Randomization revisited

5 Apr, 2020 at 16:55 | Posted in Economics | Leave a comment

Development economists have been using randomized controlled trials (RCTs) for the best part of two decades, and economists working on welfare policies in the US have been doing so for much longer. The years of experience have made the discussions richer and more nuanced, and both proponents and critics have learned from one another, at least to an extent. In this essay, I do not attempt to reconstruct the full range of questions that I have written about elsewhere. Instead, I focus on a few of the issues that are prominent in this volume of critical perspectives.

imagesThe RCT is a useful tool, but I think that is a mistake to put method ahead of substance. I have written papers using RCTs. Like other methods of investigation, they are often useful, and, like other methods, they have dangers and drawbacks. Methodological prejudice can only tie our hands. Context is always important, and we must adapt our methods to the problem at hand. It is not true that an RCT, when feasible, will always do better than an observational study. This should not be controversial, but my reading of the rhetoric in the literature suggests that the following statements might still make some uncomfortable, particularly the second: (a) RCTs are affected by the same problems of inference and estimation that economists have faced using other methods, and (b) no RCT can ever legitimately claim to have established causality.

My theme is that RCTs have no special status, they have no exemption from the problems of inference that econometricians have always wrestled with, and there is nothing that they, and only they, can accomplish. Just as none of the strengths of RCTs are possessed by RCTs alone, none of their weaknesses are theirs alone, and I shall take pains to emphasize those facts. There is no gold standard. There are good studies and bad studies, and that is all.

Angus Deaton

Great essay.

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 both exaggerated and 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.

Deaton’s essay underscores the problem many ‘randomistas’ end up with when underestimating heterogeneity and interaction is not only an external validity problem when trying to ‘export’ regression results to different times or different target populations. It is also often an internal problem to the millions of regression estimates that economists produce every year.

‘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. And since trials usually are not repeated, unbiasedness and balance on average over repeated trials say nothing about any one trial. ‘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/system. 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.

RCTs have very little reach beyond giving descriptions of what has happened in the past. From the perspective of the future and for policy purposes they are as a rule of limited value since they cannot tell us what background factors were held constant when the trial intervention was being made.

RCTs usually do not provide evidence that the results are exportable to other target systems. RCTs cannot be taken for granted to give generalizable results. That something works somewhere for someone is no warranty for us to believe it to work for us here or even that it works generally.

Why we need Big Theories

4 Apr, 2020 at 18:13 | Posted in Theory of Science & Methodology | Leave a comment

 

Nights in white satin

4 Apr, 2020 at 15:46 | Posted in Varia | 1 Comment

 

Moody Blues classic that still — after more than 50 years — gives me goose pimples every time I listen to it.

Statsskulden är vårt minsta problem nu

4 Apr, 2020 at 14:37 | Posted in Economics | 1 Comment

Den största risken är att vi precis som 2008 underskattar nedgången … Men Magdalena Andersson verkar fast i sin metafor att hon sparat duktigt och därför kan vi använda lite av det hon ”sparat i ladan”. Men metaforen är fel, för en regering måste skydda sin befolkning även när ”ladan är tom”.

Coronavirus economic impact concept imageI stora kriser som krig och pandemier ställs de vanliga reglerna på ända. Precis allt måste göras för att besegra viruset och skydda samhället från en större katastrof. Den sjukvårdskris som snart kommer explodera har vi dessutom sparat oss in i. Just nu hade vi hellre haft fler anställda och vårdplatser än alla miljarder kronor vi sparat. Därför trollas det nu med knäna i vården för att reparera 30 års svältkur.

Den andra krisen är den massarbetslöshet och ekonomiska depression vi står inför. Även den måste regeringen göra allt för att hindra …

Det är dags att lägga 90-talets sparretorik bakom sig. Ladan brinner. Om den ska kunna släckas avgörs inom kort. Framtiden kommer döma försiktiga politiker hårt.

Daniel Suhonen

Yours truly och några få andra nationalekonomer — de som fortfarande har lite kontakt med verkligheten — har under ett par års tid nu frågat sig varför vi i det här landet har en regering som inte vågar satsa 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 — i likhet med många andra studenter från Handelshögskolan i Stockholm — har rejäla kunskapsluckor. Kanske borde man sluta lära ut monetaristiskt Chicago-nonsens från 70-talet och istället följa med i teoriutvecklingen. Lite ‘functional finance’ och MMT kanske inte skulle skada även på maktelitens lekskola …

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. Den konsoliderade statsskulden ligger idag på lite över 20 procent av BNP och enligt regeringens prognoser kommer den att vara kring 16 procent om två år. 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 ”värna om statsfinanserna” bör en ansvarsfull rege­ringen se till att värna om samhällets framtid. När numera t.o.m. IMF insett att det är kontraproduktivt att föra en ekonomisk politik med syfte att minska statsskulden, är 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.

How money is created

4 Apr, 2020 at 10:29 | Posted in Economics | 23 Comments

Everything we know is not just wrong – it’s backwards. When banks make loans, they create money. This is because money is really just an IOU. The role of the central bank is to preside over a legal order that effectively grants banks the exclusive right to create IOUs of a certain kind, ones that the government will recognise as legal tender by its willingness to accept them in payment of taxes.

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There’s really no limit on how much banks could create, provided they can find someone willing to borrow it. They will never get caught short, for the simple reason that borrowers do not, generally speaking, take the cash and put it under their mattresses; ultimately, any money a bank loans out will just end up back in some bank again. So for the banking system as a whole, every loan just becomes another deposit. What’s more, insofar as banks do need to acquire funds from the central bank, they can borrow as much as they like; all the latter really does is set the rate of interest, the cost of money, not its quantity. Since the beginning of the recession, the US and British central banks have reduced that cost to almost nothing. In fact, with “quantitative easing” they’ve been effectively pumping as much money as they can into the banks, without producing any inflationary effects.

What this means is that the real limit on the amount of money in circulation is not how much the central bank is willing to lend, but how much government, firms, and ordinary citizens, are willing to borrow. Government spending is the main driver in all this … So there’s no question of public spending “crowding out” private investment. It’s exactly the opposite.

David Graeber

Sounds odd, doesn’t it?

This guy must sure be one of those strange and dangerous heterodox cranks?

Well, maybe you should reconsider …

The reality of how money is created today differs from the description found in some economics textbooks:
• Rather than banks receiving deposits when households save and then lending them out, bank lending creates deposits.
• In normal times, the central bank does not fix the amount of money in circulation, nor is central bank money ‘multiplied up’ into more loans and deposits …
Most of the money in circulation is created, not by the printing presses of the Bank of England, but by the commercial banks themselves: banks create money whenever they lend to someone in the economy or buy an asset from consumers. And in contrast to descriptions found in some textbooks, the Bank of England does not directly control the quantity of either base or broad money. The Bank of England is nevertheless still able to influence the amount of money in the economy. It does so in normal times by setting monetary policy — through the interest rate that it pays on reserves held by commercial banks with the Bank of England. More recently, though, with Bank Rate constrained by the effective lower bound, the Bank of England’s asset purchase programme has sought to raise the quantity of broad money in circulation. This in turn affects the prices and quantities of a range of assets in the economy, including money.

Michael McLeay, Amar Radia and Ryland Thomas
Bank of England’s Monetary Analysis Directorate

Blott en dag

4 Apr, 2020 at 10:25 | Posted in Varia | Leave a comment

 

Ain’t no sunshine when she’s gone

3 Apr, 2020 at 18:51 | Posted in Varia | Leave a comment

 

Acclaimed soul singer behind hit Ain’t No Sunshine, Bill Withers, has died from heart complications aged 81. RIP.

Politiska reformer bakom ökade ojämlikheten

3 Apr, 2020 at 18:38 | Posted in Economics | 1 Comment

Både den rikaste och den fattigaste tiondelen av befolkningen sticker ut i statistiken, men det finns även skillnader inom dessa grupper. Under 70-talet minskade de rikaste 10 procentens andel av inkomsterna från omkring en fjärdedel till en femtedel, men har sedan 1980 knaprat sig tillbaka. Den rikaste procentens andel har däremot nästan fördubblats till cirka 7 procent av landets samlade inkomster. Det mesta av ökningen står kapitalinkomsterna för, en inkomst som kommer av sparat kapital snarare än arbete.

loDet beror på marknaden, men även 80-talets avregleringar (privatisering av statliga bolag) och andra politiska reformer. Redan 1991 sänktes skatten på kapitalinkomster, vilket gör det lönsammare att ta ut vinster som utdelning i stället för lön. Under 00-talet avskaffades skatterna på arv och gåvor, förmögenhet och fastigheter.

Jobbskatteavdragen och det ökade värdet av bostäder och bostadsrätter har spätt på ökningen mellan de rikaste och de fattigaste ytterligare. En effekt är att utdelningarna i onoterade fåmansbolag har ökat. För sådana är skatten 10 procentenheter lägre än i börsnoterade bolag.

– Det finns ett enormt incitament för ägare av fåmansbolag att ta ut sina inkomster som utdelning i stället för lön. De går primärt till människor i den övre delen av inkomstfördelningen. Och samtidigt som kapitalinkomsterna i toppen ökat så har de som saknar jobb halkat efter i relativa termer, säger Håkan Selin, docent i nationalekonomi och verksam vid IFAU, Institutet för arbetsmarknads- och utbildningspolitisk utvärdering.

Mats Karlsson / Forskning.se

Cauchy logic and economics

3 Apr, 2020 at 11:21 | Posted in Economics | Leave a comment

 

Yours truly has no problem with solving problems in mathematics by ‘defining’ them away. But how about the real world? Maybe that ought to be a question to ponder even for economists all to fond of uncritically following the mathematical way when applying their mathematical models to the real world, where indeed “you can never have infinitely many heaps” …

In econometrics we often run into the ‘Cauchy logic’ — the data is treated as if it were from a larger population, a ‘superpopulation’ where repeated realizations of the data are imagined. Just imagine there could be more worlds than the one we live in and the problem is fixed …

Accepting Haavelmo’s domain of probability theory and sample space of infinite populations – just as Fisher’s “hypothetical infinite population, of which the actual data are regarded as constituting a random sample”, von Mises’s “collective” or Gibbs’s ”ensemble” – also implies that judgments are made on the basis of observations that are actually never made!

Infinitely repeated trials or samplings never take place in the real world. So that cannot be a sound inductive basis for a science with aspirations of explaining real-world socio-economic processes, structures or events. It’s — just as the Cauchy mathematical logic of ‘defining’ away problems — not tenable.

In social sciences — including economics — it’s always wise to ponder C. S. Peirce’s remark that universes are not as common as peanuts …

Coronakrisen — ett postkeynesianskt perspektiv

2 Apr, 2020 at 17:07 | Posted in Economics | 2 Comments

UnknownDet har uppstått ett brett politiskt stöd under coronakrisen för finanspolitiska stimulanser i de enskilda EU-länderna (och i Storbritannien). EU har åtminstone tillfälligt släppt sina stränga krav på offentlig budgetbalans och de nationella regeringarna har tvingats att göra avkall på sina egna finanspolitiska regler. Den expansiva finanspolitiken på ländernivå för att rädda jobb och företag har få restriktioner. Långräntorna är låga och kommer förmodligen att sjunka ytterligare trots de finanspolitiska åtgärderna – finansmarknaden förväntar sig nya penningpolitiska stimulanser och regeringar och riksbanker kommer att skapa nya pengar för att ”finansiera” de offentliga budgetunderskotten. Inflationstrycket i dagens internationella lågkonjunktur är dessutom obefintligt.

Vidare ökar utrymmet för en inhemsk efterfrågestimulans i länder som Sverige när även omvärlden för en liknande ekonomisk politik. De stora OECD-ländernas expansiva finanspolitik kommer dessutom att gynna Sveriges export. Det är fullt förståeligt att EuroMemo inte kan särbehandla EU-länder med en egen valuta i sitt upprop. Men vi kan inte bortse ifrån det faktum att kronans värde har en tendens att sjunka i tider av turbulenta finansmarknader. Krondeprecieringar utgör en ytterligare stimulans av vår export. Till detta ska läggas att en expansiv finanspolitisk i ett land på basis av ett ökat offentligt penningutbud förutsätter att landet har en egen valuta. En samordnad eller rentav samfälld finanspolitik i EU är inte bara en politisk omöjlighet i dagsläget utan också av mindre betydelse för Sverige under coronakrisen.

Det hade kanske varit på sin plats i uppropet med en kommentar av de företags- och bankstöd som redan har genomförts i EU-länderna. Förslag om en alternativ ekonomisk politik hade varit välkomna. Uppropet menar att en finansiering av offentliga initiativ för att övervinna coronakrisen och bygga upp en hållbar framtid är omöjlig på nationell nivå. Konkret rekommenderar uppropet en utgivning av euroobligationer och en förstärkning av EUs budget, åtgärder som dock är svåra att genomföra, speciellt med kort varsel för att lindra dagens ekonomiska kris.

För att förhindra massarbetslöshet, fattigdom och ojämlikhet måste den sociala dimensionen prioriteras i den ekonomiska politiken på EU-nivå enligt uppropet Men det hade varit konstruktivt att nämna behovet av en omfattande utbildnings- och arbetsmarknadspolitik för att möta kraven på en omställning av produktionen i coronakrisens kölvatten. I en rapport uttryckte EuroMemo Group nyligen en kritik av den omställningsorienterade arbetsmarknadspolitiken. Rapporten avfärdade politiken som en nordisk variant av ”supply-side economics”. Den förespråkade i stället Hyman Minskys ”job creation programs”, ett doktrinärt och snävt synsätt som även var svårt att försvara innan coronakrisen.

Ett progressivt program för att bekämpa dagens ekonomiska kris och lägga grunden till en återhämtning i EU-området måste bestå av åtgärder på nationell nivå som är ”postkeynesianskt” efterfrågeorienterade och ”nordiskt” utbudsorienterade. Köpkraften måste upprätthållas genom skattelättnader för låg- och medelinkomsttagare, reformeringar av pensions- och socialförsäkringssystemet- och helikopterpengar. En massiv satsning på utbildning och arbetsmarknadspolitik är nödvändig för att arbetslösa tillfälligt ska kunna ta andra jobb under dagens ekonomiska kris och för att anpassa arbetsmarknaden till en ekonomi utan corona. Skattelättnader för och subventioner till gröna investeringar är andra exempel på en progressiv utbudsekonomi.

Lennart Erixon

Dumb and Dumber — the Chicago version

2 Apr, 2020 at 12:18 | Posted in Economics | Leave a comment

dumb_aA couple of years ago, in a lecture on the US recession, Robert Lucas gave an outline of what the New Classical school of macroeconomics today thinks on the latest downturns in the US economy and its future prospects.

Lucas starts by showing that real US GDP has grown at an average yearly rate of 3 per cent since 1870, with one big dip during the Depression of the 1930s and a big – but smaller – dip in the recent recession.

After stating his view that the US recession that started in 2008 was basically caused by a run for liquidity, Lucas then goes on to discuss the prospect of recovery from where the US economy is today, maintaining that past experience would suggest an “automatic” recovery, if the free market system is left to repair itself to equilibrium unimpeded by social welfare activities of the government.

As could be expected there is no room for any Keynesian type considerations on eventual shortages of aggregate demand discouraging the recovery of the economy. No, as usual in the new classical macroeconomic school’s explanations and prescriptions, the blame game points to the government and its lack of supply side policies.

Lucas is convinced that what might arrest the recovery are higher taxes on the rich, greater government involvement in the medical sector and tougher regulations of the financial sector. But — if left to run its course unimpeded by European type welfare state activities — the free market will fix it all.

In a rather cavalier manner — without a hint of argument or presentation of empirical facts — Lucas dismisses even the possibility of a shortfall of demand. For someone who already 30 years ago proclaimed Keynesianism dead — “people don’t take Keynesian theorizing seriously anymore; the audience starts to whisper and giggle to one another” — this is of course only what could be expected. Demand considerations are simply ruled out on whimsical theoretical-ideological grounds, much like we have seen other neo-liberal economists do over and over again in their attempts to explain away the fact that the latest economic crises shows how the markets have failed to deliver. If there is a problem with the economy, the true cause has to be government.

Chicago economics is a dangerous pseudo-scientific zombie ideology that ultimately relies on the poor having to pay for the mistakes of the rich. Trying to explain business cycles in terms of rational expectations has failed blatantly. Maybe it would be asking too much of freshwater economists like Lucas to concede that, but it’s still a fact that ought to be embarrassing.

shackleIf at some time my skeleton should come to be used by a teacher of osteology to illustrate his lectures, will his students seek to infer my capacities for thinking, feeling, and deciding from a study of my bones? If they do, and any report of their proceedings should reach the Elysian Fields, I shall be much distressed, for they will be using a model which entirely ignores the greater number of relevant variables, and all of the important ones. Yet this is what ‘rational expectations’ does to economics.

G. L. S. Shackle

Game theory — a scientific cul-de-sac

1 Apr, 2020 at 13:56 | Posted in Economics | 4 Comments

Half a century ago there were widespread hopes game theory would provide a unified theory of social science. Today it has become obvious those hopes did not materialize. This ought to come as no surprise. Reductionist and atomistic models of social interaction — such as the ones mainstream economics and game theory are founded on — will never deliver sustainable building blocks for a realist and relevant social science. That is also — as yours truly argues in real-world economics review — the reason why game theory never will be anything but a footnote in the history of social science.

Lars Pålsson Syll_06Heavy use of formalism and mathematics easily foster the view that a theory is scientific. But although game theory may produce ‘absolute truths’ in imaginary model worlds, in the real world the game theoretic models are nothing but — as Rubinstein (2012a) puts it — fables. Fables much reminiscent of the models used in logic, but also like them, delivering very little of value for social sciences trying to explain and understand real-life phenomena. The games that game theory portrays are model constructs, models without significant predictive capacity simply because they do not describe an always much more complex and uncertain reality …

Although some economists consider it useful to apply game theory and use game theoretical definitions, axioms, and theorems and (try to) test if real-world phenomena ‘satisfy’ the axioms and the inferences made from them, we have argued that that view is without warrant. When confronted with the real world we can (hopefully) judge if game theory really tells us if things are as postulated. The final court of appeal for models is the real world, and as long as no convincing justification is put forward for how the inferential bridging de facto is made, model building is little more than hand-waving that give us rather little warrant for making inductive inferences from the model world to the real world.

The real challenge in social science is to accept uncertainty and still try to explain why different kinds of transactions and social interactions take place. Simply conjuring problems away by assuming patently unreal things and treating uncertainty as if it was possible to reduce to stochastic risk, is like playing tennis with the net down. That is not the kind of game that scientists working on constructing a relevant and realist science want to play.

COVID-19 depression antidote (II)

31 Mar, 2020 at 19:16 | Posted in Varia | 1 Comment

 

Maths and economics

31 Mar, 2020 at 15:05 | Posted in Economics | Leave a comment

Many American undergraduates in Economics interested in doing a Ph.D. are surprised to learn that the first year of an Econ Ph.D. feels much more like entering a Ph.D. in solving mathematical models by hand than it does with learning economics. Typically, there is very little reading or writing involved, but loads and loads of fast algebra is required. Why is it like this? …

ecoOne reason to use math is that it is easy to use math to trick people. Often, if you make your assumptions in plain English, they will sound ridiculous. But if you couch them in terms of equations, integrals, and matrices, they will appear more sophisticated, and the unrealism of the assumptions may not be obvious, even to people with Ph.D.’s from places like Harvard and Stanford, or to editors at top theory journals such as Econometrica …

Given the importance of signaling in all walks of life, and given the power of math, not just to illuminate and to signal, but also to trick, confuse, and bewilder, it thus makes perfect sense that roughly 99% of the core training in an economics Ph.D. is in fact in math rather than economics.

Douglas L. Campbell

Indeed.

No, there is nothing wrong with mathematics per se.

No, there is nothing wrong with applying mathematics to economics.

amathMathematics is one valuable tool among other valuable tools for understanding and explaining things in economics.

What is, however, totally wrong, are the utterly simplistic beliefs that

• “math is the only valid tool”

• “math is always and everywhere self-evidently applicable”

• “math is all that really counts”

• “if it’s not in math, it’s not really economics”

• “almost everything can be adequately understood and analyzed with math”

Mainstream economists have always wanted to use their hammer, and so have decided to pretend that the world looks like a nail. Pretending that uncertainty can be reduced to risk and that all activities, relations, processes and events can be adequately converted to pure numbers, have only contributed to making economics irrelevant and powerless when confronting real-world financial crises and economic havoc.

How do we put an end to this intellectual cataclysm? How do we re-establish credence and trust in economics as a science? Five changes are absolutely decisive.

(1) Stop pretending that we have exact and rigorous answers on everything. Because we don’t. We build models and theories and tell people that we can calculate and foresee the future. But we do this based on mathematical and statistical assumptions that often have little or nothing to do with reality. By pretending that there is no really important difference between model and reality we lull people into thinking that we have things under control. We haven’t! This false feeling of security was one of the factors that contributed to the financial crisis of 2008.

(2) Stop the childish and exaggerated belief in mathematics giving answers to important economic questions. Mathematics gives exact answers to exact questions. But the relevant and interesting questions we face in the economic realm are rarely of that kind. Questions like “Is 2 + 2 = 4?” are never posed in real economies. Instead of a fundamentally misplaced reliance on abstract mathematical-deductive-axiomatic models having anything of substance to contribute to our knowledge of real economies, it would be far better if we pursued “thicker” models and relevant empirical studies and observations.

(3) Stop pretending that there are laws in economics. There are no universal laws in economics. Economies are not like planetary systems or physics labs. The most we can aspire to in real economies is establishing possible tendencies with varying degrees of generalizability.

(4) Stop treating other social sciences as poor relations. Economics has long suffered from hubris. A more broad-minded and multifarious science would enrich today’s altogether too autistic economics.

(5) Stop building models and making forecasts of the future based on totally unreal micro-founded macro models with intertemporally optimizing robot-like representative actors equipped with rational expectations. This is pure nonsense. We have to build our models on assumptions that are not so blatantly in contradiction to reality. Assuming that people are green and come from Mars is not a good – not even as a ‘successive approximation’ – modelling strategy.

Good reasons to become a Keynesian

30 Mar, 2020 at 18:14 | Posted in Economics | 1 Comment

Until [2008], when the banking industry came crashing down and depression loomed for the first time in my lifetime, I had never thought to read The General Theory of Employment, Interest, and Money, despite my interest in economics … I had heard that it was a very difficult book and that the book had been refuted by Milton Friedman, though he admired Keynes’s earlier work on monetarism. I would not have been surprised by, or inclined to challenge, the claim made in 1992 by Gregory Mankiw, a prominent macroeconomist at Harvard, that “after fifty years of additional progress in economic science, The General Theory is an outdated book. . . . We are in a much better position than Keynes was to figure out how the economy works.”

adaWe have learned since [2008] that the present generation of economists has not figured out how the economy works …

Baffled by the profession’s disarray, I decided I had better read The General Theory. Having done so, I have concluded that, despite its antiquity, it is the best guide we have to the crisis …

It is an especially difficult read for present-day academic economists, because it is based on a conception of economics remote from theirs. This is what made the book seem “outdated” to Mankiw — and has made it, indeed, a largely unread classic … The dominant conception of economics today, and one that has guided my own academic work in the economics of law, is that economics is the study of rational choice … Keynes wanted to be realistic about decision-making rather than explore how far an economist could get by assuming that people really do base decisions on some approximation to cost-benefit analysis …

Economists may have forgotten The General Theory and moved on, but economics has not outgrown it, or the informal mode of argument that it exemplifies, which can illuminate nooks and crannies that are closed to mathematics. Keynes’s masterpiece is many things, but “outdated” it is not.

Richard Posner

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