World-System (1950-2000+) Unstable Cycles in the Iranian Economy

 

In prior blog postings, I have usually displayed only the first three state variables of a DCM (Dynamic Components Model). There are three reasons: (1) Typically, the first three state variables explain at least 90% of the variation in the underlying indicators. For example, in Iran (see the Measurement Matrix below in the Notes) the first three components (IR1, IR2, IR2) explain 98% of the variation in the underlying indicators. (2) Also, typically, the first state variable describes overall growth in the system and the next two state variables describe historical cycles and feedback controllers (here and here). And, (3) it is difficult to explain the dynamic path of state variables in more than three dimensions.

However, interesting dynamics are observed in the lower-order state variables. In the graphic above, the state space IR4, IR5 and IR6 is displayed. The graphic above shows the unstable, cyclical dynamic state-space interaction between IR4=(a Population-Resource controller), IR5=(an Environmental-Economy controller) and IR6=(Human Development-Employment Controller). Movement on the graph is from the center outward. 

The remaining three state variables, IR7-IR9 (graphed above), also have mild cyclical dynamics and are theoretically interesting (IR7=a Employment-Resources-Globalization Controller, IR8=An Emissions-Energy Controller and IR9=a Population-Employment Controller). They just explain an insignificant amount of variation.

Macrosocioeconomic systems are very complicated: everything is related to everything somewhere in the system. Policy measures that try to improve minor feedback controllers will have little overall impact on the system.

Notes

The first state variable (row of the Measurement Matrix, IR1) describes overall growth in the Iranian Economy. The second state variable, IR2, describes  Unemployment and Globalization, (IR2 = 0.9091 SL.UEM.TOTL.ZS + 0.335 KOF) and the third state variable, IR3, is an environmental-globalization feedback controller, (IR3 = 0.827 KOF - 0.3878 SL.UEM.TOTL.ZS - 0.258 EF - 0.217 EG.USE.COM.KT.OE), for unemployment, ecological footprint and energy use.

The next three state variables (rows of the Measurement Matrix) describe (1) a Population-Resource controller IR4 = (0.60541 N + 0.5104 HDI - 0.32993 GDP - 0.3036 EG -  0.2797 CO2 - 0.243 EF), (2) an Environmental-Economy controller IR5 = (0.731 EF + 0.21639 GDP - 0.5199 CO2, - 0.3020 EG - 0.21948 L) and (3) an Human Development-Employment Controller IR6 = (0.4050 HDI + 0.31822 GDP - 0.74027 N). Together, these feedback controllers only explain about 0.005% of the variation.

The final three state variables describe (1) an Employment-Resources-Globalization Controller IR7 = (0.64207 Q + 0.44614 L - 0.297 EF -0.2962 EG - 0.28808 KOF), (2) an Emissions-Energy Controller IR8 = (0.6428 CO2 + 0.247 EF  - 0.6843 EG), and (3) a Population-Employment Controller IR9 = (0.62266 N + 0.39963 GDP - 0.5687 HDI  0.2119 EG). Although these might be theoretically interesting controllers, they explain an insignificant amount of variation.

Further reading:

• Iranian Revolution a series of events that culminated in the overthrow of the Pahlavi dynasty in 1979.

• Strait of Hormuz a strait between the Persian Gulf and the Gulf of Oman. It provides the only sea passage from the Persian Gulf to the open ocean and is one of the world's most strategically important choke points.

• Iran-Contra Affair a political scandal in the United States that centered on arms trafficking to Iran between 1981 and 1986, facilitated by senior officials of the Ronald Reagan administration

• Iran Nuclear Program one of the most scrutinized nuclear programs in the world, has sparked intense international concern.

• Pahlavi Iran the Iranian state under the rule of the Pahlavi dynasty. The Pahlavi dynasty was created in 1925 and lasted until 1979 when it was ousted as part of the Iranian Revolution, which ended the Iranian monarchy and established the Islamic Republic of Iran.

• Iran-Iraq War an armed conflict between Iran and Iraq that lasted from September 1980 to August 1988. Active hostilities began with the Iraqi invasion of Iran and lasted for nearly eight years, until the acceptance of United Nations Security Council Resolution 598 by both sides.

• Iranian Economy a mixed, centrally planned economy with a large public sector. It consists of hydrocarbon, agricultural and service sectors, in addition to manufacturing and financial services, with over 40 industries traded on the Tehran Stock Exchange.

Blog Roll:

• Stabilizing the Iranian Economy Easy but not easy!
  
• A Deep Dive into the Iranian State Space Cycles vs. Control
  
• The Iranian Revolution Still being worked out today.
  
• Will Israel and US Attacks Hurt the World-System? Yes
  
• How Does the Iranian Economy Work? Not like a Neoclassical, free-market economy.
  
• What was the Impact of the Iranian Revolution? Elimination of Cycles!
• Iranian Globalization and Unemployment Created the discontent that led to the Iranian Revolution.
• Iran as a Neoclassical Economy US Technological domination!

World-System (1960-2100) Stable French Technology Cycles

 

The 2025 Nobel Prize in Economics (here) was awarded for having explained the role of innovation and Creative Destruction in Sustained Economic Growth. Particularly interesting (to me) was the Aghion and Hewitt paper  A Model of Growth Through Creative Destruction, which won them part of the Prize. Does the 2025 Nobel Prize have anything to say about current French economic development and political instability?

I have two explicit models for technological change, one for Productivity change (TECHP) and another for Efficiency change (TECHE). The models are based on State Space indexes (see the Notes below) constructed using Principal Components Analysis (PCA). The Phase Space for the FR TECHE model is displayed above. The Phase Space for the FR TECHP model is displayed below.

Both models are cyclical and stable with periods of over a Century (see the Notes below). 

Over time, in the graphic above, the two types of Technology peak at different points in France. TECHP peaks first followed by TECHE. I other words, when productivity gains are exhausted, technology improvement turns toward efficiency. The problem for France is that both measures of technological change are about to go into decline after 2025 and not predicted to recover until after 2100 (at least in the models).

From my models, at least, it does not appear that Technological change will intervene to save France from an impending Steady State Economy and possibly continued Political instability.

You can experiment yourself with the FRL20 TECH Models models  and compare the outputs to the unstable Schumpeter Creative Destruction Model.

Notes

Blog Roll for FRL20 models and Theory Models:

• FRL20 Model
• FRL20 TECH Models
• Schumpeter Creative Destruction Model

Measurement Models

Modes

System Matrices

World-System (1960-2150) Unstable Cycles in Colombia

 

Notes

CO_L20 Measurement Matrix:

CO_L20 BAU System Matrix:

CO_L20 BAU Stabilized Sytem Matrix:

Technological Long Waves

 

The Kondratiev Wave is an important element of World-Systems Theory. The graphic above is taken from Andreas Goldschmidt and gives historical specifics for technological cycles. Goldschmidt's formulation allows for the idea to be tested (one of the models I always test), is partially consistent with economic Growth theory (particularly if we do not assume a functional form for exogenous disembodied technological change in the Solow-Swan Model) and I can present some examples.

• The Iranian Economy prior to 1979 and associated Tech Bubble.

World-System (1960-2500) Unstable System Cycles in Latin America

 

In an earlier post (here and here), I found that the best forecasting model for Argentina was the LA20 Model (Latin America Regional Economy). Out until 2100 (the furthest out the IPCC is willing to go on Global Emission Scenarios), it looks as if Latin American Integration would provide a desirable future, at least for Argentina (here). This post explores what happens after 2100, out to 2500. Of course, no one knows the future (especially out to 2500), but the LA20 Model is a computer program that can be run out to any date. Sometimes it is insightful just to see what happens!

The LA20 Model is unstable and cyclical (the eigenvalues and AIC statistics are presented in the graphic above for the Business as Usual BAU model).  In the Phase Plot, above, time moves from left to right and cycles increase in magnitude and severity.** Although the short-term future might look endurable, the long-term future is not. Luckily, a lot (maybe everything) can change after 2100, especially in the face of Environmental Crisis.

Another reason to look at long-run cycles in Latin America is that cycles (particularly Kondratiev Waves or K-Waves) are discussed extensively and qualitatively in World-Systems Theory. It is refreshingly concrete to see actual historical cycles tested with a statistically estimated model. However, a future of unstable cycles is probably one reason why Latin American Integration has been so problematic.

Notes

** And will require that bailouts increase in magnitude and severity.

LA20 BAU Measurement Matrix:

The State Space of the LA20 model has three components that explain 99% of the variation in the indicators: LA1=(Overall Growth), LA2=(LU-Q-EG) an Unemployment Controller and LA3=(N+L-CO2-Q) a Population Controller. LA1 reinforces the conclusions of Balanced Growth Theory (all major parts of the Economy have to grow together). LA2 balances Unemployment (LU) against overall production (Q) and Energy Use (EG)--reducing LU requires increasing energy-intensive production. LA3 is a Malthusian-Environmental component balancing Population (N) and Labor Force (L) Growth against Emission (CO2) intensive production (Q).

The unstable LA20 BAU model has cyclical periods under a decade but no effective damping time (table above). 

The stable LA20 BAU model also has cyclical periods under a decade but damping times of about 150 years.

NOTE: Periods in both models are longer than those assumed by Kondratiev Waves or K-Wave models (45-60 years). LA2 could be expanded to a Marxian Economic component with (0.901 L - 0.272 Q - 0.239 EG - 0.144 L) where the standard Marxian Economic component is (Q - wL) assuming fixed Ricardian wages. Most of these ideas (Malthusian, Marxian Economic, Balanced Growth Theory and Kondratiev Waves or K-Wave) can be combined in Systems Theory models. However, the result for LA does not mean that the ideas can be generalized to all regions, countries and time periods (see Unified Growth Theory).

You can experiment with the LA20 BAU model here. Suggestions are given in the code for how to stabilize the model.

Ex. 1.0 Can you find a way to eliminate cycles once the model has been stabilized? 

The solution to this Exercise can be found in the LA_TECHP model which I will describe in a future post. 

Descriptions of the how the Dynamic Component State Space models are constructed are given in the Boiler Plate.

World-System (1800-2000) Marx, Malthus and Ricardo: Together Again

 

You can experiment with the W_M456 model (here). Notice that the model is nonlinear and unstable.

Notes

Boiler Plate

 

Notes

The first six indicators in standard scores are taken from the World Development Indicators (WDI). KOF = KOF Index of Globalization, EF = Ecological Footprint, HDI = Human Development Index. 

State Space Model Estimation

The Measurement Matrix for the state space models was constructed using Principal Components Analysis with standardized data from the World Development Indicators. The statistical analysis was conducted in an extension of the dse package. The package is currently supported by an online portal (here) and can be downloaded, with the R-programming language, for any personal computer here. Code for the state space Dynamic Component models (DCMs) is available on my Google drive (here) and referenced in each post.

Atlanta Fed Economy Now

My approach to forecasting is similar to the EconomyNow model used by the Atlanta Federal Reserve. Since the new Republican Administration is signaling that they would like to eliminate the Federal Reserve, the app might well not be available in the future.

While the app is still available, there have been some interesting developments. In earlier forecasts, the Atlanta Fed was showing GDP growth predictions outside the Blue Chip Consensus. Right now, after unorthodox economic policies from the Trump II Administration, the EconomyNow model is predicting a drastic drop in GDP (the Financial Forecast Center is only predicting a slight drop here).

Another comparison for what I have presented above are the IPCC Emission Scenarios. These scenarios are for the World System. Needless to say, (1) the new Right-Wing Republican administration plans on withdrawing the US from all attempts to study or ameliorate Climate Change and (2) the IPCC does not produce any RW modes for the World System (but seem my forecasts here).

Climate Change

Another comparison for what I have presented above are the IPCC Emission Scenarios. These scenarios are for the World System. Needless to say, (1) the new Right-Wing Republican administration plans on withdrawing the US from all attempts to study or ameliorate Climate Change and (2) the IPCC does not produce any RW modes for the World System (but seem my forecasts here).

World System

The longest running set of data we have for the World-System is the Maddison Project based on the work of Angus Maddison (more information is available here). Data on production (Q) and population (N) for most countries and regions runs from years 0-2000. More data becomes available as we near the year 2000. 

Available data were entered in a spreadsheet (see Population above, double click to enlarge). Missing data were interpolated with nonlinear spline smoothing using the R programming Language.

In cases where initial values were not available (see GDP above), the E-M Algorithm was used to estimate initial conditions.

From the graph of GDP above (W_Q) for the World System, it can be seen that economic growth from the year 0-1500 was basically flat. The period of British Capitalism (after 1500) had a small plateau of growth. Takeoff does not happen until the Nineteenth Century.

From a system's perspective, the only model that can be tested for the entire period is Kenneth Boulding's Malthusian Systems Model [Q,N] = f[Q,N].

When developed as a State Space model (measurement matrix above) there are two components: W1=Growth and W2=(Q-N), the Malthusian Controller. When more data is available, the Malthusian Controller can be generalized to other SocioEconomic theories.

What the Malthusian Controller shows (plotted as Q-N above) is that a long-developing Malthusian Crisis (Q<N) started in the Late Middle Ages and accelerated through the period of British Capitalism (Dark Satanic Mills) and was reversed spectacularly during the Nineteenth Century.  Takeoff in response to a deepening Malthusian Crisis would not be an unreasonable way to view Modern Economic Growth.

Hurricane Forecasting

My vision for SocioEconomic system forecasting is to follow the US National Oceanic and Atmospheric Administration's (NOAA) approach to hurricane (Economic Crisis?) forecasting using Spaghetti Models (see below).

Currently, Economic forecasting does not use Multimodel Inference but it is getting there! The best state space model for the US SocioEconomic System in the graphic at the beginning of this post is the World System (W) model based on the AIC Criterion.

Climate Change

Another comparison for what I have presented above are the IPCC Emission Scenarios. These scenarios are for the World System. Needless to say, the new Right-Wing Republican administration plans on withdrawing the US from all attempts to study or ameliorate Climate Change.

Error Correcting Controllers (ECC)

In another post (here), I presented Leibenstein's Malthusian Error Correcting Controller (ECC). It can be generalized to the dominant ECCs in most theoretical economic models (above). These controllers can be further generalized. For example, (X-U) and (L-U) can be generalized to (N-U), a more general Urbanization Controller which describes market expansion for economic growth. In countries and periods with limited data, (N-U) might subsume all these processes. ECCs describe important feedback processes in SocioTechnical System that are typically not recognized as such in academic literature.

Kaya Identity

The basic theoretical model underlying all the World-System models I crate is the Kaya Identity. There are a number of advantages to starting theoretical development with the Kaya Identity: (1) An "identity" is true by definition Adding other variables to the model ensure that theory construction is on a solid footing. (2) The Kaya Identity is also used as the foundation for the IPCC Emissions Scenarios allowing a linkage between World-Systems Theory and the work of the IPCC.

World Development Indicators (WDI)

After WWII, extensive data sets on all countries in the World-System became available from the World Bank (here). The indicators above where chose to construct the state space for each WDI-based model. Addition indicators can be added for specific forecasts and analyses.