Economics, sociology, anthropology, history, psychology, and the other social sciences are currently taught in an unorganised manner. The undergraduate degree in any of these disciplines consists of about 20 separate courses that each differ markedly from the other 19 and that are unrecogniseable of those of the other disciplines. The language used in each course is different, the perspective on the same events differs, and there are deep contradictions in any course with what is said in the other courses.
The ways things are taught are usually also very old-fashioned and dull, with little use made of the possibilities of virtual reality and field trips. Pontificating teachers dominate the courses, with little of the knowledge truly reaching the students.
It can be done much better. I think it is possible to teach students the actual content of all the regular social science undergrad courses in one curriculum in a manner that they understand the material and see the interconnections. It can certainly be done for the relatively bright students, say the top 30% of the usual students found in the West.
The biggest change needed is to teach the material in terms of basic patterns, with more complex arguments taught later as combinations of basic patterns. Another change needed is to enforce a single language on the entire curriculum. Finally, what is needed is far more use of virtual reality-teaching and field trips so that students experience the phenomena they are meant to understand, unlocking their visual acuity and emotional skills as learning tools. Students should learn with their whole being, not merely with their abstractive capacities.
What do I mean by basic patterns and how would one mobilise more of the mental faculties of students? Let me give three examples from different disciplines to illustrate the immense similarities between them and how it can be presented.
A basic sociological pattern (eg Durkheim) is that of comparative advantage: a group of individuals can produce more if they each specialise in what they are relatively best at. One does not need to introduce exchange or prices to make that point, because those are other patterns. The basic pattern of comparative advantage is that there exist different productivities across entities.
This pattern should be taught in a layered manner, from exceptionally simple to incredibly complex. In the simplest form, one would have two people with comparative advantages. Students can learn to recognise it in a game, where the only object is to maximise some notion of joint production via the allocation of time. Once students have experienced this possibility, one can expand the pattern to talk about comparative advantages between countries, between the countryside and the city, between rulers and the ruled, between parents and their children, between partners in a marriage. The various forms of comparative advantage in various realms can be experienced in a virtual reality game, as well as by students re-interpreting their experiences as social beings.
Once students ‘get’ the point, both at a cognitive and emotional level, one can then put this into maths and statistics (which can become incredibly complex very quickly). By doing it this way round, mathematics is put in its proper place in social science: as a codification of what one knows by more basic means, not as the original source of the knowledge. The next step is to then combine the comparative advantage pattern with other patterns, like exchange and prices, or the notion of prior investments that create comparative advantages over time.
A different pattern is that of abstract ideation wherein the approach to any social problem is to imagine some possible solution that comes with causal pathways as to how to get there. This act of the imagination has a huge number of examples, but the key thing is that a problem is encountered that requires a leap from where one is to where one thinks one could be. This pattern too can be taught in an experiential and layered manner.
A simple version of this is literally that of a journey with an obstacle (a tree over the road, a stream) where an act of the imagination causes one to jump over or go around the obstacle, using implicit knowledge of both the road and the obstacle. A less simple example is of imagining a paddle to get a boat to move from one end to the other. Another example is to imagine redistribution to solve poverty. A less simple example again is to imagine a god to which one can appeal to get it to rain (imagined solutions need not be right!). All these examples can be made experiential, enforced by field trips and actual conversations with people experiencing problems and telling stories of supposed solutions. By going over selected examples one is effectively re-imagining social science as a whole, breaking it all down into quite simple patterns.
Note that for this pattern one does not engage with the supposed solutions or even the supposed problems: it is the act of imagination that is itself put under the microscope, put into stylised and personal experiences, and eventually mathematised. For instance, the idea of a perfect market or a productivity possibilities frontier are classic examples of imaginative thinking in economics, but one need not look at either in any detail to ‘get’ the idea of a leap of the imagination from what is to what could be.
A third example of a pattern is increasing returns to scale, ie that more can be produced if resources are bundled towards the same end. This too can go from very trite (cooperation begets more output) to more poignant (a unified band of warriors can subdue a much larger population and get all the benefits). By drawing out how very complex historical and societal processes involve very simple basic patterns, such as that the state at heart can be seen as a monopoly of violence, unifying themes between the social sciences are brought out that are currently known by insiders but that students will generically never see.
To learn to see basic patterns in history, current institutions, and in different social situations can be practised both via virtual reality games, as well as via field trips wherein students get to experience what it is like to be swept away by the crowd, to feel powerful, to be bewildered by hyper-inflation, and to be afraid of the unknown.
More complex phenomena and ideas can then be gradually built up as combinations of basic patterns. A well-functioning market for instance is a combination of various things: prior production by many sellers, planned consumption by many buyers, mediated exchange, visible price formation and implicit formation of knowledge about quality and trustworthiness. Each of these is a different pattern that can be seen in all the social sciences and that first should be studied and experienced on its own before adding them all together in an actual market. By letting students see the complexity of something like a market, they would also understand why it has proven too difficult to actually mathematise markets and that yet the discipline of economics relies heavily on market-derived thinking by simply presuming properties associated with markets in various situations (i.e. law of one price, zero-profits, etc.). Students would thus also start to see the quasi-religious elements in the various social sciences, not as a failing but as the optimal approach to complexity. Rather than present quasi-religious elements as a critique they would learn to see such elements are normal and present in all social sciences. There would thus be a liberation from false pretenses.
The teaching of mathematics at primary schools, particularly the Singapore model, now follows exactly this line of thinking: from simple to complex where one first really gets familiar with each basic pattern before combining the patterns. Children are for instance drilled into a lot of multiplications to ‘get’ what multiplication means. When they are then taught about exponentials they first extrapolate from their prior experience of multiplication to recognise that exponentials look a lot like a sequence of multiplications, though over time they learn it truly is a new pattern that then itself becomes the basis of further explorations.
Also, the Singapore model of teaching mathematics coopts the visual memory of students by using pictures, as-if situations, and natural-looking objects to teach the basic patterns. Many of the basic patterns of mathematics can be experienced, which makes it far easier for students to ‘get’ them and then to hold onto them. In the case of addition, multiplication and division this is trivial. But it is now also done for the normal distribution (which emerges for instance when one looks at the dispersion patterns of kicking a ball) and for logarithms (which emerges when one looks at increments in perception).
We should teach social science in the same way but coopting even more of the mental faculties of students, which would make seemingly complex and mysterious phenomena like love and religion look almost trivial once properly dissected.
Why don’t we do this already and what are hence the barriers? The biggest problem is the prior teaching and career incentives of the social scientists currently doing the teaching.
Social science has become increasingly specialised such that there are now thousands of little territories dominated by small groups of scientists who each write their own textbook about their supposedly unique subject area. This territorial game comes with the incentive for each little group to invent their own language or else to invent a very different meaning to the same words used by others. In the language of first-year economics, what each group does is to erect entry barriers to their basic knowledge so as to increase the monopoly rents they can then extract.
The current social scientists are not going to let go of their monopoly rents easily. In the development of an integrative curriculum they will complain and obstruct. They will resist the unification of language; they will resist having to re-think their subject in terms of simpler patterns; and they will only engage with more modern and immersive forms of teaching if they feel they have to.
The more famous the social scientist, the more of a problem they can be expected to be because the more they would have to lose from the de-mystification of their subject areas. The less famous social scientists have less to lose, but of course are usually less able to do the work of dissecting what is known across many areas into much simpler patterns.
A unifying approach to social science is potentially a huge boon to the university that gets it right, and as such something that interests the hierarchy. University administrators are used to having to deal with the egos of scientists and will thus easily recognise their inevitable whinging. Yet, on the other hand the administrations can fear the risks involved in field trips and immersive experiences needed to have students experience high-emotive phenomenon, such as the power of a crowd or the lure of religion. Scientists will on the other hand fear this much less and be rather intrigued by the challenge of creating the right environment in which such phenomena can be made experiential.
So one should expect both scientists and administrators to have problems with the approach sketched above, with the scientists fearing additional work and the loss of mystique whilst the administrators fearing the potential results of actual learning, i.e. students who have truly been challenged and changed.
What would it take to organise this? The virtual reality challenge is quite difficult. I happen to know that one attempt in this direction (Playconomics) took the creators 2 years of their life to program just one course. To put 10 courses into this kind of format would thus easily cost 20 work-years of high-end programming, i.e. it would easily take a team of 5 good programmers 4 years.
One should also not underestimate the task of dissecting current social science into more basic patterns. Based on my own experimentation in this direction over the years, I estimate it would need a team of about 5 good social scientists from the different disciplines incrementally going over the material together and agreeing on a common language and a common view of how the more complex phenomenon can be broken down into shared simpler patterns. They should be able to crack it in 2 years and then optimise the teaching in 5.
Then there is the experimentation with formats and field trips and whatnot. It will take a few years to get that right, costing a lot of effort in terms of organisation.
So I think it would take a team of roughly 15 people some 5 years to develop this and set it up as a 3.5 year set of 20 courses. If one adds material and facilities to this, one is hence talking in the range of 10-20 million dollars in terms of developmental costs. To do the experimentation one would furthermore need the active cooperation of an existing education institution with reasonable students being taught the initial courses.
Once there is an integrated curriculum, it is easy to see how it can evolve and spread: it would become like a commercially-owned internet platform for which any team in the world could build additional ‘apps’, where new developers would use the same language and the same set of basic patterns. Innovation would happen in terms of new areas, new complex patterns, and new teaching methods.
The commercial package as a whole could then be marketed and managed to reach millions of students each year who would all do the same exams, replacing the ridiculous situation we have now where each university maintains its own virtually identical curriculum in terms of content. The university system as a whole would thus be made much more efficient and profitable by getting rid of the immense and pointless duplication currently in the system.
A professionalisation of social science can also be expected to transform universities and the academy.
In terms of universities, we would go to the situation where there are a few universities that develop whole integrated curricula like the one I sketched above, whilst the rest become franchises in terms of content. As with car-manufacturers, we should get a few highly experimental top-end universities that compete with new designs and philosophies, ruthlessly experimenting on their own students and offering suites of products for external local tastes. The rest should specialise in providing feed-back to individual students, organising their own field trips, and adding a bit of local content, but otherwise simply teach the content of the leaders, branded as such.
The academy would also be transformed because a unified teaching approach would go a long way to break down the unnecessary silos between the many sub-disciplines. The students who are taught the unifying language and set of ideas would simply no longer respect the barriers to entry between groups. This should make it far easier to communicate and learn from each other. It would then become visible how little real innovation there has been to the basic curriculum in some areas and how much duplication there is in terms of research and ideas between areas. In turn, this should down the line lead to far fewer social scientists in academia, with perchance a growth of them elsewhere, such as in policy institutes and for-profit enterprises.
It can be done and embryonic steps in this direction can be seen across the world by different teams and individuals. The CoreEconomics project for instance enforces a single language and the Playconomics project uses virtual reality to great effect. Yet there is no attempt anywhere to truly scale all this up and to destroy the silos that constrain social science. The key problem is not so much the intellectual challenge or even the costs, but the current incentives of both scientists and administrators.
- note to self[↩]
Generally speaking, it’s a ‘yes’ from me.
Maybe you can get Charlie Munger to give you a billion or so in his will. This is roughly his approach.
James Watson of DNA fame towards the end of his career exclaimed: ‘Molecules are real. The rest is sociology.” By “real” he meant that molecules of a given kind are identifiable and measurable [precisely independently of assigning to them any role in a complex, especially any functional role in processes such as nutrition and procreation. It is not that these roles are subjective, but that they are flexible and contextual, full of redundancy that permits adaptability.
At the human level her n cognition and emotion come in there is a sharp break from the basic assumption of the physical sciences that nothing really real can be created of destroyed. There is jut so much energy, so many particles. But new knowledge is continua; y been created, together with new means of communication, Unlike food or space that are diminished by being shared, knowledge, emotions and formas of organisation are usually enhanced by being shared. Un sharing such things we create new identities for ourselves as scientists of football fans that change the shapes of our lives.
For a long time we have assumed that all our activities have a single ultimate end, and the great religions tried to say what it is, while ideologists have tried to persuade us that that is a prescription they can implement by suppressing diversity in the name of certain abstractions that are both scientifically and humanly adequate.
Meanwhile the evolutionary process is directed towards inventing new forms of organisation of the basic bits it plays with, oblivious of how the outcome of its gambling affects us. What it produces for us is ecology of organisms more or less adapted to each other in a host of different ways. There is every reason to think that while we need to communicate in our search for understanding, there is no one language into each all our knowledge can be translated without loss or some important content.
“there is no one language into each all our knowledge can be translated without loss or some important content”
Sure, but we still teach kids the alphabet, then teach them how to make words, then sentences, then paragraphs, and then write comments on blogs. Also, no redundant letters in the alphabet!
What’s your point John? One cannot improve on any current teaching?
Ȋ Ηఎህદ ಗစ ႞Ꭰᗕᚣ ឃḣᴀṮ Ύ⊙⊍ ⫙ⱸㅅ⼌
(in case that doesn’t come through, it’s unicode gylphs that look like “I have no idea what you mean”)
I think it might be useful to have at an early stage “how will economics change to reflect this new approach” and “whose language should we start using”. The key question will be “what do we give up in the name of a standard base taught to all students”. Your “three basic concepts” are someone else’s “three complete irrelevancies” and their “dominant discourse, patriarchy and privilege” are your “oh god not again”. I suspect it will actually be “one core principle from each of 250 major specialties“, rather than “three core from the five areas I care about”. If you think “economics” is broad, check out “geography” or “psychology” (some might argue that economics is merely a branch of one of those disciplines).
To some extent this can be simpler than I think you imagine, because there are a lot of orthogonal concepts and even disciplines. Insofar as, say, religious studies intersects with economics there’s not a lot of conflict at a discipline level so standardising approaches and language will require very little change. Whether there’s any benefit is a different question.
My experience, as an engineer flitting around doing interest subjects, was that there wasn’t a huge amount of cross-over even when I went out of my way to look for it. What we did have was multi-labelled courses where one group would contain (say) sociology, gender studies, teaching and law students all getting credits in different departments, but using the same lectures and tutorials and occasionally the same assessment. Perhaps I benefited from an early example of this cross-disciplinary approach? Or, dare I say it, that you lack exposure to something that’s commonplace outside your “supposedly unique subject area” :)
Note that the engineering school officially and explicitly encouraged that kind of external course-taking, but there was very little uptake and significant complaining about even the very limited “6 week introduction to each of the other four engineering departments”. Making the engineers learn about criminology would have caused outrage.
Systems dynamic paradigm.
Start with Loopy by nicky case in kindy.
Move to dynamicland ( has to be seen to be believed) as classroom.
Extend stock flow feedback diagram relative and relevant to curriculum.
Any system. In 1992 K attended Cherrybrook High and delivered classes intro and stella sd software. Models from physics to Hamlet.
Eventually emergent behaviour will emerge – yr 6-7. Yr 10 chaos and bifurcation. yr 12 the depth of models and intuition of students imho will produce actual real world admin models. Reverse the spreadsheet. .. models to generate numbers after scenario in model. (Any politicians listening).
Your costing may be correct. In the 90’s I worked with 2 ‘engineers engineers’. One had a working memory which to my relatively small mind, had no bound. Standing in front of 5-10 vertical domain experts he would construction a basic mental model map, annotate with positive negative feedbacks, have values yelled out and at an answer point he also knew the expected values bound – flooring most in the room. He did f1-11 modelnand was able to show within 2 days ( a complex system!) That the wing commanders had ‘polished their brass’ before leaving. Our ‘readiness’ (requirement for defence ops funding) is based on this. Further, after completing whole dynamic model ( @45% reduction took 20+ A0 sheets to print – I only saw it once as I didn’t have clearance) woke at 3am one morning, roughed up a board game, had his family play it and wasnable to present it later that week. Exceptional yes. But just a 10yr learning curve. Hi Mark.
Loopy and explorable explanations.
https://ncase.me/
Brett Victor
http://worrydream.com/
You MUST see classrooms in the future as dynamic lands…
https://dynamicland.org/
Best learning talk ever, logo creater, turtle robot. (I hope lego pays a squiilion in royalties)
https://en.wikipedia.org/wiki/Seymour_Papert
And the book – has this ever been surpassed?
https://en.wikipedia.org/wiki/Mindstorms_(book)
Mark won PM’s innovation award for fleer doctor.
https://www.linkedin.com/in/mark-heffernan-4810451
https://www.iseesystems.com/consulting/
You are missing one part of the equation: The motivation of students. The reason students are learning less and less is because many simply want to get through and pass. Many people like simple things and not complex things. This is why people like facebook (simple text and a few pictures), and not all of those 3D real-life worlds. And this is why they like 6 points per Powerpoint page to remember, and not an interesting story to consider.
This means if you actually teach so they learn something (which requires thought), everyone who doesn’t want to learn something will complain and these people won’t be balanced out enough by those who actually did want to learn something when they fill in your teaching survey, and hey presto, management will force you to teach to the lowest common denominator. The Australian government will then enforce this by taking these surveys as teaching quality (despite being negatively correlated with actual learning, even in the short term let alone long term!).
How many students are like this? Well, in my state of Victoria, all universities except two (Melbourne and Monash) will take more or less any student in most courses (including those that failed Year 12 via “special entry” which isn’t so special considering the number). So the majority of courses are doomed to bottom fishing and teaching to those who don’t want to know.
The other thing is how much they have learnt before. If you take anyone in, some won’t understand e.g., really simple graphs (many in fact — they probably haven’t done maths since year 9), and what you might fascinating won’t be to them (how does competitive advantage relate to the Kardashians?..).
So your course would be great for some places; but not e.g., most places in Aus. I find that disappointing, but as far as I can tell, that’s the way it is for now.
The other thing which has gone the wrong direction is your second suggest that you teach simple things before complex things. If you did this, how would students have a choice to do any subject they want anywhere in their degree? You would clearly be trumped twice over by marketing.
yep, right on both counts. No way this would work in a regular place in Australia where you have to compete for students across departments in the first year on the basis of who promises the students the most outrageous returns for no effort.
So yes, you need some degree of intellectual hunger amongst students, which is in short supply in Oz. A commercial mindset is not necessarily in the way given the potential returns, and once set up one can introduce lots of choice in this system, but you’d certainly have to shelter it while you grow it.
There is a reason nothing like this exists anywhere: the system evolved disorganised with incentives for more disorganisation. Yet, the importance of more general pattern-based understanding is arguable greater than before precisely because shallow is the new normal, giving those who learn more useful stuff a great advantage.
The confusion due to using different words for the same subject is most significant as is a lack of presentation of how separate subjects are related. If there was a central general subject (possibly in macroeconomics) to which a number of branches of ancillary subjects could be attached, this would greatly ease the amount of confusion as to where they are all related. Such a suitable central or trunk reference would then allow and encourage a more consistent use of related words.
What conrad said. Was John Dawkins the most malevolent influence on tertiary education that Australian has ever had? Discuss.
Ken possibly, on the other hand I understand that Dawkins himself didn’t expect that his system would run on so unchecked and unrevised for so so long.
I would dam him for his unforgivable naivety.
Universities should be incentivising professors to do this, rather than the umpteenth publication in a narrow field.
Senior professors’ roles should primarily be about the public good, whether teaching, mentoring, exploring links to policy or the ‘meta’ issues of the discipline. Instead we often see the opposite in today’s environment — professors are expected to publish the most, and, compounded with selection effects, professors are least likely to worry about anything unrelated to publishing. We complain ironically about out students only wanting to pass, yet many academics only want to publish.
The obvious reason publications (and grant money) are incentivised is that the biggest attractor of students to a university is prestige, and prestige is almost entirely based on research reputation (the only exceptions I can think of are the top-rated US teaching colleagues).
For example, you could have the best courses on Earth, but if your name was Southern Cross University, you would get vastly less students than if your name was Melbourne University. So that’s actually what students want, and universities respond to this.
The other reason people are not as worried about teaching as they could be is because, at least in Australia, the main form of evaluation (student surveys) is either not or weakly negatively correlated with actual learning. So if you were to do a good job in terms of actual learning, there is a good chance you would be punished for it. Doing a bad job in some ways also gets you praise.
It reminds of a colleague of mine who used to be a primary school teacher decades ago. She commented: “I remember that once upon a time, inspectors used to come around to make sure the kids were happy because you were doing a good job, not giving them lollies”. Of course in Australia, the adult equivalent of giving them lollies is highly praised. You could get a teaching award for it.
Conrad
We all, in our various ways, know that the current setup is total merde .
Any ideas as to how-what could be, practically, done about it??
There are any number of small changes — Paul Fritjers has previously complained about this previously in some posts (I could lists a page of small things, but I’ll resist)
At present, the biggest general problem is that Aus universities have gone too far down the road to corporatisation. This is really the government’s fault as they essentially forced it to happen. So you end up with generally (but not always) failed academics in higher level management pretending to be business managers, and paying themselves huge amounts for it (more than the PM of Australia).
They then think of endless KPIs, surround themselves by huge numbers of other fat-cats with their own KPIs, and it creates bizarre incentives and huge waste. I think where I work there are at least 20 PVCs/DVCs etc. So if each one costs 1.5 million including staff costs, that’s 30 million of waste, as well as huge opportunity costs (each one needs to make themselves look important by wasting other people’s time).
The obvious problem here is that there is no simple way to evaluate them, as the main factor that determines how good or bad a university happens to be is prestigious, and this changes over decades or more. Even when they have poor ideas that costs tens of millions, it may not change anything obvious for years. Thus they are not like business managers in the sense that they are accountable to a bottom line or similar.
Again, the end culprit here is really the government. They want universities to make money, rank high on international tables, make students happy on outcome surveys (c.f., learn something), pretend to be corporate businesses, and so on. They then think of rules to force them too, and all the perverse outcomes follow. It’s not like these problems are unknown.
For example, the fact that happiness surveys don’t actually tell you much about teaching went all the way to the Canadian Court of Arbitration, and they had to accept this. But their universities keep using them. Similarly, most people get at least in part evaluated by the number of publications they write. So areas where people write a lot (and hence often think little) dominate the other areas, including important ones such as some on the cutting edge of technology.
Seems to me that a core problem might be : the student gets the (deferred) debt and the institution gets the money. At the same time the same institution decides who is suitable to be or not be a student.
An other problem is the separation of vocational training funding from the Tertiary funding system- from memory total funding for vocational training is actually a bit less now than it was ten years ago.
PS have you read No End of a Lesson
Australia’s Unified National System of Higher Education
Stuart Macintyre, André Brett, Gwilym Croucher ?
The problem of asymettrical information is a big one for students. It is also why prestige is so important. If you had external testing, then this would help a lot in some areas (it is only threatened when politically motivated by the government now — such as in Teaching degrees). You could also get rid of satisfaction surveys entirely if that happened, because if the endogenous standard was set low, then the actual outcomes would be known.
The problem with vocational funding is that it is also a disaster, and in places like Victoria exploited so much that universities are happy because they realize they won’t be targeted until someone solves that problem first.
I haven’t read the book.
It’s while since we read it the book, narrative wise, didn’t quite engage for me.
However it does contain a lot of well researched history ,and after 30 years it’s as best as I know the only attempt at a systematic review of the system that we have.
It’s hard to think of any other big ticket policy area that has not in 30 years had a major Review.
Just out today: https://www.nature.com/articles/d41586-019-00613-z?fbclid=IwAR2rub2YZul6c1vRvEj-7ZAls226IpKm8RlhHIbBUUDkCloURwKTAan7ih8
Australia’s chief scientist having a go at the mania universities have for quantity (easy to measure, makes a good management KPI) over quality. Where I work, the person who got the university research prize published 40 papers in one year — one of my colleagues noted “isn’t that proof scientific corruption”.
Worship of metrics, is a familiar theme to me, many of our public galleries are obsessed with ‘visitor numbers ‘ – for example some go as far as counting people who use the foyer as a short cut to the shops as ‘visitors ‘ or counting visitors to galleries in other states,cities and towns , that have hung works on loan from that Gallery as visitors.
In the process they often end up completely confusing ends and means.
Who is the academic you are referring to? I am guessing s/he is a medical research grant gate-keeper.
As far as macroeconomics is concerned, this subject is made to appear to be complex and as a result there are various schools of thought and much confusion in the minds of students who are seeking proper knowledge about it. However the answer to the complexity problem is to separate the various KINDS of business transactions that are possible withing the national social system.
I reckon there are only about 10 kinds, see my working paper SSRN 2865571 “Einstein’s Criterion Applied to Logical Macroeconomics Modeling”. With this model captured and defined, one is then in a position to analise and to discover how our social system really works. For more details about my research on this important subject please write to me at chesterdh@hotmail.com and receive a free e-copy of my 310 page book “Consequential Macroeconomics”.
Today macroeconomics is treated as an inexact topic within the humanities, because at a first look it appears to be a very complex and easily confused matter. But this attitude does not give it fair justice–we should be trying to find a better way to approach and examine the subject, in a good way that avoids these problems of complexity and confusion. Suppose we ask ourselves the question: “how many different KINDS of financial transactions occur within our society?” Then the simple answer shows that that only a limited number of them are possible.
Although our society comprises of many millions of participants, to answer this question properly we should be ready to consider the aggregates of all the various kinds of activities (no matter who performs them), and then idealize these activities so that they fall into a acceptable number of more general terms, for the expression of a relatively small number of different but specific social functions. Here, each activity is found to apply between a particular pair of agents or entities—with each entity having its own individual properties. Then to cover the whole social system of a country (excluding foreign trade), the author finds that it takes only 19 mutual flows of money for the purchase and payment of goods, services, access rights, taxes, credit, investments, valuable legal documents, etc. Also these flows are between only 6 different representative entities.
The analysis that led to this unexpected result was performed by the author and it may be found in his working paper (on the internet) as SSRN 2865571 “Einstein’s Criterion Applied to Logical Macroeconomics Modeling”. In this model these 19 double flows of money verses goods, etc., are shown. They are found to pass between only 6 kinds of role-playing entities. Of course, there are a number of different configurations that are possible for this type of simplification, but if one tries to eliminate all the unnecessary complications and sticks to the basic activities, then these particular quantities provide the most concise result, and yet it is presented in a fully comprehensive manner that is suitable for further analysis.
Surprisingly, past representation of our social system by this kind of an interpretation model has not been previously properly examined nor even presented before. Other partial versions have been previously modeled (using 4 entities, by Professor Hudson), but they are inexact due to either their being over-simplified, or in the case of econometrics, much too complicated and almost impossible to follow. These two reasons of over-simplification and over-complexity are why there is this non-scientific confusion by many economists and their failure to obtain a good understanding about how the whole system works.
The model being described here in this paper is unique, in being the first to include, along with some additional aspects, all 3 factors of production, of Adam Smith’s “Wealth of Nations” book of 1776. The three factors of production are Land, Labor and Capital and along with their returns of Ground-Rent, Wages and Interest/Dividends, respectively. All of them are all included in this presentation diagram.
(Economics’ historians will recall, as originally explained by Adam Smith and David Ricardo, the independent functions of landlords and capitalists. The former rent and speculate in land values whilst the latter are owners of the durable capital goods in industry, which may be hired out. Regrettably these different functions were deliberately combined for political reasons by John Bates Clark and company about 1900, resulting in the neglect of their different influences on our social system.)
The diagram of this model is in my paper (noted above). A mention of the related teaching process is also provided in my short working SSRN 2600103 “A Mechanical Model for Teaching Macroeconomics”. With this model in its different forms, the various parts and activities of the Big Picture of our social system can be properly identified and defined. Subsequently by analysis, the way our social system works can then be properly calculated and illustrated.
This analysis is introduced by the mathematics and logic that was devised by Nobel Laureate Wassiley W. Leontief, when he invented the important “Input-Output” matrix methodology (that he applied it to the production sector only). This short-hand method of modeling the whole system replaces the above-mentioned block-and-flow diagram. It enables one to really get to grips with what is going-on within our social system. Subsequently it will be found that it is the topology of the matrix which actually provides the key to this. The logic and math is not hard and is suitable for high-school students, who have been shown the basic properties of square matrices.
By this technique it is comparatively easy to introduce a change to a pre-set social system that is theoretical in equilibrium (even though we know that this ideal is never actually attained–it being a convenient way to begin the study). This change will then create an imbalance and we need to regain equilibrium again. Thus, sudden changes or policy decisions may be simulated and the effects of them determined, which will point the way to what policy is best.
In my book about it, (see below) 3 changes associated with taxation are investigated in hand-worked numerical examples. In fact when I first worked it out, the irrefutable logical results were a surprise, even to me!
Developments of these ideas about making our subject more truly scientific (thereby avoiding the past pseudo-science being taught at universities), may be found in my recent book: “Consequential Macroeconomics—Rationalizing About How Our Social System Works”. Please write to me at chesterdh@hotmail.com for a free e-copy of this 310 page book and for additional information.
Hi David,
thanks for engaging. Without putting in a lot of time, I of course cannot really comment on the ’19+6′ model of the macro-economy you envision, but I applaud the basic reductionist approach that tries to be as close to actual events as one can within an abstract system. I think that is the way to go, though I note you essentially here talk about exchange, production, etc., which doesnt easily get at crowd-phenomena (over-optimism, hyper-inflation, trust breakdowns) that one would certainly also want to include so it would have to be more than 19+6.
I guess if we were doing this together, we’d try to see how many of your 19+6 I already have in my list and how many I could further steal from you to include the main additional explanatory power you might offer. Or vice versa, I dont actually care.
David Harold Chester says:
“derived from first principles, using the absolutely minimum necessary amount of analytic logic.”
Fantastic to hear… seems rare in economics and almost impossible in social sciences barring statistical analysis.
“Two vital features of the procedure for portraying our society are that it is to be modeled by using a diagram, and that it is in the form of a system.”
And thanks again, a diagram, Feynman being famous for his diagrams, and a system metaphor being non reductive. Bravo.
I need diagrams. Show me a formula with log^10 and I wince. Show me a 3d space with trajectories and link behavior over time and I get it.
As can be seen from my tardy comment above – on mobile in sun whilst waiting for my child (thanks for posting NG) – I fell in love with system dynamics as I was able to approach expert domain knowledge with causal loops, stock & flow diagrams and then “drive” the model to test my usually wanting knowledge. A supurb way imho to do anything from macroeconomics to hamlet – yes even hamlet. Kids love to see how, by say effecting Prince Hamlet revenge factor or Hamlet’s mood and behaviour, they can alter events later. I have delivered class at Cherrybrook Hign in sydney of both preditor prey model and hamlet. A long time ago – 1990’s.
The same applies to any social model needs vs wants, safety, love and belonging, esteem, etc. and with ‘big data’ and say, millions of individual subjective results from derived from need wants, would provide a richer and more detailed view of society and interaction with your model for example. I represennted Dr Majola J. H. Oosthuizen to gain commercial funding for development of such a tool allowing to join any system dynamics model via the web – a first in the ’90’s.
David again re treatment of macroeconomics “”we should be trying to find a better way to approach and examine the subject, in a good way that avoids these problems of complexity and confusion.”
Here is a attempt, worthy of anyone reading this blog, do do just that:
“Summary
Macroeconomic theory was invented in the 1930s to develop policies to prevent a stock market bubble and Great Depression. It’s failed to predict or explain the 1990s stock market bubble or almost anything in the 2000s decade. This article proposes combining System Dynamics, invented at MIT in the 1960s, with macroeconomics to form a new Dynamic Macroeconomics theory that will predict and explain such things as recessions, inflation, and bubbles.”
John J. Xenakis
http://www.generationaldynamics.com/pg/ww2010.i.macro061025.htm
A student of;
Professor John Sterman, director of the MIT System Dynamics Group, as saying: “Thoughtful leaders increasingly recognize that we are not only failing to solve the persistent problems we face, but are in fact causing them. System dynamics is designed to help avoid such policy resistance and identify high-leverage policies for sustained improvement.”
http://jsterman.scripts.mit.edu/Online_Publications.html
I again below, post links to develop in society over a generation, the ability to understand causal loops and feedback;
– kindergartens start with Loopy ( fantastic explorable explaination on this site incl democracy NG )
– through to any diagramatic stock flow mathmatical simulation tools. I envisage through schooling the models are developed at age-appropriate levels able to be validated at next level and expanded on towards a year 12 student being completely able to develop system simulations – hard or soft – physics or social. And able to determine policy outcomes.
Start young:
Loopy and explorable explanations. See also NCase;
“We become what we behold, a game about news cycles, vicious cycles, infinite cycles”
And note NG re voting and democracy;
“Parable of the polygons, a playable post on the shape of society:
https://ncase.me/
Soft side:
“Simulating Hamlet in the Classroom.”
Hopkins, Pamela Lee.
System Dynamics Review 8, no. 1 (1992): 91-98.
https://ocw.mit.edu/courses/sloan-school-of-management/15-988-system-dynamics-self-study-fall-1998-spring-1999/readings/
SD Tools now:
https://www.systemdynamics.org/tools
Tools also and ML, fuzzy, neural nets and on to physics etc but I like mine to be human readable.
Tool of the future actually working now – you MUST see:
“”Dynamicland is a communal computer, designed for agency, not apps, where people can think like whole humans. It’s the next step in our mission to incubate a humane dynamic medium whose full power is accessible to all people.”…
https://dynamicland.org/
Instigator of dynamicland – Brett Victor
http://worrydream.com/
I look forward in anticipation…
Name known to our host.
For a while I couldn’t remember what this reminded me of, but then I realised. Charlie Munger.
He’s made a great deal of money seeking out his own general purpose social and economic science regular patterns and tips.
His 2007 USC Gould School of Law Commencement Speech is worth a read.
The above link is to my paper dealing with the teaching of macroeconomics using a mechanical model that one can make. It can also be found on the internet directly as SSRN 2600103