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MMT economists do not seek to enumerate how many angels can dance on the head of a pin

One of the recurring criticisms that mainstream economists make of Modern Monetary Theory (MMT) is that does not follow the rules of formalism that have become the norm in the economics profession. The implication is that by not following these conventions, MMT economists are unable to say anything precise and scientific. Apparently, a literary discourse cannot convey anything that is sound. Pity that some of the greatest contributions to human knowledge have come from those who could write properly. But this criticism of MMT is about something else again. Dominant academic communities develop their own rules of enquiry, which encompass perspectives of the field to be studied, procedures to be followed, methods and techniques to be used and the end goals of the analysis. If those communities become riddled with Groupthink, then a degree of uniformity in practice becomes expected and enforced either subtly through peer group pressure or more coercively through publication, grant and promotional practices, which effectively determine whether a person will advance or be cast aside. The criticism waged against MMT economists that we don’t follow the normal rules of exposition is really an attempt to enforce the discipline of the mainstream (New Keynesian) community and avoid discussion of substantive issues, such as empirical congruence or extent of anomaly. If the dominant paradigm can convince young scholars and the public that its techniques and methods are the only sound way in which to conduct scientific enquiry and highlight an emerging threat as not being up to speed then it can avoid the scrutiny.

In September 2021, the Banque de France decided to reduce its credibility by publishing a Working Paper – The Meaning of MMT (WP #833).

It was a tawdry effort and full of errors and misrepresentations.

For example, it claims MMT economists believe that social welfare initiatives have “no cost”, or that “structural policies” are always “negative” in impact, etc.

I don’t intend to discuss the paper because it is so bad, but it does raise an important issue, which I have touched upon before but which seems to keep cropping up.

That is, the role of formalism.

The Banque de France paper concludes in relation to our work:

Their academic publications are also very repetitive, lacking in empirical analysis and almost exclusively literary, which does not allow to verify their assertions or to compare them with the recommendations of other schools of thought.

The “lacking in empirical analysis” criticism is a joke – consider how many graphs and tables and related discussion I produce just in my blog.

And if you were to consult my academic work – there is a lot of heavy econometric analysis there over many years – heaps of empirical analysis.

But the focus here is that we once again we encounter this notion that MMT economists do not use the mathematical tools and methods of enquiry that define mainstream New Keynesian economics.

As if that is a weakness.

Worryingly, I also detect among younger and emerging MMT economists are sense of ‘inferiority’ about a lack of use of mathematics or a sense of ‘necessity’ for MMT to be developed as a mathematical discipline to accord with the conventions they have learned in mainstream graduate programs in economics.

I reject that outright.

And, while many heterodox economists that I have known over my career have no background in mathematics or mathematical statistics, I can say that I, personally have a strong background, especially in mathematical statistics and econometrics, and applied economics using the state of art estimation techniques.

So my rejection is one of choice rather than a lack of skill.

The same could be said about some of the most famous economists – like Alfred Marshall and John Maynard Keynes, who were both trained initially as mathematicians.

Neither author used mathematical techniques in their major works (‘Principles’ and ‘General Theory’).

The major texts before the 1930s, all avoided any systematic use of mathematics, despite their authors being well-versed in the techniques.

The shift really occurred in the post World War 2 period when in the words of Roy Weintraub in his 2002 work ‘ How Economics Became a Mathematic’:

… economics was reshaped … as a mathematical discipline …

In epistemological terms, the profession really shifted from what it sought to know, to sustaining what it wanted people believe was valid economic enquiry.

The old textbooks used to represent different schools of thought and allow the students to debate the pros and cons of each relevant to real world problems.

The same students used to study economic history (often a compulsory first-year university course) to teach them the importance of context, institutions, politics and history.

And many studied the history of economic thought to gain an appreciation of the evolution of the discipline of economics.

In the 1970s that really changed and textbooks started pumping out the ‘one true model’ approach with scant attention to competing views. Broader subjects such as history and thought were culled from degree programs and the insularity of the discipline became heightened.

In this blog post – The evidence from the sociologists against economic thinking is compelling (November 12, 2019) – I discussed research that focuses on the way mainstream economists think.

The research surveyed economists and reported that one senior and eminent professor told them that:

You are only supposed to follow certain rules. If you don’t follow certain rules, you are not an economist. So that means you should derive the way people behave from strict maximization theory … The opposite [to being axiomatic] would be arguing by example. You’re not allowed to do that … There is a word for it. People say ‘that’s anecdotal.’ That’s the end of you if people have said you’re anecdotal … [T]he modern thing [people say] is: ‘it’s not identified.’ God, when your causality is not identified, that’s the end of you.

I also reported in this blog post the way in which economic research had become standardised.

Prominent New Keynesian, Olivier Blanchard Olivier Blanchard summarised the way in which economics had to be practised in his August 2008 article – The State of Macro.

Economists follow:

… strict, haiku-like, rules … [the economics papers] … look very similar to each other in structure, and very different from the way they did thirty years ago …

Graduate students are trained to follow these ‘haiku-like’ rules, that govern an economics paper’s chance of publication success, which then determines academic ppointments, promotion, grant success, and other elevations of influence (becoming chief economist in IMF etc).

So we get a formulaic approach to publications in macroeconomics that goes something like this:

  • Assert without foundation – so-called micro-foundations – rationality, maximisation, rational expectations.
  • Cannot deal with real world people so deal with one infinitely-lived agent!
  • Assert efficient, competitive markets as optimality benchmark.
  • Write some trivial mathematical equations and solve.
  • Policy shock ‘solution’ to ‘prove’, for example, that fiscal policy ineffective (Ricardian equivalence) and austerity is good. Perhaps allow some short-run stimulus effect.
  • Get some data – realise poor fit – add some ad hoc lags (price stickiness etc) to improve ‘fit’ but end up with identical long-term results.
  • Maintain pretense that micro-foundations are intact – after all it is the only claim to intellectual authority.
  • Publish articles that reinforce starting assumptions.
  • Knowledge quotient – ZERO – GIGO.

This is why the publication bias problem in mainstream macroeconomics is so significant.

One of the major issues with this approach is that it is inherently dishonest – persuading us that it is scientific and worthy of authority yet being so compromised as to be worthless.

In this blog post – Mainstream macroeconomic fads – just a waste of time (September 18, 2009) – I discussed the reasons why I would make such an accusation.

The summary point, to reinforce the dot points above, is that the mainstream macroeconomics paradigm claim they are rigourous because they begin with a set of first principles based on stylised assumptions of human behaviour that no psychologist or sociologist would recognise.

These assumptions about rationality and maximising strategies, individually pursued (devoid of social influence) are mathematically specified to allow a ‘solution’.

So the economists claim that their ‘macroeconomics’ is ground in microeconomic behaviour – which they, in turn, claim allows for consistency, a failure in their eyes of the economics of Keynes.

The mathematical framework they produce is by definition highly simplistic because otherwise they would not be able to ‘solve’ it for the unknown variables of interest (output, inflation etc) using standard mathematical approaches.

That then creates an issue.

To move from a theoretical mathematical rendition to a statistical model that econometricians estimate (unknown values) using regression techniques applied to real world data requires a statistical ‘specification’ – estimating equations with dependent variables and explanatory variables.

But the problem is that the simplistic theoretical models provide poor specifications if one is interested in capturing real world data movements.

What to do?

Solution – introduce ad hoc new variables (such as lags between variable responses) to allow the estimating equation to achieve desirable statistical properties – known as ‘goodness of fit’ and sound residual (the unexplained) performance.

The primary justification for the ad hocery is empirical.

But that creates a further issue.

If we believe that starting from first principles – micro optimising foundations – is rigourous then it is usually impossible to relate the econometric specification used to ‘fit the data’ with anything that can be derived from these foundations.

Which means that any results obtained from the data-fitting exercise cannot be used to justify the foundations.

The ‘rigour’ always fails to deliver anything remotely consistent with reality and the ad hoc (non rigourous) tack ons are then used to salvage the empirical exercise.

So at the end of the process there is no rigour at all.

And any policy analysis that comes from that sort of approach is typically useless for helping us understand real world problems.

Moreover it actively undermines the capacity to solve these problems by coming up with stupid conclusions that governments can run out of money or cause inflation and destroy their currencies if they run deficits etc.

The point is that there is no automatic virtue in using mathematics in economic analysis.

Keynes and formalism

Various writers made the same accusations of Keynes’ 1936 book – General Theory of Employment, Interest and Money.

Apparently, it needed economists trained in mathematics to reconstruct the General Theory into formal terms before it made any sense.

Even in recent times, this criticism continues to be made – for example, the 2010 article by Roger Backhouse – An Abstruse and Mathematical Argument: The use of Mathematical Reasoning in the General Theory.

Further, Keynes was warned by his peers that by adopting the conceptual apparatus, tools, and language of the classical school, which he aimed to attack, he would be blurring the argument and leaving himself open to having his ideas hijacked by the mainstream of the day.

Keynes made matters difficult for himself early on in the General Theory (Chapter 2), when he accepted the neoclassical postulate that the real wage is equal to the marginal product of labour and that the two move in opposite directions as a result of the assertion of diminishing marginl returns in production to labour (with short-run capital fixed).

The Stockholm School economist, Bertil Ohlin advised against the use of this ‘competitive’ assumption and Keynes wrote back to him in 1937 saying:

I have always regarded decreasing physical returns in the short period as one of the very few incontrovertible propositions of our miserable subject!

You can find the full discussion in Volume 14 of the – The Collected Writings of John Maynard Keynes – edited by Donald Moggridge and published by Macmillan in 1973. The ‘Letter to B. Ohlin, April 29, 1937 appears on pages 187-191.

By 1939, after two economists John Dunlop and Lorie Tarshis and published several articles (separately) criticising this assumption, Keynes published a follow up article (‘Relative Movements in Real Wages and Output’), which admitted he had erred, effectively ratifying the initial observations of Bertil Ohlin.

But by then the hijacking was underway and the outcome was the neoclassical-Keynesian synthesis, which essentially declared the insights of Keynes to be special cases where wage ridigity was found – and, by construction, an ephemeral situation.

This framework dominated the way macroeconomics was taught in the Post World War II period to the detriment of our discipline.

The current dominance of the New Keynesian paradigm is also the result of that hijacking and has no ‘Keynes’ or ‘macroeconomics’ in it.

The point is that in developing a new approach, it is unwise to use the language and concepts of the degenerative paradigm.

Paradigm shift requires new ways of doing things

Next year marks the 60th anniversary of the publication of Thomas Kuhn’s book – The Structure of Scientific Revolutions – which discusses the way in which scientific activity is conducted and the way in which “normal science” is disrupted by “revolutionary science”, which, from time to time, leads to paradigm shifts where the old orthodoxy, the dominant approach, is replaced rather than augmented by a new, more consistent and empirically tractable knowledge base.

In Chapter VIII The Response to Crisis, Kuhn discusses the transition to a new dominant paradigm as the existing orthodoxy gives way (pages 84-85):

The transition from a paradigm in crisis to a new one from which a new tradition of normal science can emerge is far from a cumulative process, one achieved by an articulation or extension of the old paradigm. Rather it is a reconstruction of the field from new fundamentals, a reconstruction that changes some of the field’s most elementary theoretical generalizations as well as many of its paradigm methods and applications. During the transition period there will be a large but never complete overlap between the problems that can be solved by the old and by the new paradigm. But there will also be a decisive difference in the modes of solution. When the transition is complete, the profession will have changed its view of the field, its methods, and its goals.

That is a very important insight to what happens.

It also highlights the point that once a new paradigm usurps the old, the practitioners will have quite different perspectives, use different methods and seek to achieve different goals.

Modern Monetary Theory (MMT) economists are clearly developing a new paradigm, which we believe is incommensurate with the old New Keynesian approach.

Our questions are different.

Our starting point is different – we seek to understand the uniqueness of being a currency issuer in stark contrast to the entitites that are currency users (households, firms, banks).

We seek to understand the actual way in which the central banks, commercial banks and treasuries interact rather than specifying how we might want them to act in some stylised fictional world and then inferring things from that fiction as if it applies to the world we live in.

And out techniques of analysis are different.

There is no point assuming the tools and frameworks of the degenerative paradigm are functional and worthy of iterating from.

That sort of approach leads nowhere.

The mainstream economists might want all the dialogue to be on their terms because they maintains their relevance.

But from where I sit they are irrelevant for those who seek to understand reality and solve real world problems.

I also discussed the issues of formality in these blog posts (among others):

1. GIGO (October 7, 2009).

2. OECD – GIGO Part 2 (July 27, 2010).

I remind readers of the observation by American (Marxist) economist Paul Sweezy who wrote in the 1972 – Monthly Review Press – article entitled Towards a Critique of Economics that mainstream economics:

… remained within the same fundamental limits … of the C19th century free market economist … they had … therefore tended … to yield diminishing returns. It has concerned itself with smaller and decreasingly significant questions … To compensate for this trivialisation of content, it has paid increasing attention to elaborating and refining its techniques. The consequence is that today we often find a truly stupefying gap between the questions posed and the techniques employed to answer them.

If you get hold of our new textbook – Macroeconomics – you will see mathematical formality when it helps to simplify the argument and advance the understanding.

Otherwise, words more than suffice.

Conclusion

Post Keynesian economist Paul Davidson wrote the following in a Chapter he contributed for the book by Bell and Kristol The Crisis in Economic Theory (Basic Books, 1981, p.157). It describes how mainstream economics uses methods and approaches that renders it unable to embrace real world problems:

There are certain purely imaginary intellectual problems for which general equilibrium models are well designed to provide precise answers (if anything really could). But this is much the same as saying that if one insists on analyzing a problem which has no real world equivalent or solution, it may be appropriate to use a model which has no real-world application. By the same token, if a model is designed specifically to deal with real-world situations it may not be able to handle purely imaginary problems.

He went on to note that heterodox approaches that “are designed specifically to deal with real-world problems … may not be very useful in resolving imaginary problems” that mainstream economists obsess over.

He said that heterodox economists are unable:

… to determine how many angels can dance on the head of a pin. On the other hand, models designed to provide answers to questions of the angel-pinhead variety, or imaginary problems involving specifying in advance the optional-allocation path over time, will be unsuitable for resolving practical, real-world economic problems.

In this tradition, Modern Monetary Theory (MMT) has never concerned itself with computing “how many angels can dance on the head of a pin”.

It is not an imaginary approach that deals with imaginary problems. It is about the real world and starts with some basic macroeconomic principles like – spending equals income.

We leave the angel-counting to the New Keynesians and their Dynamic Stochastic General Equilibrium (DSGE) models.

Young economists who are interested in MMT should never feel that pursuing their enquiry in non-mainstream terms is inferior to the way the mainstream zealots do things.

That is enough for today!

(c) Copyright 2021 William Mitchell. All Rights Reserved.

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    This Post Has 22 Comments
    1. We don’t write in Latin and use Roman Numerals either, that then require interpretation into the ‘common tongue’ via some ‘priest’.

      MMT is the economic bible in English. It is a revolution of Lutherian magnitude.

      It is the start of the economic reformation.

    2. It is all about power and the power dynamic and more like a religion than a science. They operate in the exact same way as the vatican. They can be bought and sold like many priests before them.

      The exact same way a political party and a church needs to find funding so do universities and economists. Right there is the problem. It is very interesting they didn’t have banking In their models when they’ve pocketed enough money from them.

      Reminds me of 3 centuries of Pagan persecution and how the church built its power either beside or right in top of Pagan sacred places and hijacked their calenders. Once established the real destruction began on the back of stories and fairy tales that they are still trying to back fit without any success today. We just need to fit a lag in their somewhere or a time machine.

      There is an invisible man living in the sky. Who watches everybody and everything they do in every minute of every day. The invisible man has a special list of 10 things he does not want you to do. If you do any of these 10 things he has a special place for you. Full of fire and smoke and torture and suffering and burning where the invisible man will lock you up for eternity.

      But he loves you. He loves you but the invisible man needs your money. The invisible man always needs money. The all seeing, all powerful, all knowing and all wise somehow just can’t handle money.

      That’s the post Keynsians in a nut shell. They can’t handle money but can handle Conch shells. Conch shells that have been dropped from of a helicopter.

      So what do we do ?

      There must be enough of us now to stand outside the IFS, the BOE and the BBC in peaceful protest. Handing out MMT books. 10 people is no good a 100 thousand on the other hand. We just need to get organised.

      We missed a trick at Cop 26. We should have been there handing out MMT books to the youth who are there in large numbers. Rather than engaging in Twitter fights when they are never going to admit to anything in that public space.

      We need to raise taxes to pay for X- has been the backbone of every Cop 26 debate and every privatisation in recent history. It’s imperative we take that tool away from them before they carve up the NHS.

      Once we take the we need to raise X to pay for Y from them. They have nothing their whole ideology falls apart. Peaceful Public protest in large numbers will be the only way to do that. We’ve tried the other way and they still control the narrative and framing.

    3. Derek, we disciples proscelytise in our own preferred way. This oldie uses Facebook and Twitter to butt in to any relevant conversation, especially where young people are present.

      Here’s another idea for UK: a stand at the Labour Party conference. The cost this year was about £2000. Our Labour Land Campaign finds this very useful and every year more people seem to know something about LVT. The conference next year is in Liverpool, which adds costs. However, I doubt whether it will happen as we will be involved in a general election and maybe the end of the Labour Party as was.

    4. 100.000 people protesting outside national central banks…now there’s an image.

      I wonder how many copies of ‘The Deficit Myth’ have been sold. That might give an indication of the number of potential protesters.

    5. Meanwhile Janet Yellen was today informing us (at Glasgow) that governments are strapped for cash, so we need private sector investors to deploy their $trillions.

      No doubt a giant carbon tax should do the trick?

      But she is forgetting that the private sector needs profits……. which will be progressively reduced as more free sun and wind fuel the globe.

    6. Neil proclaims that “MMT is the economic bible in English. It is a revolution of Lutherian magnitude.” And that it is. Perhaps an even better religious analogy would refer to the early Jesus movement of Second Temple Judaism vs. the Roman Empire. Why? Because both the original gospel (lost by marriage to that empire) and MMT (so far kept unsullied by people like Bill) have to do with the best in the human spirit and its social expression. I’ve said it before and I’ll say it again. Fritz Schumacher’s tagline to his famous “Small Is Beautiful” fits MMT to a T: “Economics as if People Mattered.”

    7. I don’t see the point in doing trivial statistical regressions on socially generated variables in a complex financial system, beyond some basic benchmarking.

      Yet that is always the complaint: “You aren’t doing statistical regressions, prove it!”

      To me, science is primarily about a coherent set of first principles and observable facts, any statistical work in a complex environment, depends on the specifics of that environment, and can change if something about that environment changes. This could be policy changes, such as the lucas critique discusses, but it is also much more broad.

      Human culture and our institutions are complex, and are best modelled through rational analysis, by reference to time series data. There is a place for using statistical analysis to tease out causal relationships, but it is primarily in public health, where treatments and prognosis are easy to measure, but hard to establish causality.

      Rarely do economic relationships work like this. Treatments are not typically things we can run “experiments” with, and even if we can, you are typically talking about nation states, so sample sizes are necessarily small, with many confounding variables. But unlike public health, where we can’t reliably audit what is happening in the human body at a detailed level, there is plenty of information about the internal mechanisms of economies in the form of time series data. Imagine if we were able to track people’s health like this on an ongoing basis: things like blood sugar, white blood cells, antibodies, etc.

      At a certain point, the mechanics of a phenomenon become sufficiently complex and nuanced, such that statistical analysis is not a good tool, it is much better to simply have an intelligent observer who can filter out relevant and irrelevant information, and while there can be cognitive biases, cognitive biases can be corrected for.

      You would not use markov models to play chess, or analyze chess positions. But economists regularly do exactly that with the economy, use an unrealistic simplification, only because it is tractable and it allows them to be more methodological about their analysis.

      Well, being methodologically structured, is not the same thing as being accurate or even accountable for your accuracy. This is the huge flaw in economic method these days. Yes, we can do some intricate statistical work like card krueger, but it is best used for informing people to analyze many complex factors together. I am worried that with the advent of machine learning, perverse metrics and incentive structures will get amplified. If you do not correct for fundamental errors or invalid thinking, machine learning will typically not give you what you hope to find.

      Mainstream often complains MMT has “nothing new”, when in reality, the truth to that is, that they have been on the losing side of post-keynesian debates for nearly 100 years now. So if it is true that most of MMT is not new, it is also true that it is accurate in a way that economists can no longer ignore, as they did to early post-keynesian critics. Because of MMT’s clarity and simplicity, it forces them into preposterous positions and incoherent defenses– and that is something they hate. So they will pull out whatever knee-jerk ill-conceived ad hominem defenses they can, shout loudly, and then ignore you. I must admit, not all mainstream economists approach this with such bad faith response, but it is much more common than you would expect if MMT were simply some fallacious deviance.

    8. Following on from Derek Henry above (love it BTW), I am reminded of my own religious experience when World Youth Day was in Sydney in 2008.

      At that time I worked for a large architecture practice in a satellite office right on Oxford St, Darlinghurst – the centre of the gay golden mile (our Mardi Gras parties were legendary). Outside our door there were hordes of catholic youths strumming guitars and singing hymns, all very wholesome and lovely.

      So I bought a t-shirt with ATHEIST in big black letters on the front, and whenever I walked up the street to get lunch or visit the main office I would smile and wave and say “welcome to Sydney” (I may have minced a little too).

      It was like parting the red sea.

      They did not smile and wave back, they would literally part to the sides of the footpath and avert their eyes. It was a fascinating experiment, and my memory of it leads me to a question that is actually on-topic: when mainstream economists write factually incorrect critiques of MMT, is it a deliberate/malicious misrepresentation of MMT to suit their argument (“shitposting” in internet terminology)? Or, is it more to do with averting their eyes – a wilful ignorance born of their devotion to their discipline?

      I guess we can generalise based on the writer. The high priests of the mainstream definitely show elements of religious-type devotion, especially when they toss in some moral arguments about the danger of governments believing they can spend their own money. On the other hand, a bank economist who has made big bets on the current system? Probably shitposting.

      As for proselytising our own cause, I can offer the following: Somewhere in between high school debating and middle-aged involvement in local politics (greens), I have learned that you cannot win an argument against bullshit. This is a fundamental issue for the left, but also for anyone pursuing MMT from any political background.

      We cannot oppose and argue against the mainstream. We must build our own narrative and frame the debate on our terms, then watch the mainstream contort their arguments to oppose us. It is the only way to win a debate.

      (sorry for all the shits in that comment, this post has got me stirred up!)

    9. Kuhns book is a good read and very important in the philosophy of Science.
      However, like Semmelwiess it is often used to justify positions outside the mainstream irrespective of their validity. The good news is that the attacks mean that the mainstream recognises a serious challenge.
      The use of mathematics and numbers expressed to an absurd precision to add a veneer of authenticity to a silly analysis is widespread in many fields and because most have lost or never had mathematical knowledge, the analysis is often not challenged. The Covid modelling over the last couple of years is just one example. Recently someone sent me some research about predictions of interest rates where the confidence intervals narrowed the further out the analysis went – a good demonstration of group think but a hopeless use of maths (the predictions were a summary of individual guesses..). This was a great example of the phenomenon Bill is talking about.
      My favourite slide to illustrate this :
      Blood circulates * Harvey * p<0.05

    10. I strongly agree with Bill Mitchell’s post above. I would add that there is no such thing as economics per se even though the term “economics” is a convenient shorthand. Economics always and everywhere is political economy and moral economy as well as real economy. Simply, we can say economics always involves political and moral decisions as well as some objective and some formal decisions.

      The history of economics and the history of economic thought are crucial subjects as is comparative economics. To think that mathematics can somehow sum up or carry the essential essence of economics is as absurd as to suggest that sociology, political science, moral philosophy and history could all be expressed wholly in the language of mathematics. Mathematics is a specialized language with specialized uses. Its pure and applied and uses are only valid under properly and tightly specified conditions.

      I would bore people to tears, and perhaps alienate them, if I went too far into such matters here. I refer to the “ontology of the real and formal” in economics. Such matters properly belong in an introduction to the ontology of economics. Suffice it for me to say here that the ontology of much (though not quite all) conventional economics is fallacious. The ontology of MMT is sound.

      Ontology is a much misunderstood and maligned subject, IMHO. Ontology is not just about dogmatic and speculative metaphysics. Far from it. There is also a large part of the subject which involves the ontology of real objects and formal objects: what they are and how, in terms of method, they may be validly combined in theories. Even more importantly, a comprehensive ontology of real and formal objects and categories clearly warns us how to NOT invalidly combine real and formal objects in a theory. There are valid ways but they are limited and must be carefully applied.

      Failure to make the ontology of a discipline explicit, continually explored/extended and subject to proper empirical testing can result in serious, indeed catastrophic errors. Conventional economics is a clear and egregious example of this problem as were, in their time, alchemy and the humors theory of medicine. If the ontology of fundamental objects and processes in a discipline is fallacious then everything will be wrong after that. The humors don’t exist thus any and all theories based on humors are nonsense.

      As Bill correctly states, the basic existents posited for conventional microeconomics simply don’t exist, meaning they are not empirically detectable or recognizable. A theory built on non-existent fundamentals is nonsense of course. Bill is actually being an empirical ontologist when he says this though he may not thank me for pointing it out. I think bad ontology of the dogmatic and speculative variety can put people right off the entire subject area and then one has to be very careful in re-introducing it, as I am discovering on multiple political economy sites.

    11. From a recent tweet thread

      Great commentary on economic methodology by @macrofoundation

      http://bilbo.economicoutlook.net/blog/?p=48613#comment-73510%5B…]

      But I still think this endless reference to ‘science’ in figuring out what economics’ methodology should be is a status play

      I think economics is about imagining alternative improved futures (both tweaks and much larger changes) in the way medicine and engineering does the same.

      But where engineering is physical and a great deal of medicine is physical (though some is social and psychological), economics is 100% about social phenomena.

      So a better metaphor is a football coach.

      Srsly

      https://clubtroppo.com.au/2021/10/16/science-is-about-the-universe-that-is-design-is-about-the-multiverse-that-might-be/

    12. “We must build our own narrative and frame the debate on our terms, then watch the mainstream contort their arguments to oppose us. It is the only way to win a debate.”

      Correct. We need a “What can MMT do for us” proposition.

    13. Yes, Neil, we must emphasize what MMT can do for us…and the why or how will follow, the appeal of the “what” motivating the understanding of the “why/how.” It’s hard to get people excited about a lens. What CAN get them excited is what can be seen through it. So how about a detailed, concrete, compelling 21st Century portrait, along the lines of Edward Bellamy’s stunning late 19th Century vision, of what a currency-sovereign society would be like, feel like to live in, were it to use MMT principles to fully serve both people and planet? While MMT has its proponents and expositors–Bill surely being among the best–it awaits its poet, an artist who can paint in words the portrait of that better, more beautiful world MMT reveals to be within our grasp.

    14. I can’t help but come to the conclusion that the slow support by those who slowly adapt their views to shift towards recognising that MMT has always been the system – under a floating exchange rate – is because Bill being the brainchild for recognising their light blinding ignorance was not a conservative who was left outside; a lion in the pack of hyenas.

      That’s not to say Bill personally is the problem (that’s just ridiculous and I don’t believe that), but by snapping us out of the hypnotic, religious, state that we’ve been induced to remain in, we’re now able to understand just what the hell happened as we look around. That the invisible experience was a methodically planned and executed process.

      Thank God, that as the ultimate whistle blower, he was able to use technology to divinely pursue spreading the word to so many of us, so that we can learn how to intuitively and intellectually see how to change things for the better; a true road scholar!

      It’s amazing to see so many disciples, prophets, neighbours etc. committed to realigning the churches view.

    15. I think your blog is brilliant professor, a pleasure to read. Often I Have heard the phrase: An increase in minimum wages will have a detrimental effect on job creation (especially in election propaganda). It is encouraging to see that the empirical research that makes this thinking obsolete and unfounded from conception has gained the recognition of: The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2021 [LINK EDITED OUT] Keep up your great work Bill.

    16. Replying to @Esp (Nov 4, 2021 at 12:15):
      You wrote: “Today’s blog reads a bit like “I can’t specify a better model”. Surely, that’s not the message you are trying to get across?”

      The pertinent question is why would you want to specify a “better model” if you know mathematical modelling is inapplicable? (Inapplicable that is, for the questions you are asking, such as power relations between labour and capital, and government decision-making that lacks all knowledge of the real world monetary system.) You need to find restricted domains for mathematical models in macroeconomics, if you do not provide restrictions your models will never be useful except by sheer fluke.

      I do not know what Bill was trying to get across about hopes for MMT models, but what I do know is something about complex systems. They often cannot be modeled using agent based or bottom-up approaches when emergent aspects arise. Banks and governments are highly emergent. They require a top-down approach. But we all know in a many-body interacting system a top-down approach cannot be complete. So you know it is a chimera to search for general models if you have an MMT understanding.

      But that does not mean some modeling cannot be done. Sectoral balances are crude but completely accurate, so you can start from there and follow Steve Keen’s direction. That will get you a long way with qualitative dynamics. If you listen to Mosler you’ll realize a lot of what he talks about can be logically modeled, quite easily, but it is so simple you do not need a spreadsheet for it, and yet it is highly relevant for policy making, if only policy-makers would listen. How good is that? A simple logic model that is highly applicable to real world policy analysis. The poli-analysts should be salivating over it, and yet they ignore it preferring fantasy to reality, almost seemingly solely because the math looks more intimidating. I know form experience heavier duty mathematics doe snot always make you better. String/M-theory in physics for example (completely useless in applications to the real world)..

      Raw econometrics is also not unimportant, while not causal modeling, it is useful for interpreting trends and discovering causal relations. Bill does this a lot. However, what the orthodoxy still get completely wrong with econometrics is in the non-linear fat tails regimes, where conventional textbook statistics does not apply (the textbooks actually normally tell students when the models do not apply, but professionals who are not statisticians, just practitioners, tend to ignore those purely mathematical requisites). Such errors are rife in econometrics. John Blatt had some choice things to say in his book “Dynamic Economic Systems” on this topic.

      An example is in pandemics: the social averages are fine to treat with conventional statistics thanks to the central limit theorem, but risks to individuals cannot be treated the same, they have fat tails, so we should not be using correlation coefficients and p-values fro those risk assessments. To accurately compute a measure (say average risk) from an underlying fat tail can take 1E15 Monte Carlo trials when for the same accuracy from a gaussian would take only 30 trials. If one uses 1 million or even 1 billion MC trials, thinking this is good coverage, but really the real world you are modeling has fat tails, then the error in estimation can still be huge then, your risk assessments might be off by up to 50%. That’s the sort of order of magnitude of errors when economists use standard methods failing to realize they are invalid.

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