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.

• Business as Usual (BAU) turns out to be one of the best models given the AIC Statistics (see below).
• Random Walk (RW) the muddling-through model assumes that random attempts to reduce poverty might eventually find a solution.
• TECH Efficiency (TECHE) assumes that attempts to manipulate the intensive coefficients in the Kaya Impact model will affect poverty (Technical efficiency could reduce Poverty but it doesn't look like that is happening in the US especially in the age of AI).
• WL20-Input assumes that keeping US Poverty in line with the World-System will at least ensure that Poverty remains at world-wide acceptable levels.
• USL20 Input assumes that growth in the US Capitalist economy provides the best way to reduce poverty (in the US, increasing poverty is just part of the Capitalist system).
• TECH Productivity (TECHP) assumes that Technical Productivity (Solow-Swan Economic Model) is the primary driver of economic growth and poverty reduction (it isn't).

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).

 

Is the US Flawed Democracy?

This Page is UNDER CONSTRUCTION

Notes

• The Economist Democracy Index published by the British media company the Economist Group is an index measuring the quality of democracy across the world. This quantitative and comparative assessment is centrally concerned with democratic rights and democratic institutions. The methodology for assessing democracy used in this democracy index is according to the Economist Intelligence Unit which is part of the Economist Group, a UK-based private company, which publishes the weekly newspaper The Economist.

Economist Democracy Index

 

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

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

• Policy Wedges and State-Space Simulation Models If ever there was any political will, there is a way to control the US Healthcare System.
• US Healthcare Expenditures: Three Futures Currently, there is no political will for keeping Health expenditures in line with growth in the US or the World Economy. However, if HC Expenditure is part of the US Political System, there may be a different future.

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

Readings

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

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.