Monday, October 12, 2026

How is the US Economy Controlled?



This Page is UNDER CONSTRUCTION.


Oct 12, 2026 Duo Share Nobel in Economics for Work on Steering Through Booms and Busts Robert E. Hall and Michael Woodford were awarded the prize for insights that helped policymakers become “better equipped to deal with shocks in the economy,” the committee said.


Notes


USL20 Measurement Model







USL20 US2-3 Model







USL20 US2-3 Model Shock Decomposition

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Sunday, October 11, 2026

USL20 (1950-2100) San Diego Geopolitica Forecasts



This Page is UNDER CONSTRUCTION.






Notes

USL20 SD Model Measurement Matrix











USL20 AIC Statistics



USL20 BAU Model




USL20 Model







WL20 Model















 

Wednesday, October 7, 2026

WL20 Poverty Scenarios


This Page is UNDER CONSTRUCTION but the results of the graphic above make it clear that predictions for Poverty in the World-System are better than in the United  States!



Notes

World Bank Poverty Reports (not very reassuring) From 1990 to 2026, the total number of people worldwide living in extreme poverty declined from around 2.3 billion to 811 million, each trying to survive on less than $3 per day. The sharp decline over this period was largely driven by robust, broad-based economic growth in East Asia and South Asia.

Over the last decade, however, global poverty reduction has slowed substantially. This slowdown is due to a combination of interconnected crises, including sluggish economic growth, high levels of debt, the effects of the COVID-19 pandemic, conflict and fragility, and severe weather-related shocks.


These overlapping crises have hit low-income countries the hardest. At the current pace of progress, it could take decades to eradicate extreme poverty.


Extreme poverty has become increasingly concentrated in Sub-Saharan Africa, and places affected by conflict and fragility. Although a necessary condition, economic growth is not enough to break the cycle of poverty. Stronger foundational investments in infrastructure, human capital, and institutions are critical to ensure people can climb the socioeconomic ladder and escape extreme poverty.



 

Monday, September 28, 2026

USL20 Poverty Scenarios


The video below was another in a long line of crazy pronouncements from US President Donald Trump but does the US have the best poverty numbers? That's easy to check.




The graphic above plots SI.POV.DDAY for the US from the World Development Indicators (black line prior to 2010). The US did have a brief reduction in Poverty around 2010 but now we are back to Business as Usual (BAU). Like a lot of other boasts, no one knows what President Trump is talking about. However, even if not accurate, it raises the question about what to expect for the future (since no one seems to believe that Trump cares much about Poverty or the Poor).

In prior posts (here and here) I've presented forecasts for US Hardship and Poverty that (1) were not very reassuring and (2) did not suggest any policy options. In this post, I will present and discuss some Poverty Scenarios based on different drivers for policy. The graphic above presents six possible future scenarios for SI.POV.DDAY from the World Development Indicators.

The TECH models indirectly address the current concern of the impact of Artificial Intelligence (AI) on employment, that is, taking away jobs. The BAU (Business as Usual) and RW (Random Walk)  describe two options for a Benevolent Neglect Policy (see below). The USL20-Input model allows the US economy to generate whatever level of economic progress it produces in terms of poverty reduction (it doesn't). The WL20-Input lets trends in development of the World System (which appears to be doing a better job of Poverty reduction) determine levels of poverty.


The best models, in terms of keeping poverty at existing levels, are the BAU and RW (benevolent neglect, see below) models. All the other models raise US Poverty above current levels. 

        None of the models considered will Reduce Poverty in the US.


Notes

Benevolent Neglect

From Google AI:



USL20 Poverty AIC Statistics



All the AIC Confidence intervals are overlapping so it is hard to pick one model as the winner.

USL20 Poverty BAU Model




At least under the BAU model, Poverty in the US is stable (I'm not sure this is a positive finding and so much for Lyndon Johnson's War on Poverty).



 

Friday, September 18, 2026

Is the US Flawed Democracy?



This Page is UNDER CONSTRUCTION







Notes


Economist Democracy Index






 

Saturday, September 5, 2026

USL20: Healthcare, Austerity, Hardship and Debt


This page is UNDER CONSTRUCTION but you can consider the information available and the Questions below until it is complete.






The Easton Political System Model with HC1 (Healthcare), AUST1 (Austerity), HARD1 (Hardship) and DEBT1 (Debt) as outputs with input from the USL20 Model.

 




Notes

QUESTIONS

  1. What are the outputs of the Political System?
  2. Should "Healthcare" be one of the outputs?
  3. The USL20 POL Model is in growth-and-collapse model (see graphic above).

USL20 POL Measurement Model







USL20 POL Model







USL20 Measurement Model






Tuesday, September 1, 2026

A Simple Model of the US Healthcare System

 



In Pasdirtz (2007) I published a State-Space "covering model" for the US Healthcare system and generated Policy Wedges for areas of the system that needed control (see Blog Roll: Healthcare for more information). In this post, I'll present a simpler model (six variables based on the Kaya Identity, see below) that might prove useful for further policy analysis.


Starting with the basic Kaya Identity (above) where N=Population, L=Labor, Q=Production (GDP), P=Prices and K=Capital.




Adding in the Healthcare Sector (terms defined below) we have a simplified Healthcare Systems model.

Kaya Identity models are easy to understand but incomplete because all the possible feedback loops in the system are never clear. The State-Space Measurement model (computed with Principal Components--see below) has three components:  HC1 = (Growth - Hospitals), HC2 = (Population Insured + Labor in HealthCare + Hospitals) and HC3 = (Growth - Prices). The graphic above displays the state variables over time. HC1 grows over time, HC2 peaks in 1975 and HC3 is cyclical.


Notes

More information about the US Healthcare System can be found in Blog Roll: Healthcare.

Readings



USL20HC Measurement Model





The State Space of the simplified Healthcare model has three components that explain 99.8% of the variation in the indicators. HC1 = (Growth - Hospitals), HC2 = (Population Insured + Labor in HealthCare + Hospitals) and HC3 = (Growth - Prices). What the three component state variables show is that the major feedback loops in the system center around Hospitals. Another way to say that is that Hospital growth controls the system and are essentially dependent on the Population of Insured patients.

Notice, in HC2, that Hospitals peaked in 1975 and hospital consolidation increased centralization. And, HC3 peaked in 1990. Although there have been structural changes in US Healthcare, this simplified system is still unstable (as are the other models with input from either the World System, WL20, or the US, USL20. 




USL20HC AIC Statistics



Notice that all the models are unstable and would require stabilize to control the system. The best model is alignment with the World System, the WL20 model.

USL20HC BAU Model




The BAU model has two unstable components involving HC1 and HC3.