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Static Scoring (Conventional Scoring)

Static scoring (conventional scoring) is an estimation method that, unlike dynamic scoring, assumes that tax changes have no impact on taxpayer behavior and thus have no effect on important macroeconomic measures like GDP, investment, and jobs. This provides a one-dimensional perspective about the effects of tax changes.

How Does Static Scoring (Conventional Scoring) Work?

Static scoring measures the changes in revenue assuming no consumer behavioral effects (e.g., savings and consumption) and holding Gross Domestic Product (GDP) constant.

For example, a tax base of $100 taxed at a 50 percent rate would yield $50 in revenue. Under a static score, increasing the tax burden to 60 percent would yield a 10 percent increase in revenue ($60).

Conventional scoring assumes that tax changes don’t affect the behavior of individuals and firms so would not take into account that a 10 percent tax increase might lead consumers to change how they consume or reduce consumption overall, which is often the case.

Static scoring provides legislators an incomplete picture of how tax policies impact the economy and revenues, leaving out context legislators need to evaluate the trade-offs between policies. Taxpayers are responsive to changes in marginal tax rates by changing their decisions to spend or save, to consume or refrain. Scoring should reflect this reality.

Dynamic scoring, on the other hand, gives policymakers a tool to differentiate between policies that look similar using conventional scoring methods but have vastly different effects on the economy. For example, increasing the tax rate on capital gains may yield a positive static score due to the assumption that economic behavior remains unchanged. However, after accounting for the behavior of investors responding to the tax increase, the government may actually lose revenue, producing a negative score. Thus, dynamic scoring takes into account multiple variables of individual and macroeconomic behavior absent from static estimates.

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