The tragedy is that there are analytical tools available which could tell us how various scenarios would play out. From the labs and universities of our country have emerged data mining, analytics, data visualization, computer processing and statistical models which can take the most complex issues and make them manageable.
The American and Global economies are complex systems. Their performance depends on complex interactions among a number of complex networks and webs.
Standard economic and financial models of the type still used in Washington have continually failed to address real world problems. The economic models, for all their apparant sophistication, still incorporate assumptions which have not been seriously updated for decades.
Financial models are largely based on the same Portfolio Theory structures which gave us Enron, Long Term Capital, and the recent global economic collapse over mortgage derivatives.
The reasons standard models don't work any more, if they ever did, is that they are not robust enough to respond to the real world. The real world is messy, uncertain, interconnected, and labyrinthine.
Traditional models postulate smooth patterns, rational behavior, and independent actions.
What the advanced models which exist in places like Los Alamos, Ann Arbor, Boston and Santa Fe do is to allow nature and the real world define itself. Using the latest data organization, analytical and visualization technology, they take raw data from the environment and let it sort itself into logical categories. They then adapt analytical structures to the patterns which emerge.
What his leads to is information for policy makers which is:
1. Holistic: All interconnections, emergences, cascades, fractal structures, and power laws are tested before conclusions are drawn.
2. Probabilistic: Various scenarios are run, and results are tabulated not just on an expected value basis, but with expected ranges of results by time frame.
3. Actuarially Sound: Demographics, credibility, homogeneity, risk and time value, are all incorporated into the model.
4. Emergent: When networks and webs result in projections where emergent structures transcend preliminary ones, those more robust projections are utilized.
As a result, the bailout and stimulus proposals can be blended with conventional government activity to produce scenarios by sector and in total. These scenarios will include probability ranges by time frame by sector.
Healthcare is a good example. In the U.S., healthcare is a complex web of patients, providers, corporations, government, employment, demographics, and administraton. Randomly injecting money into the systems will result in random welfare impact.
Only by following the money through the complex web of activity, and directing it at the micro level where possible is there a chance of having optimal impact on welfare, wellness, jobs, the deficit, and gdp.
Historical transformations in the eras of the automobile, computer, electronics, and so on have shown definite patterns. The need now is for a sustainable transition which is envoironmentally friendly and resource efficient.
Future blogs wll provide additonal material on models which respond to the landscape of the twenty first century.
Lee
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