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The truth about tax reform: Can dynamic scoring truly reflect the economic impact?
Dynamic scoring has become a hot topic in the U.S. government’s tax policy discussions. Dynamic scoring is a technique used to forecast government revenues, spending and budget deficits that adjust based on how people and organizations respond to changes in tax reform or other fiscal strategies. Unlike "static scoring", dynamic scoring attempts to more accurately reflect the impact of tax changes by predicting the reactions of economic actors.
Dynamic scoring relies on economic models that predict human behavior after tax or other policy changes are implemented.
However, the non-determinism of dynamic scoring is also that for proposals that differ significantly from current policy, forecast uncertainty increases significantly. In practice, these models rely on a large amount of judgment, and there is currently no evidence that dynamic scoring is more accurate than static scoring.
Some economists argue that conclusions based on dynamic scores are often overly optimistic. They pointed out that the U.S. Congressional Budget Office (CBO) actually includes some dynamic scoring elements in its approach. And if more dynamic scoring is added to budget analysis, it may lead to the risk of politicization.
The experience of the U.S. government (2015-2018)
Between 2015 and 2018, many U.S. Republican legislators pushed for the use of dynamic scoring to argue that supply-side tax policies, such as the Bush tax cuts of 2001 and 2011, could deliver more benefits than static scoring would predict. High gross domestic product (GDP) growth and increased tax revenue. Although this proposition has been questioned by some economists, it still gained a lot of support during the legislative process.
The results of dynamic analysis depend on assumptions about future behavior and rates of change.
In addition to what Congress has done, many state governments have also adopted dynamic scoring policies. In the case of Kansas, the state government reduced personal income taxes in the hope of economic growth and relied on positive dynamic scoring assumptions to examine tax revenue growth. However, the results of this policy did not meet original expectations. Instead, it triggered a sustained revenue deficit, forcing the legislature to adjust the tax system in 2016.
Lessons from Kansas
The Kansas example highlights the potential risks of dynamic scoring in practice. Starting from the idea that "tax cuts can bring immediate and lasting benefits," the local government reduced investment in infrastructure and education, but subsequently suffered fiscal deficits and poor economic performance.
Kansas’ Rainy Day Fund reports that funding levels are $570 million lower than before the tax cuts.
This case forced legislators to re-evaluate their tax reform policies, and ultimately made corresponding adjustments in the election. The elected legislative body voted to pass the bill, although it was vetoed by the governor at the time, but it became a dynamic Marks of marking for questioning and reflection.
Thinking about potential future impacts
Do dynamic scores really reflect the economic impact of tax reform? The answer to this question seems to remain unresolved, especially in the face of potentially large discrepancies between the effects of policy implementation and expectations. Whether future tax reform policies should rely more on the assumption of dynamic scoring, or whether the conservatism of static scoring should be more carefully considered, remains a challenge for policymakers.
Faced with the complexity and unpredictability of this category, we can’t help but think: Can fully trusting the rationality of dynamic scoring really bring us stable income and development in the future economy?
