The Economics Simulation Project – Part 1


Std Laffer Curve


Equally Valid Possible Laffer Curve

While discussing the pros and cons of the Laffer Curve (at times a bit too loudly), I realized a basic problem with the standard Laffer Curve Diagram as it is normally shown; it has no numbers along the axes, which means that the chart is purely conjectural and any relationship to the actual economy is purely coincidental. And there is no way to prove that the usual shape of the Laffer Curve is more (or less) accurate than the curves shown in the second image or third image. Without hard numbers and actual research being done, there’s no way of determining the shape of the curve and therefore it is impossible to develop a tax policy that optimizes collection of tax revenue. So instead doing research, they did what economists do best, they made assumptions and then threw a lot of fancy math equations and “proved” what they already believed.


Another Potentially Valid Laffer Curve

At which point, it occurred to me that what is really needed is some kind of empirical evidence instead of theoretical conclusions. Economics, as currently practiced, is taught and discussed using basic assumptions that are never tested or proven and many times seemingly unreasonable. In fact, Milton Friedman, the driving force of the Chicago School of Economics that forms the bedrock of the free market beliefs in favor today stated in no uncertain terms that the assumptions used when discussing economics did NOT have to be realistic or applicable to the real world. Apparently economics has triumphed over GIGO (Garbage In, Garbage Out).

If only there was some way to simulate the American economy and get empirical results, instead of theorizing  . . .

Many have worked on simulating economies before, but as best I can tell, they start by turning their assumptions into math equations and when they are finished running their equations, they have “proved” exactly what they assumed in the beginning. Which allows others to make different assumptions into different equations and generate totally different results. It’s not a very satisfying solution.

The EconoSim Project

Which is where the Concurrency Explorer (ConcX) and Avian Computing come in. Instead of trying to build formulas and equations that mimic human behaviors, ConcX birds can be developed that buy stuff and spend money in ways that generally mimic the way that actual consumers and businesses and governments do. So far, Consumer birds have been developed that “earn” salaries and pay expenses (food, clothes, medicines, rent or mortgages, transportation, etc). Because each Consumer has a budget (based on their earnings) and expenses (again based on their earnings), it becomes possible to identify and track where their money is spent over the years. Perhaps more importantly, Consumers also track where they didn’t spend money, making it possible to precisely estimate how much economic activity was subtracted from the GDP.

In addition to Consumer birds, Vendor birds collect the purchase payments that the Consumers make while Government birds collect taxes that they Consumers pay on their income and purchases.

For a typical run, a different Consumer bird is setup to represent each quintile (20%) of American society. Additional Consumers can be setup with any levels of income or expenses desired. The decision to categorize Consumers by quintile is based on the data that is most readily available.

Data Sources

The data for salaries and expenses are based on data collected by the Bureau of Labor Statistics going back to early 1980’s. Additionally, the percentage spent on each category of expense is also available. Income and poverty data from US Census Bureau is also used, as well as reports generated by the Congressional Budget Office (CBO).

There are several reasons for going back only to the early 1980’s. Primarily and most pragmatically, the data prior to the 1980’s is structured significantly differently, requiring a major effort on the part of yours truly to make the early data usable. But there is another reason. Inflation was rampant in the 70’s and early 80’s, disproportionately affecting different categories, making it more difficult to use the data before 1984-ish.

Consumer Expense Categories

Consumer expenses are based on the same representative basket of goods and services purchased by consumers each month used to calculate the Consumer Price Index (CPI). This data is collected monthly by the Bureau of Labor Statistics (BLS) and is publicly available on their website. There are literally thousands of items in the basket whose prices are tracked from month to month in locations all across America. These individual prices are then put into eight major categories:

  • Housing
  • Food and Beverage
  • Apparel
  • Transportation
  • Medical
  • Recreation
  • Education and Communication
  • Other

By following these same categories in the Consumer birds, we are able to leverage the data made available by the BLS as well as significantly reduce the number of assumptions that need to be made to estimate consumer expenses (I know that many of my initial assumptions about expenses were wrong, based on the amounts & percentages provided by the BLS).

Using this publicly available data also ensures that any others who attempt to simulate the economy have a common starting point for their simulations or analyses. Using common data allows other projects analyzing or simulating the economy to make direct, apples to apples, comparisons.

More in the next blog

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