata sektorn skuldsätta sig för att nya pengar ska skapas till ekonomin. Hög privat skuldsättning har dock i den ekonomiska forskningen pekats ut som främsta riskfaktorn för allvarliga finansiella kriser.

En väg att gå vore att Riksbanken skapade och delade ut pengar direkt till regeringen eller medborgarna utan att någon måste skuldsätta sig och betala ränta. Då kan regeringen inte längre gömma sig bakom överskottsmålet. De får pengar direkt i handen som måste spenderas.

På så vis ges Riksbanken nya verktyg att stimulera ekonomin och inflationen utan att svenska kronans värde, tillgångspriserna, skuldsättningen och de ekonomiska klyftorna ökar.

Samuel Kazen Orrefur, Markus Kallifatides, Daniel Suhonen

Cos’è la MMT?

16 May, 2021 at 10:48 | Posted in Economics | Comments Off on Cos’è la MMT?

Pin su {Re} Riletture estive di Rete MMTMMT è due cose: è una lente di osservazione dei processi di creazione e circolazione del denaro, ed è una ricetta per la piena occupazione e la stabilità dei prezzi. Quanto alla prima, i contributi migliori di MMT sono quelli che, sviscerando i nessi tecnici tra banca centrale, banche e Tesoro, dimostrano che il denaro a disposizione della spesa pubblica proviene sempre, inevitabilmente, dalla banca centrale, e che la differenza tra finanziamento sul mercato e monetizzazione del debito è una distinzione istituzionale e politica. La ricchezza finanziaria di famiglie e imprese, a sua volta, non può che essere alimentata dal credito bancario e dal disavanzo pubblico, ed entrambi sono strumenti che sostengono la crescita e, se sfrenati, causano crisi finanziarie o inflazione. Eppure, le regole di politica economica degli ultimi trent’anni hanno privilegiato unicamente il ruolo della banca centrale che manovrando il costo del denaro può solo incoraggiare o scoraggiare il debito privato.

Gli economisti MMT (e non) che usavano questo modo di vedere già prima della crisi hanno potuto decifrare meglio di altri i motivi per cui, contrariamente al senso comune, il pacchetto fiscale di Obama non avrebbe fatto salire i tassi, l’assenza di una politica fiscale comune europea avrebbe violentemente destabilizzato l’euro, e il Quantitative Easing non avrebbe prodotto inflazione. E ha potuto comprendere meglio di altri perché l’unica opzione sul tavolo per arrestare la frana dell’euro nel 2012 era che la BCE intervenisse ritagliandosi nuovi spazi d’azione che sembravano proibiti dalle regole della moneta unica. Una lente di lettura efficace, dunque: la stessa che il Levy Economics Institute adoperò per criticare, controcorrente, la riduzione del debito pubblico durante l’amministrazione Clinton perché rischiava di diventare la premessa di un’impetuosa crescita del debito privato, come è puntualmente accaduto fino al collasso del 2008. Quanto alle ricette MMT, a qualcuno piace liquidarle un po’ troppo frettolosamente, riassumendole superficialmente nel principio del paese di Cuccagna in cui basta stampare denaro per diventare ricchi. Il punto è evidentemente un altro, ed è quello di spostare l’attenzione dalla dimensione del debito alla qualità della spesa e all’efficacia dell’imposizione fiscale, monitorandone con estrema attenzione le ricadute potenzialmente inflazionistiche. Il disegno è quello di dare massima priorità alla creazione di opportunità di lavoro, sia privato che di utilità sociale, adoperando la politica fiscale in maniera funzionale al raggiungimento del fine.

Andrea Terzi

Another positive contribution of MMT, especially from a European point of view, is also that it makes it transparently clear why the euro-experiment has been such a monumental disaster. The neoliberal dream of having over-national currencies just doesn’t fit well with reality. When an economy is in a crisis, it must be possible for the state to manage and spend its own money to stabilize the economy.

When the euro was launched back in 1999, it was celebrated with fireworks at the European Central Bank headquarters in Frankfurt. Today we know better. There are no reasons to celebrate. On the contrary.

euroAlready since its start, the euro has been in crisis. And the crisis is far from over. The tough austerity measures imposed in the eurozone has made economy after economy contract. And it has not only made things worse in the periphery countries, but also in countries like France and Germany. Alarming facts that should be taken seriously.

The problems — created to a large extent by the euro — may not only endanger our economies, but also our democracy itself. How much whipping can democracy take? How many more are going to get seriously hurt and ruined before we end this madness and scrap the euro?

The euro has taken away the possibility for national governments to manage their economies in a meaningful way — and in country after country, the people have had to pay the true costs of its concomitant misguided austerity policies.

The unfolding of the repeated economic crises in euroland during the last decade has shown beyond any doubts that the euro is not only an economic project but just as much a political one. What the neoliberal revolution during the 1980s and 1990s didn’t manage to accomplish, the euro shall now force on us.

But do the peoples of Europe really want to deprive themselves of economic autonomy and slash social welfare at the slightest sign of economic distress? Are​ increasing income inequality and a federal überstate really the stuff that our dreams are made of? I very much doubt it.

The gender wage gap

15 May, 2021 at 19:40 | Posted in Economics | Comments Off on The gender wage gap

uberUber has conducted a study of internal pay differentials between men and women, which they describe as “gender blind” … The study found a 7% pay gap in favor of men. They present their findings as proof that there are issues unrelated to gender that impact driver pay. They quantify the reasons for the gap as follows:

Where: 20% is due to where people choose to drive (routes/neighborhoods).

Experience: 30% is due to experience …

Speed: 50% was due to speed, they claim that men drive slightly faster, so complete more trips per hour …

The company’s reputation has been affected by its sexist and unprofessional corporate culture, and its continued lack of gender balance won’t help. Nor, I suspect, will its insistence, with research conducted by its own staff to prove it, that the pay gap is fair. This simply adds insult to obnoxiousness.

But then, why would we have expected any different? The Uber case study’s conclusions may actually be almost the opposite of what they were trying to prove. Rather than showing that the pay gap is a natural consequence of our gendered differences, they have actually shown that systems designed to insistently ignore differences tend to become normed to the preferences of those who create them.

Avivah Wittenberg-Cox

Spending a couple of hours going through a JEL survey of modern research on the gender wage gap, yours truly was struck almost immediately by how little that research really has accomplished in terms of explaining gender wage discrimination. With all the heavy regression and econometric alchemy used, wage discrimination is somehow more or less conjured away …

Trying to reduce the risk of having established only ‘spurious relations’ when dealing with observational data, statisticians and econometricians standardly add control variables. The hope is that one thereby will be able to make more reliable causal inferences. But if you do not manage to get hold of all potential confounding factors, the model risks producing estimates of the variable of interest that are even worse than models without any control variables at all. Conclusion: think twice before you simply include ‘control variables’ in your models!

That women are working in different areas than men, and have other educations than men, etc., etc., are not only the result of ‘free choices’ causing a gender wage gap, but actually to a large degree itself the consequence of discrimination.

The gender pay gap is a fact that, sad to say, to a non-negligible extent is the result of discrimination. And even though many women are not deliberately discriminated against, but rather ‘self-select’ (sic!) into lower-wage jobs, this in no way magically explains away the discrimination gap. As decades of socialization research has shown, women may be ‘structural’ victims of impersonal social mechanisms that in different ways aggrieve them.

Looking at wage discrimination from a graph theoretical point of view one could arguably identify three paths between gender discrimination (D) and wages (W):

  1. D => W
  2. D => OCC => W
  3. D => OCC <= A => W

where occupation (OCC) is a mediator variable and unobserved ability (A) is a variable that affects both occupational choice and wages. The usual way to find out the effect of discrimination on wages is to perform a regression “controlling” for OCC to get what one considers a “meaningful” estimate of real gender wage discrimination:

W = a + bD + cOCC

The problem with this procedure is that conditioning on OCC not only closes the mediation path (2), but — since OCC is a “collider” — opens up the backdoor path (3) and creates a spurious and biased estimate. Forgetting that may even result in the gender discrimination effect being positively related to wages! So if we want to go down the standard path (controlling for OCC) we certainly also have to control for A if we want to have a chance of identifying the causal effect of gender discrimination on wages. And that may, of course, be tough going, since A often (as here) is unobserved and perhaps even unobservable …

The experimental dilemma

15 May, 2021 at 10:43 | Posted in Economics | Comments Off on The experimental dilemma

resissWe can either let theory guide us in our attempt to estimate causal relationships from data … or we don’t let theory guide us. If we let theory guide us, our causal inferences will be ‘incredible’ because our theoretical knowledge is itself not certain … If we do not let theory guide us, we have no good reason to believe that our causal conclusions are true either of the experimental population or of other populations because we have no understanding of the mechanisms that are responsible for a causal relationship to hold in the first place, and it is difficult to see how we could generalize an experimental result to other settings if this understanding doesn’t exist. Either way, then, causal inference seems to be a cul-de-sac.

Nowadays many mainstream economists maintain that ‘imaginative empirical methods’ — especially randomized experiments (RCTs) — can help us to answer questions concerning the external validity of economic models. In their view, they are, more or less, tests of ‘an underlying economic model’ and enable economists to make the right selection from the ever-expanding ‘collection of potentially applicable models.’

It is widely believed among economists that the scientific value of randomization — contrary to other methods — is totally uncontroversial and that randomized experiments are free from bias. When looked at carefully, however, there are in fact few real reasons to share this optimism on the alleged ’experimental turn’ in economics. Strictly seen, randomization does not guarantee anything.

‘Ideally controlled experiments’ tell us with certainty what causes what effects — but only given the right ‘closures.’ Making appropriate extrapolations from (ideal, accidental, natural or quasi) experiments to different settings, populations or target systems, is not easy. ‘It works there’ is no evidence for ‘it will work here’. Causes deduced in an experimental setting still have to show that they come with an export-warrant to the target population. The causal background assumptions made have to be justified, and without licenses to export, the value of ‘rigorous’ and ‘precise’ methods — and ‘on-average-knowledge’ — is despairingly small.

the-right-toolThe almost religious belief with which its propagators — including ‘Nobel prize’ winners like Duflo, Banerjee and Kremer  — portray it, cannot hide the fact that RCTs cannot be taken for granted to give generalizable results. That something works somewhere is no warranty for us to believe it to work for us here or that it works generally.

The present RCT idolatry is dangerous. Believing there is only one really good evidence-based method on the market — and that randomization is the only way to achieve scientific validity — blinds people to searching for and using other methods that in many contexts are better. RCTs are simply not the best method for all questions and in all circumstances. Insisting on using only one tool often means using the wrong tool.

Next Page »

Blog at WordPress.com.
Entries and Comments feeds.