An editorial in the December 21 Wall Street Journal discusses the impact of a tax rate change in Oregon. The point of this posting is that predicting outcomes is not easy.
In Oregon’s case, the state voted to increase the marginal tax rate on the wealthy by ~2%. They predicted the financial benefit to the state by estimating the impact of the higher tax rate on the reported income and capital gains from the current year. This is how they sold it to the voters. The following financial year showed that the total revenue from the segment of the population that had the increased tax rate decreased significantly, -27%. How could this happen?
First, this change happened during the recession, across the change. This revenue drop occured while the economy was recovering.
It turns out that there was a steep drop in the number of people paying the higher tax rate (10,000 less or a drop of 26%) So where did they go? It has been assumed that they adjusted their financials and decisions to ensure that they ended up in a lower income bracket. This is done by delaying or eliminating the sale of assets, which was confirmed by the reduction in the capital gains in Oregon by 43% (a drop of $1.5B).
I believe the message is about the predictability of a complex system when you make a change. To model the system without any change in behavior due to the change is ignorant. In an improvement project, we standardize the work processes and end up seeing impacts well beyond the removal of a defect or reduction in time. Complex systems have so many interdependencies, that you must truly pilot test the changes before they are fully understood.