USL20 Health Care Forecasts

Recently, the PBS News Hour interviewed a Primary Care Physician (here) to discuss problems in the US Healthcare System.

The summary of problems (from Google AI, above) suggests the following solutions  (also Google AI) to get control of the system:

To help understand the problems and difficulties, I ran four forecasts with the USL20HC Model (presented in the graph above). Both the Business-As-Usual (BAU) model and the USL203 Model as input** are unstable. Stabilizing (controlling) the BAUC model produces more moderate growth until after 2100.

Controlling specific parts of the system (Prices and Hospital Investment) without affecting Quality of Service will not be easy. Attempts to control Prices have failed (see Pasdirtz, 2007) largely for political reasons. ChatGPT notes:

A reduction in demand for Healthcare when the Baby Boomer Generation has aged out of the system might help. Until then, I do not see the political will necessary to change the system. However, Healthcare costs are directly related to the US Affordability Crisis (Google AI):

If dealing with the US Affordability Crisis becomes one of the outputs of the US Political System, then Healthcare expenditure has to be considered. If the US Healthcare System becomes more fully integrated with the US Political System, the relationships between HC1 = (Growth - Hospitals) might become more closely related to Austerity, Hardship and Debt management--and be affected by Growth or Collapse in the US Political System.

Right now, problems in the US Healthcare System are more a function of what the US Political System thinks it is supposed to be doing for the American people. In the Trump II Administration, it is not entire clear what the US Political System thinks it is supposed to be doing for the American people.

Notes

• Healthcare in the United States  largely provided by private sector healthcare facilities, and paid for by a combination of public programs, county indigent health care programs, private insurance, and out-of-pocket payments. The U.S. is the only developed country without a system of universal healthcare, with around 92% of the population covered under some kind of health insurance for some, or all of the year.
  
  
• The Affordable Care Act  formally the Patient Protection and Affordable Care Act (PPACA) and informally known as Obamacare, is a landmark U.S. federal statute enacted by the 111th United States Congress and signed into law by President Barack Obama on March 23, 2010. Together with amendments made to it by the Health Care and Education Reconciliation Act of 2010, it represents the U.S. healthcare system's most significant regulatory overhaul and expansion of coverage since the enactment of Medicare and Medicaid in 1965. Most of the act remains in effect.
  
  
• Medicare Sustainable Growth Rate a method used by the Centers for Medicare and Medicaid Services (CMS) in the United States to control spending by Medicare on physician services.

** The idea behind using the USL203 Model as input is to keep growth of the US Healthcare system in line with growth of the US Economy (see Pasdirtz, 2007). See also, US Healthcare, Austerity and Debt.

Pasdirtz (2007) Controlling the US Healthcare System with Policy Wedges Springer Health.

For more of my posts about the US Healthcare system, see Blog Roll: Healthcare. For more information about how the State Space models were constructed and the data sources, see the Boiler Plate. You can run the USL20HC Model model yourself using the R-code on my Google Site.

USL20HC Measurement Model

The indicators above implement the basic Kaya Identity: N -> L -> Q -> K -> GDP.

Expanding the Kaya Identity to fit the US Healthcare system, we get the Directed Graph above.

Three components in the USL20HC State Space (computed using Principal Components Analysis, PCA) explain 99.80% of the variation in the indicators. HC1 is the Hospital-Growth Controller. HC2 is Output Controller and HC3 is the investment controller.

Using the Expanded Kaya Identity (above) chatGPT suggests controlling the US Healthcare system by direct interventional in the following indicators: Capping Prices, Controlling Investment and limiting Hospital Consolidation. Healthcare labor and insured population would depend on the growth limits imposed. Direct intervention would allow direct control of growth rates.

USL20HC BAU Model System Matrix

The USL20HC Model has two unstable components, HC1= (Hospital-Growth Controller) and HC3 = (Investment Controller).

USL20HC BAUC Model System Matrix

Notice that stabilizing the USL20HC Model model turns the HC1 = (Hospital-Growth Controller) into a Random Walk while HC3 = (Investment Controller) requires a reduced growth rate.

 

Austerity Forecasts for the UK (1980-2060)

The AUST index (see the details below) captures a number of issues of importance in UK Politics: (1) Increasing military expenditures to meet Russian Challenges and US withdrawals from NATO, (2) Increasing Health Expenditures to upgrade the National Health Service (NHS) and at the same time, (4) Not reducing Education Expenditures and (5) Not increasing overall Government expenditures.

Notes

• Shefner, 2015 here and here Austerity and Anti-Systemic Protest, JWSR.
  
  
  

UK AUST Measurement Model

The AUST index has three components that explain 96% of the variation in the indicators. AUST1 = (Overall Growth), AUST2 = (GE+G+GE-GH) and AUTS3 = (G+GM-GE-GH) where GE=(Government Education), G=(Total Government), GE=(Government Eduction), GH=(Government Health) and (GM=Government Military).

Overtime, AUST1 increased and reached a asymptote around 2010, AUST2 peaked in 1975 and 2010 and AUST3 increased from 1975 until 2000 and then started increasing again after 2010.

UK AUST1 AICs

The best AUST1 model takes the W-index as input.

UK AUST1 W Input Model

The AUST1 W-Input model is stable with negative effects from W3 (World Commodity Markets).

Over time

W3 peaks around 1980 and increases again after 2010.

Hardship Forecasts for the United Kingdom (1980-2060)

Notes

UKL20 HARD Measurement Model

UK1 AIC Statistics

 

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

What If Iran Dominated the Middle East? World-System (1960-2100)

 

Iran has currently reentered talks with the US over the Iranian nuclear program (here) after the US Bombed Iran's nuclear facilities on June 22, 2025. Iran and the US have had a long history of troubled and turbulent relations. Both the US and Israel seem to fear that one day a nuclear powered Iran could dominate the Middle East. 

The best model for the Middle East is to stabilize growth rates with no Geopolitical Alignments. 

Since I have models of the Iranian (IRLM), the Middle-Eastern Regional (MEA _BAU), the US (USL20) and the World (WL20) economies, I can predict different paths of overall growth under different Geopolitical Alignments.

• The Best Model (in terms of growth) is the MEA BAU (Business as Usual) model, essentially the Middle East without a dominant regional hegemon.
• The Next-Best Model is MEA driven by the Iranian Economy (IRL20)
• The Also-Ran Models are MEA driven by the US Economy (USL20) and the World System (WL20) when compared to a Random Walk (RW, the Middle East struggling to find some Geopolitical Alignments that work).

The only one of these models that is stable (see the AIC Statistics below) is MEA linked to the World System (WL20), but that  model peaks after 2020 and then declines. In other words, stability for the Middle East would involve growth-and-collapse rather than a steady state (growth rates of the BAU model could easily be modified to produce a steady state, see the MEA_L20 code).

Notice in the MEA_L20 code, stabilizing the system is not enough to prevent collapse. Growth rate of the Malthusian Factor, MEA2= (N-CO2-EG-Q), must be reduced beyond simply stabilizing the system. 

A simple summary of the MEA Measurement Model above is that growth is controlled by a Malthusian factor, MEA2 = (N-CO2-EG-Q), and Energy Use, MEA3 = (Q-E). The interactions between the Control Components and Growth (in the System Matrix):

are small. You could also experiment with strengthening feedback effects by modifying the off-diagonal elements of F.

For the future, ChatGPT reports:

 

Notes

For more of my posts on Iran, see the Blog Roll. For more information about data sources and about how the State Space Dynamic Component Models were constructed, see the Boiler Plate.

IR Measurement Model

The IR Measurement Model has three components: IR1 = (Growth), IR2 = (0.9091 LU - 0.335 KOF) and IR3 = (0.827 KOF - 0.3878 LU - 0.258 EF - 0.217 EG) where LU = Unemployment, KOF = Globalization, EF = Ecological Footprint. Notice the low weightings on HDI, the Human Development Index.

MEA Measurement Model

The MEA Measurement Model has three components that explain 99% of the variation in the indicators: MEA1 = (Overall Growth), MEA2 = (0.8746 LU - 0.361 EG - 0.2320 CO2), MEA3 = (0.708 Q - 0.604 EG) where LU = Unemployment, EG = Energy use, CO2 = Emissions and Q = GDP. Briefly, Growth is controlled by an Unemployment-Energy use controller and a GDP-Energy use controller.

IR_MEA Model

The MEA1 model is unstable.

MEA BAU Model

The MEA L20 System Matrix has three unstable diagonal coefficients (greater than 1.0).

IR_MEA AIC Statistics

The IR_MEA models (RW, BAU, World, US and IRL20) are all very close together with the RW actually being best.

World-System (1970-2100) Inequality Forecasts for Italy

                     

This page is UNDER CONSTRUCTION but you can study the graphic, the State Space model outputs and the Wikipedia links below. 

The best model (using the AIC Statistics) is driven by the EU index but the best model, in terms of reducing Inequality (GINI coefficient) is input from the World System.

Notes

You can run the ITL20 Model in R-code (here). For more of my posts see Blog Roll: Italy, the Boiler Plate and the Introduction to State Space Models.

Questions

1. Is the story of Inequality in Italy simply a story or "rich vs. poor" people?
2. How is Inequality controlled in Italy (see GINI2 and GINI3)?
3. It Italy became a Steady-State Economy, would stable, current levels of Inequality be acceptable to the Political System?

Wikipedia Links

• Economy of Italy a highly developed social market economy. It is the third-largest national economy in the European Union, the 8th-largest economy in the world by nominal GDP, and the 12th-largest by PPP-adjusted GDP.
• Politics of Italy  conducted through a parliamentary republic with a multi-party system. Italy has been a democratic republic since 2 June 1946, when the monarchy was abolished by popular referendum and a constituent assembly, formed by the representatives of all the anti-fascist forces that contributed to the defeat of Nazi and Fascist forces during the liberation of Italy, was elected to draft a constitution, which was promulgated on 1 January 1948.
• History of Italy inhabited by humans since the Paleolithic. During antiquity, there were many peoples in the Italian peninsula, including Etruscans, Latins, Samnites, Umbri, Cisalpine Gauls, Greeks in Magna Graecia and others. Most significantly, Italy was the cradle of the Roman civilization.
• Geography of Italy includes the description of all the physical geographical elements of Italy. Italy, whose territory largely coincides with the homonymous geographical region, is located in southern Europe and comprises the long, boot-shaped Italian Peninsula crossed by the Apennines, the southern side of Alps, the large plain of the Po Valley and some islands including Sicily and Sardinia. 

Inequality Measurement Model

AIC Statistics

State-Space Models

World-System (1970-2100): Geopolitical Alignment Forecasts for Italy

 

                     

This page is UNDER CONSTRUCTION but you can study the graphic above and the State Space Model outputs below. 

The best model (using the AIC Statistics) is driven by the RW (Random Walk) model, in terms of increasing Growth is input from the EU (European Union).

Notes

You can run the ITL20 Model in R-code (here). For more of my posts see Blog Roll: Italy, the Boiler Plate and the Introduction to State Space Models.

Questions

1. What is the best Geopolitical Alignment for Italy?

Wikipedia Links

• Economy of Italy a highly developed social market economy. It is the third-largest national economy in the European Union, the 8th-largest economy in the world by nominal GDP, and the 12th-largest by PPP-adjusted GDP.
• Politics of Italy  conducted through a parliamentary republic with a multi-party system. Italy has been a democratic republic since 2 June 1946, when the monarchy was abolished by popular referendum and a constituent assembly, formed by the representatives of all the anti-fascist forces that contributed to the defeat of Nazi and Fascist forces during the liberation of Italy, was elected to draft a constitution, which was promulgated on 1 January 1948.
• History of Italy inhabited by humans since the Paleolithic. During antiquity, there were many peoples in the Italian peninsula, including Etruscans, Latins, Samnites, Umbri, Cisalpine Gauls, Greeks in Magna Graecia and others. Most significantly, Italy was the cradle of the Roman civilization.
• Geography of Italy includes the description of all the physical geographical elements of Italy. Italy, whose territory largely coincides with the homonymous geographical region, is located in southern Europe and comprises the long, boot-shaped Italian Peninsula crossed by the Apennines, the southern side of Alps, the large plain of the Po Valley and some islands including Sicily and Sardinia. 

IT1 AIC Statistics

IT1 EU Model