Dynamic Scoring: Meaning, Pros and Cons, Example

What Is Dynamic Scoring?

Dynamic scoring is a method of estimating the budgetary impact of a change in government policy. It is notable because it accounts for the secondary economic effects of a policy on all sources of government revenue and expenses, in addition to the direct effects of a policy on spending and revenue. In dynamic scoring, secondary effects are estimated using macroeconomic or econometric models.

Because these models can take many forms and include different assumptions, the results of dynamic scoring can be highly dependent on the specific model and assumptions used.

Dynamic scoring is contrasted from static scoring, which estimates only the direct impact that a policy change will have on government revenues and expenditures without otherwise assuming any change in the economy as a result of the policy. 

Understanding Dynamic Scoring

When any government policy changes, people will tend to change their behavior in response. To a large extent, this is usually the point of the policy change in the first place. But we also know that changes in government policy can often come with unintended consequences and that changes in people’s behavior may involve more than just immediate and direct responses. 

Because fiscal concerns are a priority for policymakers, the direct and indirect effects of a policy change on government revenues and expenditures are typically of particular interest. To this end, when a new policy is proposed, estimating and projecting the fiscal impact of the new policy on the government’s budget is a major component of the debate around the policy change. The process of estimating the fiscal impact of policy change is known as “scoring.”

How Dynamic Scoring Is Done

Scoring is traditionally done through a method now referred to as static scoring. In static scoring, the direct fiscal impact of a policy is measured or estimated using a simple model.

For spending changes this is usually quite straightforward; the fiscal impact is the amount appropriated for the expenditure or an estimate based on simple assumptions around participation or demand on a particular program. For tax policy changes, estimating revenue generation is usually simple and noncontroversial.  

For example, if a proposal is put forth to place a $0.05 per gallon retail tax on milk and 50,000 gallons of milk are bought and sold annually in a jurisdiction, then static scoring estimates that tax revenue will increase by $0.05 x 50,000 = $2,500 per year. However, because such a tax will raise the total price that consumers pay for milk, and the law of demand tells us that people will tend to buy less at higher prices, the actual tax revenue will almost certainly be less than $2,500 per year. This is where dynamic scoring comes in. 

With dynamic scoring, economists can use economic models to predict how much demand for milk will fall due to the new tax. They can then estimate how much this decrease will affect annual tax revenue.

Note that in theory, this technique should arrive at a more accurate estimate of the actual fiscal impact of a policy change. However, because dynamic scoring relies on economic theory and econometric modeling, the improved accuracy of any estimate produced will only be as good as the theory, assumptions, and model it depends on. While more accurate in theory, dynamic scoring can also introduce potential for error. 

Advantages and Disadvantages of Dynamic Scoring

Dynamic scoring has two primary advantages: It can improve the accuracy of budget scores, and it can remove bias against pro-growth policies.

When policies cause the economy to grow, they impact the budget because the government is now bringing in more revenue while spending less money on programs like unemployment. On the other hand, if the economy is slowing down, the government makes less revenue while spending more on social safety net programs.

Dynamic scoring assesses the impact of government policies beyond pure spending, making it possible to budget more accurately.

In comparison, static scoring ignores macroeconomic effects. This can cause the budgetary costs of pro-growth policies to appear higher than they actually are. Conversely, this can cause the costs of anti-growth policies to appear lower than they actually are. Dynamic scoring takes into consideration the true benefits and costs of pro-growth or anti-growth policies.

Some of the primary disadvantages of dynamic scoring are that it relies on theory-based models that are not always accurate; the fact that economists don't have a true way to measure the impact of policies in practice; and that macroeconomic models used in dynamic scoring tend to ignore certain aspects of public investment and the impact of income inequality.

Dynamic Scoring vs. Static Scoring

Static scoring assumes that tax changes don't have any effect on the decisions of taxpayers. As a result, static scoring assumes that these tax changes have no impact on macroeconomic indicators, such as gross domestic product (GDP), jobs, and investment.

Dynamic scoring, on the other hand, seeks to analyze the impact that policy changes have on the behavior of taxpayers, and how those behaviors impact macroeconomic factors. Static scoring is limited in scope and one-dimensional. Dynamic scoring is broader, encompassing a variety of areas that can be influenced by changes in policies.

Real-World Example

The Tax Cuts and Jobs Act, passed in 2017, was analyzed by the Joint Committee of Taxation (JCT) before being passed, and under static scoring, was expected to increase the budget by $1.5 trillion dollars. When dynamic scoring was used, taking into consideration macroeconomic factors, the TCJA was shown to increase the deficit by a smaller amount: $1.1 trillion.

The reason dynamic scoring showed a smaller increase in the deficit is because it showed that tax cuts would actually increase economic activity. It included the impact the act would have on disposable income, which would be increased, causing people to spend more, boosting the economy. The lower tax rates would also increase savings and investments.

The Bottom Line

Dynamic scoring is a method of calculating the economic impact of government policy. It aims to make a comprehensive estimate of fiscal impact by considering not just a policy's direct effects, but its secondary effects, as well. This includes changes how individuals and firms might respond to the policy in terms of demand, spending, and saving, for instance.

Dynamic scoring can provide policymakers with a detailed and comprehensive prediction of a policy's effects, but it's also based on econometric models which rely on assumptions, some possibly inaccurate. Dynamic scoring stands in contrast with static scoring, which is limited to estimating the direct fiscal impact of a policy.