World-System (1950-2100) How to Balance the World System

In an earlier post (here), I found that the US-MX-CA World Trading System could reach a Steady State in a number of ways.

Creating a Steady State in the World System, keeping Industrialization and Environmental Degradation in balance, involves mitigating the cascading effects of Collapsing Oil Markets and collapsing Agricultural markets.

This fictional future is controversial: (1) As long as population growth and technological change continue to increase, the Neoclassical Economic Growth model will never reach equilibrium (unlimited growth forever), (2) In World-Systems Theory, although we live in a World of interacting economic systems, because there is no World Government to legislate a Steady State, there is no governed World System** and (3) the IPCC Emission Scenarios (see the Boiler Plate and the BAU Scenario) envision a scenario where the World-System is eventually in a Steady State. Continued uncontrolled industrialization seems inevitable and, at the same time, inconsistent with environmental balance.

And, worse yet, the best scenario for the US-MX-CA Trading System (using the AIC to evaluate models) is growth-and-collapse (SSP2.0-6.0 in the IPCC Scenarios) when driven by the World System (here). In this post I will explore ways to create a Steady State in the World System because (1) the WL203 Model  is often, in my experience, a good input for country-level World-System models, (2) the IPCC Emission Scenarios are all conducted in terms of the World System, (3) Limits-to-Growth policy recommendations are directed at the World System and (4) I want to address the issue of how environmental balance is supposed to happen without World government.

 

The graphic above presents a number of experiments with the WL203 Model (you can run the experiments yourself here). These futures look a lot like the IPCC Emission Scenarios because growth of the entire World System produces emissions. 

There are three growth-and-collapse scenarios: WL20, F[1,2] = 0 and F[2,3]=0. The magnitude of collapse is increased by reducing the effects of feedback loops from Food Production (F[1,2]=0) and decreased by reductions in the feedback effects of Oil Production (F[2,3]=0). Reducing both feedback effects to zero produces a high-level steady state (F[1,2] = 0 and F[2,3]=0). Setting growth in the World System to a Random Walk produces an immediate steady state (F[1,1]=0). 

The counterfactual experiments are discussed more fully in the Notes below. But, what do the model results mean in a practical sense for policy action:

• Oil and food production (through the oil-driven Green Revolution) are essential for Industrial society. We typically don't think of oil markets and agricultural markets as historical feedback controllers, but they will become controllers when Peak Oil is reached (oil is a non-renewable resources). Electric vehicles, wind and solar energy serve to reduce feedback effects from Oil Markets.
• Current uses of oil (burning in combustion engines, making plastic bottles, medical devices, industrial fertilizers, etc.) will be restricted after Peak Oil. It would be prudent to reduce industrial growth rates and conserve existing supplies of all scare, non-renewable resources.

All of these policy measures are being attempted to some extent (but reducing growth rates seems to be the most difficult). My assumption is that the only way to motivate global action is from entering growth-and-collapse mode and then focussing political action, if it is not too late (result from the WL203 Model here suggest that there will be a rebound (see the Recovery Forecast below in the Notes) after 2115 and the World System could recover). Environmental Mitigation will most likely not be undertaken voluntarily.

Notes

** In World-Systems Theory, the hyphen between "World" and "System" indicates a world of systems. The term "World System" indicates a one-world system. The World System is typically used by the IPCC in Integrated Assessment Models (IAMS). The Contradiction here is that there is no World Government to manage environmental degradation.

The time plot above shows the dominant component from the WL203 Model. From 1950 to 2008, the blue line tracks the actual data. From 2008 to 2108, the different time paths are created by setting various elements in the WL203 Model System Matrix (F) to zero or one. Let me first describe how the state space is constructed and then describe the System Matrix (F) (more information about the models is available in the Boiler Plate).

The approximate state space is constructed using Principal Components Analysis (PCA). The PCA measurement matrix is presented above. The first component (W1) is the dominant component and explains 87.4% of the variation in the underlying indicators. The other two components (W2 and W3) are historical feedback controllers. 

The first component, W1=(Growth-LP), is overall growth compared to the Living Planet Index (LP), an indicator of the state of global biological diversity. Over time the LP Index peaks after 1975 and declines after that (see the graphic above). In the future, the (Growth-LP) historical controller might become more important but right now, the decline in global biological diversity will just continue.

The second component, W2=(LP+P.Wheat.-GWP-TEMP), is an historical feedback controller that links the LP index and the Agricultural market (P.Wheat.) to Gross World Product and Global Surface Temperature. For the period from 1970-2000, W2 was in positive territory. From 2000 to the present, W2 has become negative meaning that GWP and Global Temperature are not in balance with Biodiversity and Agricultural production.

The third component, W3=(P.Oil.-OIL-EF), is also an historical feedback controller for Oil Markets and the Ecological Footprint. From the graphic above, the Oil-Market-Footprint controller seems to be reaching a steady state (Peak Oil) but this can mean that  (1) Oil Prices will keep climbing as supplies dwindle or (2) Prices will decline as demand declines.

The System Matrix, F (above), shows the interaction between the three state variables (column [,4] is the constant term in the statistical model). The system is stable (ignoring the constant) and cyclical (periods and damping time over hundreds of years). 

Results of manipulating the System Matrix:

• WL20 In the graphic above, the dark black line is the basic model forecast: slowing growth in the present and collapse shortly after that.
• F[1,2] = 0 The coefficient -0.02519461 is the negative feedback effect of food production, W2. Without this feedback effect, collapse happens more rapidly.
• F[2,3] = 0 The coefficient -0.05250691 is the negative effect of the Oil-Market-Footprint W3, on food production, W2. Eliminating this feedback effect reduces the amount of collapse after 2050.
• F[2,3] = F[3,2] = 0 Eliminating the interaction between W2 and W3, leads to gradual growth and then a steady state after 2100.
• F[1,1] = 1 Finally, setting growth to a Random Walk, results in an immediate steady state.

What do these results mean in terms of balancing and controlling the World System? 

First, the World system has it's own feedback mechanisms that will limit growth. It should be no surprise that Peak Oil and damage to Agricultural production systems will put the World System in a growth and collapse mode. The two systems (Oil Production and the Green Revolution) are intimately linked and can fail together to provide energy and food for the Industrial Revolution. 

Second, a World Government would be helpful in minimizing the effects of collapse but I can't see nations agreeing to be governed before 2100 (current effects by the United Nations have been unsuccessful). 

Third, our current Integrate Assessment Models (for example, the DICE model) seem to have none of these feedback effects. 

Fourth, my results seem to align with the IPCC Emission Scenarios which makes sense because system growth, energy emissions and global temperature are intimately liked (I will do a more detailed comparison on a future post).

No one knows the future; all we have are projections from models. Politicians who claim that all the model projections are a hoax simply rely on their gut instincts to say that everything will be fine--a massive act of ignorance, denial and hubris before the fall.

Recovery Forecast

Since the WL203 model (here) is cyclical and stable, the prediction for the far-distant future (after 2130) is for recovery. But notice that the system does not reach the same level it had reached in 2000; Entropy takes it's toll.

A Systems Perspective on World-Systems Theory

My major preoccupation in this blog is how the quantitate concepts of General Systems Theory (GST) can be applied to qualitative World Systems Theory (WST) in order to generate testable conjectures and hypotheses. In a prior post (here), I discussed the world-system as a unit of analysis. Since then, I have been looking for a reference that might summarize the relationship between GST and WST. A 1997 article in the Journal of Geography by Debra Straussfogel (referenced below) is excellent. In this post, I'll summarize the article and suggest a direction for future posts (for more detail, please reference the article).

WST is an interdisciplinary perspective meant to refocus artificial academic disciplines (arts and sciences) on a unified study of macro-societal systems. The Straussfogel article is written from the perspective of Human Geography rather than from the discipline of Sociology where WST was developed. In Human Geography, GST (General Systems Theory as developed by von Bertalanffy, 1971) was considered a mechanistic way "...of portraying humans as deterministic entities behaving in predictable ways, like so many molecules and chemical reactions" (p. 119). The more qualitative, humanist WST approach provided a path to Complex Systems Theory (CST) "the study of complex, hierarchically structured, nonequilibrium, and dynamic systems" (p. 119).

In the late 1970's, Wallerstein developed WST without reference to GST. He was dissatisfied with Marxist theories of development (historical materialism) and Western theories of Modernization. Wallerstein saw classes and nations as part of a larger social system. That larger system, the world-system, should be the unit of analysis for societal development as discussed in the last post.

The logic of the world-system is defined by its economic mode of production, diagrammed above from Wikispaces (here). Three modes of production are described and interrelated: (1) Core production processes involve the most advanced levels of technology that take cheaply produced raw materials and turn them into high-value consumer goods. (2) Peripheral production processes use cheap labor to extract raw materials used in core production processes. (3) Semi-peripheral production and consumption processes contain some advanced technology and also provide markets for high-profit consumer goods.

A1: The world-system is structured hierarchically into core, semi-perpheral and peripheral states.

H1: Production processes and technological processes are different in core, semi-peripheral and peripheral states. The higher in the world-system hierarchy, the more advanced the technology.

Different modes of production within the assumed (A1) world-system hierarchy (core-, semi-peripheral and peripheral) suggest a testable hypothesis (H1). Unlike neoclassical economic models which assume the same Cobb-Douglas production process throughout the world system (see my discussion here), WST predicts different production processes. The theoretical problem will be to come up with a model (other than the Cobb-Douglas model) that provides a more general description of economic modes of production that can be estimated across the world-system (one candidate model I have discussed in other posts, here, is the I=PAT model).

A2: The modern world-system is globalized and devoted the ceaseless accumulation of capital.

The modern world-system is the first truly global system dedicated to the "ceaseless accumulation of capital".  Earlier "world empires" (single states) and "mini-systems" were not based on advanced technology. I have left "capital accumulation" as an assumption because, as I will discuss later, "capital" is a poorly defined term with questionable operational definitions and poor measurement.

H2: Economic production advantages lead to commercial, financial and political-military advantages.

C2: The nation with the strongest economic production advantages becomes the hegemonic leader of the world-system and uses it's cultural values to reinforce it's dominance.

Wallerstein borrowed economic determinism from Marxist theory and used it to derive hypotheses about production advantages (H2) and corollaries (C2) about hegemonic leadership within the world-system. At base, these hypotheses require a good definition of technology and economic production to be testable.

WST views economic production in terms of "commodity chains" that lead from the sites of agricultural production or natural resource extraction to consumption. Processes that can be monopolized and made more capital intensive become core processes.  With global commodity chains and the world-wide division of labor, wages are lowest in the peripheral and highest in the core states, perpetuating inequality. Core-peripheral relations are thus based on "unequal exchange" and exploitation for profit of the periphery by the core.

H2a: Peripheral nation states are disadvantaged by unequal exchange with the core and semi-peripheral nation states.

Hypothesis H2a seems at first to involve a value judgement and is directly contradicted by the neoclassical economic theory of comparative advantage. However, H2a is essentially a counterfactual: what would development have been like for a peripheral country without links to core and semi-peripheral nation states? In order to test the counterfactual, we need a model that can be "experimentally" manipulated, that is, simulated under different exogenous conditions. For a number of reasons (the most important being lack of internal dynamics that I will discuss in future posts), neoclassical economic models are not particularly useful for counterfactual analysis while state-space systems models are.

Although the hierarchical structure of the world-system might seem static, there are business cycles and trends (long waves or Kondratiev cycles) as well as cycles of hegemonic succession, war, trade and control. None of these cycles can be captured by neoclassical economic models that assume continuous exponential growth. There is also, over time, "broadening and depending" of the world-system as more states become incorporated into the division of labor and more land, labor and capital are commodified and mechanized. Cycles and trends in the world-system are driven by the open nature of the system.

A3: Each state in the world-system is an open system.

H3: State variables are open to influences internal to each nation state, from other nation states in the world system and from random forces.

C3: Weak peripheral states have weak internal state dynamics and are more subject to external forces than strong core states.

Here is the point where CST enters WST. Typically, economic models (such as William Nordhaus' DICE and RICE models) are only open to trade. Each nation has the same state variables with different parameters. The models are not open to random influences, technology transfer or information transfer. The models have no internal or external cyclical dynamics. The entire neoclassical world economic system is deterministic.

CST argues that economies are dissipative systems, that is, they grow by exchanging energy and matter with their environment (not by disembodied technological progress as is assumed in neoclassical economic theory). As each economic system grows, it depletes it's environment. Changes in the environment force changes and adaptions within the system. The history of dissipative systems is not repeatable because the environment surrounding the systems has changed over time.

The implications of these assumptions, hypotheses and corollaries are many. In future posts I will look in more detail at WST, GST and CST trying to derive more testable hypotheses from the qualitative writings. In another blog (here) I will be looking at existing causal macro systems and evaluating them in terms of systems theory. In other blogs, I am statistically estimating and simulating open state-space systems models of the stock market (here) and nation states within the world system (here and here). Hopefully, in the future, this work will come together in some coherent, punishable form.

REFERENCES

Straussfogel, D. (1997) A Systems Perspective on World-Systems Theory, Journal of Geography, Volume 96, Issue 2, ops 119-126.

von Bertalanffy, L. (1971) General Systems Theory. Harmondsowrth, UK: The Penguin Press.