In the past, I was not one who cared much for definitions. Now, I realize that the lack of clear definitions, particularly in the Social Sciences, has led to unnecessary misunderstanding. For example, in grade school, students learn that the Earth is a complex system with a number of spheres and feedback loops (see the graphic above--humans are located in the Biosphere). Then, students get to college and (might) learn in a Sociology course that there is (or maybe there isn't) a Capitalist World System. Or, they might read that the IPCC (Intergovernmental Panel on Climate Change) is having trouble identifying feedback loops in Human Systems. Then they might go back to Sociology (or Economics) and find that feedback loops are never discussed and that even the concept of a system is not taken very seriously.
Or a student might go to ChatGPT (here) and be given the definition above (with more text in the Notes below). At first, I had a problem with "components" and "work together to achieve a specific goal or function." Does the Earth System have a goal? Does it have components such as gear shifts (cars) or central processing units (computers)? Then I realized that the "component" parts of the definition are imposed on physical systems (which may or may not have them) so that we humans can better understand what we are talking about.
In the Earth System, the Atmosphere, Cryosphere, Hydrosphere and Lithosphere work together to support the Biosphere (Human, plant, animal life and consciousness--see Gaia philosophy). In my experience, critics have a field day with Systems Theory when it gets too speculative (e.g., Parsonian Systems Theory) and when definitions remain murky (particularly operational definitions, that is, measurement).
Just to make the discussion somewhat more concrete, does the graphic above (the Kaya Identity used by the IPCC) describe a system (where N=Population, Q=Output, E=Energy, CO2=Carbon Emissions and T = Global Temperature)? The extensive variables (N, Q, E, CO2 and T) are causally connected. The Impact (I=PAT) is described by the intensive variables (q=Q/N, e=E/Q, c=CO2/E and t=T/CO2).
As a conceptual system, the Kaya Identity is clear about the components, the interconnections, the purpose (explain climate change), the boundary (anything other than the extensive variables is out of the system) and inputs-outputs (N -> T). It is only missing "feedback" mechanisms which, evidently, are optional. As a physical system, we know that all sorts of extensive and intensive variables are missing. Let's look at two well-known conceptual systems, the Malthusian Model and the Capitalist model to fill in some gaps.
The Malthusian system model (and here) is widely and deliberately misunderstood for all sorts of political reasons but the model (above) is simple, straightforward and unavoidable when trying to understand population growth and control. Population grows when there is an excess of Births over Deaths (b-d). Production (Q) does not necessarily keep pace with population growth (there is no technological change in the model--I'll add that next) and the difference, ECC=(Q-N), is the Error Correcting Controller (if you want to see specific examples of appropriately weighted ECCs, see the WL16 model). When population growth exceeds economic growth, it is a signal for population to decrease (or production to increase, if that is possible). The model is particularly appropriate for Peripheral Countries and for time periods before the Industrial Revolution.
The Capitalist Model (above) assumes that a system driven by technology can support any level of population growth. There are two kinds of technological change: Endogenous (tech) and Exogenous (TECH). The ECC in this model involves employment (L) and the substitution (or addition) of embodied technology (Fixed Capital) for workers. The original version of the model (from David Ricardo and Karl Marx) assumed that profits were generated from a fixed, subsistence wage (W=wL) when compared to production, R=(Q-wL), thus the ECC = (Q-L). The model is particularly appropriate for Core Countries and for time periods after the Industrial Revolution.
In the Essays on Biography, Part II, John Maynard Keynes wrote about both Malthus and Ricardo and their lengthy correspondence. Keynes felt that the foundations of Economics could have been based on either Malthus or Ricardo, but that Ricardo won to the detriment of future thinking. There is really no reason to have to choose. Both authors had perceptive insights. However, from the standpoint of Systems Theory, it is easier to start with Malthus. The Malthusian ECC can easily be generalized (here, here and here).
It is also important to understand that I am developing conceptual systems. The linkage to real systems is tested using statistical analysis, specifically Dynamic Component Models (DCMs). The reason for DCMs is that Directed Graphs can (1) easily get very complicated, (2) are not Canonical and (3) are isomorphic with a single DCM. For example, the Malthusian model can be easily added to the Capitalist model and both are isomorphic (when statistically estimated) with a DCM. In other words, Directed Graphs help us clarify thinking but they do not related uniquely to some real system.
Also, the DCM model separates growth components (state variables) from feedback components (cyclical variables). The components (state variables) are statistically independent since they are constructed with Principal Components Analysis (PCA). So we can analyze economic growth and business cycles separately and independently and still conduct a systems analysis.
Returning to the problem of whether or not there is a Capitalist World System and, if so, when and where did it develop, my solution would be to test the Malthusian and Capitalist models separately during a specific historical period where data is available. A Capitalist World System model would have to have a Capitalist ECC. For example, the Long Sixteenth Century World System Model (WL16, here) has both an Environmental and a Malthusian ECC. Since the Industrial Revolution Take-off did not happen until the Nineteenth Century (here), the result for L16 makes sense.
World-Systems Theory looks at a world of countries (systems) under hierarchical control, Core Countries controlling Peripheral Countries. My approach is to test the hierarchical structure using different input variables to a DCM for each country and region. I also include a World System model (for example, WL16) to link directly with the IPCC World models and with the Limits to Growth models.
One more topic to address is attributes of the system: (1) Observability (are all the system states observable), (2) Reachability (are all the states reachable), (3) Controllability (Is the system controllable), (4) Stability (is the system stable), (5) etc. All these attributes are measurable for DCM models (see the dse, Dynamic System Estimation program). These attributes are only available in a formal systems model with clearly defined (through PCA) state variables.
Notes
Readers might wonder why I have not included a Market Model in the basic models above: (1) Both the Malthusian and Capitalist models are conducted in real terms (quantities are divided by prices), (2) there are no markets for population except in a slave system and (3) markets do not actually control the entire socioeconomic system (I prove the issue here).
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