Alternate Futures for Afghanistan

 

Notes

• War in Afghanistan (2001-2021)
• Soviet-Afghan War (1979-1989)
• AF_L20 Model The model is an unstable Moving Average model that can be stabilized (instructions in the code).
• Blog Roll: Afghanistan
• The Revenge of Geography
• New Strategy in Afghanistan

AIC Statistics

Alternate Geopolitical Alignments for Israel

 

What is the "best" Geopolitial Alignment for Israel? In this post, I look at some options: (1) None (Business-as-Usual, BAU, or Muddling Along, Random Walk, RW), (2) Alignment with the Region (Middle East North Africa, MEA), (3) Alignment with the World System (W) or (4) Alignment with the US. Google AI reports the Conventional Wisdom:

However, the first question is "what do we mean by best?"

In terms of Systems Theory, the question is whether a Steady State Economy in Israel (and the Middle East) would be best or whether the Neoclassical Economic Dream of unstable, endless exponential growth is best. I cannot answer the question for policy makers even though endless economic growth is not possible on a finite planet. We just have to keep the question in the back of our minds as we are evaluating Geopolitical futures for Israel.

Another more specific question is whether we are interested in the short- or long-term? In the short-term, Israel is at War with Iran and currently aligned with the United States. So, the Long-term Attractor Path is of more interest since the path is unknown.

Using various IL_L20 Models, I ran five alternatives plotted in the graphic at the start of this post.  The best long-term model, which provides short-term exponential growth and long-term stability, is the IL_L20 MEA Input model (see the Notes below).

The second-best option is the IL_L20 BAU Model, but it is unstable. As a policy counterfactual, consider stabilizing the BAU model (see the Notes--stability involves reducing growth rates). Under a stable BAU regime, the IL_L20 Model reaches a Steady State around 2150 and provides over a century of continued growth for Israel.

Interestingly enough, alignment with US input is not best because the model is quite cyclical (see the Phase Diagram of the IL_L20 US-Input Model here). The prediction from US-Input model is that, after the War with Iran, the US will direct strategic attention elsewhere (back to Asia?) as happened after past Peace Agreements.

• Abraham Accords a set of agreements that established diplomatic normalization between Israel and several Arab states, beginning with the United Arab Emirates and Bahrain.
• Oslo Accords a pair of interim agreements between Israel and the Palestine Liberation Organization (PLO): the Oslo I Accord, signed in Washington, D.C., in 1993;^[1] and the Oslo II Accord, signed in Taba, Egypt, in 1995.
• Israel-Egypt Peace Treaty following the 1978 Camp David Accords, the Egypt–Israel treaty was signed by Anwar Sadat, President of Egypt, and Menachem Begin, Prime Minister of Israel, and witnessed by Jimmy Carter, President of the United States.
• Israel-Jordan Peace Treaty an agreement that ended the state of war that had existed between the two countries since the 1948 Arab–Israeli War and established mutual diplomatic relations.
• Gaza Peace Plan a multilateral agreement between Israel and Hamas that aims to address the ongoing Gaza war and broader Middle Eastern crisis.
• Two-State Solution a proposed approach to resolving the Israeli–Palestinian conflict, by creating two states on the territory of the former Mandatory Palestine.
• Arab-Israel Normalization since the 1970s, a parallel effort to find terms upon which peace can be agreed to in the Arab–Israeli conflict and also specifically the Israeli–Palestinian conflict.

Notes

More readings:

• Israel: A Blind Spot for Steady Staters
• The Crisis in the Middle East is a Crisis of Growth
• The Myth of Israel Innovation
• Blog Roll: Israel

You can run the IL_L20 model, written in R-code, here. Instructions in the code show how to stabilize the system. Other models for the Middle East and North Africa are available here.

IL_L20 Measurement Model

Three Component State Variables explain over 98% of the variation in the indicators: IL1 = (Overall Growth), IL2 = (LU - KOF - EF) Unemployment Controller and IL3 = (EF + L  - KOF - HDI) Environmental-Labor Controller.

IL1 AIC Statistics

The AIC Statistics are all closely grouped meaning that there is not one, dominant Geopolitical model.

IL_L20 BAU Model

The IL_L20 BAU Model is unstable and cyclical.

IL_L20 BAU Model Controlled

The IL20 BAU Controlled Model is stable and cyclical.

The historical time plot for the IL_L20 BAU Model is presented above.

The historical time plot for the stabilized IL_L20 BAU model is presented above.

IL_L20 MEA-Input Model

The IL_L20 MEA-Input Model provides the best attractor path. However, it seems quite unlikely that a stable Middle East will happen anytime in the foreseeable future.

Future Scenarios for Iran

In an Opinion piece for the NY Times How Does This End? Four Scenarios for What Comes Next With Iran, Bret Stephens argues that there are four likely future scenarios for the War in Iran: (1) Regime Change, (2) Regime Modification, (3) Both sides declare 

victory and (4) the Realistic Path, US seizes Kharg Island (see the video above which argues that the "Realistic Path" is a trap). These scenarios are all relatively short-term.

My interests are in more long-term Geopolitical Alignments that might benefit Iran. It seems that most of the World-System has abandoned Iran. Russia, China, and the EU are all sitting on the sidelines while the US and Israel continue an Air War. And, my simulations with the IR_LM model show that leaving Iran to "go it alone" (the Business-as-Usual or BAU model) produces the best future prospects (see the simulations here). The US and Israel seem intent on not letting the BAU Scenario go forward.

I asked ChatGPT about the Geopolitical Consequences of the current US-Israel-Iran War:

I can investigate the effects of a Global Oil Shock by using the WL203 Model.

The third component state variable (see Notes below) is dominated by Oil Prices. A large one standard deviation shock to the W3 component (an Oil Price Shock and associated effects: Wheat Prices, Oil Production and Ecological Footprint) produces the shock decomposition above. Overall growth in the World System (W1)  takes a negative shock that is never fully recovered. The same is true for the W2 state variable (an Environmental Controller); the negative shock is never recovered. Eventually, however, Oil Price Controller (W3) returns to the attractor path.

Notes

Remaking the Middle East: The U.S., Israel & Iran | FRONTLINE 

You can run the WL203 Model and the IR_LM model using R-code and investigate different counterfactual future paths (see the notes in the code).

For more information see:

• Blog Roll: Iran
• Blog Roll: Syria
• What If Iran Dominated the Middle East?
• Blog Roll: US
• Blog Roll: Russia
• Blog Roll: China
• Blog Roll: The World System

WL20 Model State Variables

The World System growth component is the  first principal component state variable for the WL20 model.

The Measurement Matrix for the WL20 model is presented above. The W1 Component (state variable) is an approximately equal and positive weighting of all the indicators except for the Living Planet Index (the planet is becoming less livable) and measures overall growth in the World System (rather than just GDP).

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

Climate Uncertainty

Is The Green Transition Over?

 

Feb 27, 2026  The New York Times (today) published an article titled Don’t Look Now, but the GreenTransition Is Still Happening in spite of retreats from Sustainable Development Goals  across the entire World-System. This would be good news if it was true, but it isn't. The NYT Article cherry-picks some positive examples but the aggregate data (graphic above) show that the Green Transition is basically stagnant.

This post will explain how the Green Transition Index (GREEN) is created and how the future forecast was constructed.

The GREEN index was created from seven indicator variables: Oil production (OIL), Oil Prices (P.OIL.), Global Temperature (TEMP), Carbon Dioxide Emissions (CO2), Carbon Emissions (Carbon) and the Ecological Footprint (TotalFootprint) and the number of Earths needed to support the current population (Earths). Data Sources are listed in the Boiler Plate. The, Principal Components Analysis (PCA) was used to construct three independent indexes that explain over 99% of the variation in the indicators (see the Measurement Model below)

The three components are: GREEN1 = (overall Growth in the Indicators), GREEN2 = OilMarket-Global Temperature controller and GREEN3 = Temperature-Oil Price Controller. The two historical controllers, GREEN2 and GREEN3, are of primary interest since they control overall growth.

The State Space model of GREEN index dynamics (see below) is stable with strong negative feedback. However, the behavior of the Green Transition over time is essentially at equilibrium and not changing. 

Shocks to the system (see below) are heavily damped. Oil Price shocks and Global Temperature shocks eventually return the system to equilibrium.

Notes

Green Transition Index Measurement Model

Green Transition model

Green Transition Shock Decomposition

Green Transition Model Full Forecast

Green Transition Full BAU Model

Sub-Saharan Africa Forecasts, World System (1960-2100)

 

According to the World Bank 2024 Pathways Out of Poverty Report  "Two-thirds of the world’s extreme poor live in Sub-Saharan Africa, rising to three-quarters when including all fragile and conflict-affected countries". From the report:

To have the maximum impact on poverty reduction, that growth must be inclusive by creating employment opportunities while ensuring that the poor can take advantage of opportunities (for example, through quality education). Promoting economic growth, basic investments, and insurance are fundamental to sustainably improve the lives of the poor. Those actions reduce multidimensional poverty and enhance resilience against extreme weather and other shocks.

What does my SSA L20 model predict for future growth in Sub-Saharan Africa? The graphic above shows forecasts from five models. The forecasts are all positive:

• Random Walk (RW) The Random Walk model presents the "Muddling-Through" baseline.
• Business as Usual (BAU) The Business-as-Usual model assumes no Geopolitical Input from other countries.
• World Input (W) The World Input Model (WL20) assumes input from the World System.
• US Input The US Input model assumes input from the US Economy.
• TECH The two Technology Models assume emphasis on Technical Productivity (TECHP) and Technical Efficiency (TECHE). They produce essentially the same forecasts.

Using the Akaike Information Criterion (AIC) the best short term model is a Random Walk (RW) while the best attractor path is presented by input from the USL20 model.

You can run the full USL20R SSA Regional Model (here), the USL20 model (here) and the WL20 model (here). The SSA1 component is an equal weighting of all the state-space indicators.

Notes

SSA L201 AIC Statistics

Hardship Forecasts for Venezuela (1960-2100)

 

According to Google AI (quote above) the Trump II Administration claims to be running Venezuela now after the Jan 3, 2026 invasion. Geopolitical Alignment with the US, however, is not the only option for the future and may (or may not) be the best option.

In this post, I will focus on what Geopolitical Alignment, if any, would be best for the Venezuela people.** The alignments range from none (RW, TECHE, TECHP, and BAU) to alignment with the World System:

• No Geopolitical Alignments One option, that no longer seems practical, is for Venezuela to be left alone to manage it's own economy. This would involve letting the country take a Random Walk (RW), simply focus on Business-as-Usual (BAU) or turning the country into a Neoclassical Economic State focusing on Technical Productivity (TECHP) and Technical Efficiency (TECHE). From the time plot above, none of these options is best. Only TECHP results in a reduction in Hardship (HARD1). In any event, in the Long Twentieth Century, Venezuela has shown little ability to manage their own economy.
• Geopolitical Alignment with Latin America The LAC model shows very little reduction in Hardship (HARD1), probably because the Latin American Region (LAC) has it's own problems managing Hardship.
• Geopolitical Alignment with the US If there is a charitable interpretation of the US Invasion it is to rid Venezuela of incompetent Left-Wing governments (Heather Cox Richardson in the video below argues that what is really going on here is the destruction of the Rules-Based World Order) and align the country permanently with the US. Using the USL20 model (US) as input would result in a large reduction in Hardship (HARD1) but would only last until 2080 when there would be a rebound to increasing Hardship.
• Geopolitical Alignment with the World System After 2080, the best  Geopolitical Alignment would be with the WL20 Model (if Venezuela survives the period of US dominance, which is not likely to be peaceful).

No one knows the future, and the future for Venezuela seems quite uncertain. The Trump II Administration will probably loose interest in the country once all the Oil is extracted (if this is even a practical possibility given the country's political uncertainty and deteriorating infrastructure).

If you are interested in understanding more about the US Invasion of Venezuela, here is an explainer from Heather Cox Richardson:

For more of my posts on Venezuela, see the Blog Roll (here).

Notes

** One Geopolitical Alignment I have not presented in the graphic at the beginning of this post is alignment with China. The uncontrolled, exponential increase in Hardship as a result of alignment with China is so great that all the other options look no better than a Random Walk (RW).

Information about data sources and descriptions of how the State Space models were constructed can be found in the Boiler Plate.

VEL20 Hardship Measurement Model

Three components were extracted from the Hardship Indicators: HARD1 = (Overall Growth), HARD1 = (CPI-LU-GINI) and HARD3 = (POV-FAM.WRK-CPI). Definitions of the indicator codes are given below. 

VEL20 Hardship Indicator Codes

The construction of the HARD index involves sixteen indicators drawn from the World Development Indicators (WDI, see Shefner et. al., 2015).

VEL20 Hardship AIC Statistics

Seven Hardship models were estimated** and the Akaike Information Criterion (AIC) statistics are presented above (smaller the better). The best short-term model is a Random Walk (RW). The best Attractor Path model is the World System (WL20).