Systems Thinking and Complexity
From mechanical equilibrium to dynamic complexity
From mechanical equilibrium to dynamic complexity
Dear Kate, that is indeed a good question and it is obvious that what you show graphically as the demand and supply functions is unsatisfactory for explaining properly about how our social system REALLY works. Yet the need is there and most of the so called experts (who are inside the humanities part of the universities) don’t seem to have a clue about how to go about it.
As a retired engineer, I chose to throw my hat into the ring. The subject of macroeconomics can be separated from the rest and it has more relevance when it comes to the governmental decisions for better living and prosperity. So I did my research there by reading up what I could at university libraries on the undergraduate and more advanced writings about this our social system. I should give some credit to some of these books and their authors but my general impression was that their methods for providing explanations are badly expressed and unclear and unsatisfactory for a new student to grasp how our society behaves.
As an engineer, I was and am seeking for a better way for modelling our social system and to describe in more exact terms how it functions. In a sense, Doughnut Economics also fails here because although it is colorful and full of life, it cannot show as in a scientific proof the reason why a particular national policy will result in the certain response of our social system. Of course there is a lot of less fixed things going on at the same time, so this solution needs a lot of care in its preparation.
What I was looking for was to properly convert our unfortunate pseudo-social science into a true one–the demise of the pseudo-science that the humanitarians have fed our student with up to now. In my well-researched book “Consequential Macroeconomics” I have achieved this goal and provide the means or model and analytic technique for the derivation of any kind of policy decision. So now it need somebody to begin to explore the various effects of each possible policy. This is a step forward, for a PhD student to take up. It is not necessarily unsuitable for a less-deeply thinking person and I have deliberately kept the language fairly simple so as not to confuse the reader. This book has no commercial value although it is on Amazon, because I offer it for free due to my belief that the pursuit of scientific knowledge and its findings should be shared by all of us. (write to me for a free e-copy at firstname.lastname@example.org and share it with your friend too).
For those with no time for getting and studying this book, my short paper SSRN 2865571 “Einstein’s Criterion Applied to Logical Macroeconomics Modeling” should get you started about how an engineer begins to consider this problem. The model is also in my book. Enjoy!
Dear All, ‘the Seneca effect’ described by Professor Ugo Bardi at a Club of Rome meeting here:
He argues that economic growth is relatively slow compared to its rapid collapse once environmental ‘carrying capacity’ has been destroyed. Interestingly he doesn’t use a ‘doughnut’ framing but argues that a slower and more careful growth may emerge.
I am not sure I am picking up on the right threads of the argument here, and I have just crossed over from another thematic area - mimicking natural systems. However, I see clear synergies between natural systems and complex systems theory. At the end of the day, we can accept the view that all of the natural world is governed by a few simple laws, whether we choose to align are philosophy with quantum mechanics or with traditional physics (hope I am not offending physicists in the room). It includes, in a typically nested and hierarchical manner, all social and cultural systems (biological constructs with either physical or cognitive boundaries or both). In an earlier discussion I was suggesting natural ecosystems operate to 9 recognisable propositions, based on new ecology theory and principles rooted in physics - scaling; thermodynamics; order; hierarchy; entropy; so forth. The sum of all the components represent the whole structure and dynamics of the (eco)system, and despite the immeasurable complexity of the system it conforms to the few simple laws that govern the universe. The capacity, ‘health’, growth, maintenance, resilience of the (eco)system is dependent on its ‘thermodynamic mass’ and thermodynamic function. On this basis we quickly recognise the current failings in existing global economic models - are deeply entropy-driven. The feedback processes fail to demonstrate the kinds of emergent properties that help regulate the function of the system and to secure or provide it with the necessary resilience it requires to meet the numerous forms of uncertainty and disturbance. So, what can we learn from nature, how do natural, complex ecosystems operate in such a way as to maintain effective function, resilience and adaptation, what does “efficiency” mean when observed in natural systems or applied to nature, does efficiency = redundancy capacity, and what form does it take - If we accept one principle, the one of eco-exergy (biomass), and it’s relationship to thermodynamic mass, how might this translate across to socio-economic systems? Similarly, if we accept that ecosystem growth and functional complexity is governed by networks + information + biomass, again does this translate across to anthropogenic systems - it should do as all systems are driven by the same universal laws. It brings me round to the 9 planetary boundaries. The first point I would make is this - 9 components to define boundaries to a complex system? If 1 or more of these is breached, as we know to be the case, then how does this impact or effect the others? Complex systems are intimately networked, it would be foolhardy and arrogant to assume we could describe the level of complexity using simple linear models let alone talk of breaching, tipping points, thresholds, so forth. We don’t even know much about baselines in complex (eco)systems. In short, at best, we can only operate a black box principle to management (vulnerability analysis and scenario-testing). What we can do is fall back on natural ecosystems as appropriate templates for understanding complex systems dynamics, function and resilience. Just skimming the surface of the subject alerts us to the current state of affairs - that most anthropogenic systems - our economics, deviate dramatically from natural, self-regulating, self-referential, thermodynamically ‘efficient’ ecosystems.
This reply by P Hobson is typical of how a humanist in economics thinks and unfortunately it is limited in the perspective taken when viewing the 'Big Picture" of our social system. It is the old problem of not seeing the wood for the trees!
When one looks for the aspects in less detail but as more generalized features, the situation can become much clearer. The way of doing this is essentially that taken by a scientist (or engineer in my case), who can manage to see things in more general terms without so much detail. The intuitive humanist enquirer cannot and never will, due to the training of his/her mind to concentrate on the details (interesting and colorful as they are).
When we take aggregates of the DIFFERENT KINDS of businesses and not the actual company or family businesses themselves, we find that only (and exactly) 10 kinds of trade exchanges are possible! They may be sub-divided into 19 different money-flows and their reciprocal flows of goods, services, documents, access rights, taxes, hire fees, rents, etc. This is shown in my working paper SSRN 2865571 “Einstein’s Criterion Applied to Logical Macroeconomics Modeling” and the model for it is at the end of this work.
So it is possible to avoid the problem of complexity and still achieve some better understanding about how our social system works, which is in my recent 310 page book “Consequential Macroeconomics” included in the list of references in that short paper above. (Write to me at email@example.com for an e-copy for free, and set your mind on the right path of what economics thinking is really all about when it finally becomes true science!)