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Dynamic Scoring: Counterpoint

July 28, 2015 01:14 PM

Jane G. Gravelle
Article first appeared online: July 22, 2015

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Stepping beyond the obvious argument that reliable estimates of macroeconomic effects would be desirable, it is important to ask two questions. First, need they be incorporated into scores or should they be provided as a supplement to scoring? Second, is there a sufficient consensus about the magnitude (and even direction) of the effect? These issues are not unrelated—the more disagreement in the profession about macroeconomic effects, the less attractive is the option of incorporating them into a single formal score and the greater the potential risk to budget discipline.

Dr. Holtz-Eakin’s claim that “...uncertainty and difficult analysis are part and parcel of the scoring business and a move to dynamic scoring would not change things significantly,” is at the heart of our disagreement. Aside from the fact that macroeconomic scoring necessarily imposes another layer of uncertainty, most conventional scores are not subject to a similar degree of uncertainty.

Dr. Holtz-Eakin provides an example of uncertainty for the Medicare drug program, which was both new and voluntary. Tax revisions, which are at the center of interest in dynamic scoring, are typically neither. Most tax items in the 2014 Camp tax reform proposal (JCT, 2014) appear on tax returns that individuals have no legal choice to avoid. Mandatory spending programs that alter existing programs that are compulsory (such as Social Security and Medicare hospital insurance) should have a certainty similar to most tax scores, and ones where participation is voluntary, such as other portions of Medicare and transfer programs, have a great deal of existing data available.

By comparison, macroeconomic estimates exhibit much more uncertainty. The JCT’s estimate for an individual rate reduction in 2005 (JCT, 2005) reported variations in macroeconomic effects equal to 17 percent of the cost. It is difficult to imagine a similar degree of uncertainty in a conventional estimate of revenues lost from rate reduction.

While Dr. Holtz-Eakin stresses that conventional scoring is as uncertain as macroeconomic scoring, he simultaneously suggests that “...a disciplined approach [to macroeconomic scoring] will get the average about right.” If there is a consensus that permits this “getting it right” the public has not been clued in. The CBO’s first dynamic analysis of the President’s budget, (CBO, 2003) undertaken while Dr. Holtz-Eakin was director, showed a range of effects equal to 2 percent of GDP, or almost 13 percent of total revenues at that time. The JCT estimate of the 2014 Camp proposal (JCT, 2014) had a range equal to 1.5 percent of GDP and 15 percent of the income tax revenues it was aiming to reform. Why report such ranges if a consensus estimate was at hand or, at least, why not identify a preferred estimate and the reason for that choice?

The CBO and JCT could have taken a position on important issues such as including cyclical effects or using direct supply elasticities rather than relying on intertemporal models, or even how to close intertemporal models, but they did not. One can only infer that they perceived a lack of consensus on these issues. As long as such a lack of consensus exists, it seems better to retain the approach of providing macroeconomic analysis with a variety of assumptions rather than incorporating some portion of these effects in the formal scores.
As I indicated in my point piece, there are assumptions that I believe are most appropriate, but those assumptions (using reduced form labor supply responses and excluding cyclical effects) would likely make dynamic scores too small to matter.

Let me now turn to some minor points. First, practically speaking, macroeconomic analysis cannot be prepared for every minor bill. However, I would take issue with the argument that confining the effects to large proposals is desirable. If a small tax cut returns more dollars relative to its conventional cost than a large one, is that not something desirable to know?  Focusing on major proposals not only creates a bias in making single large changes rather than smaller incremental ones, but it also opens the door to gaming the system by packaging proposals with positive effects into large packages and splitting those with negative effects into smaller ones.

Second, the advantage cited of allowing policymakers to distinguish between proposals that increase growth and those that reduce it places emphasis on growth when there are other aspects of policymaking that may be equally important. Economic growth objectives may conflict with distributional ones, but as of the present there is no mandate to measure distributional effects. Similarly, economic growth may conflict with social welfare objectives, but there is no mandate to measure social welfare. For example, labor participation would no doubt increase if we abolish Medicare and Social Security but such a policy may reduce welfare because of various market failures that make social insurance desirable.

Third, note that the issue of stabilizing the debt only occurs when intertemporal models are used and it means that a tax policy cannot be estimated in isolation. This constraint seems to be a major drawback of using these models. At the same time, making it clear that tax cuts directed at increasing saving will eventually be offset by crowding out seems a valuable insight that is obscured by the use of intertemporal models. Policymakers need to know that even with our most generous assumptions, tax cuts reduce national savings through crowding out, and the best method of increasing savings in the economy is to reduce the deficit, even if we do it by raising taxes.

Finally, I would like to clarify the claim that the Administration has historically engaged in dynamic scoring. By longstanding practice, the Administration scores in the same way as conventional scoring by the CBO, except that it produces a baseline forecast that assumes the budget is enacted (just as the CBO and the JCT score on a baseline that assumes current law). (See Donihue & Kitchen, 1999, for a discussion of the Administration’s baseline projections). Tax changes are then scored off that baseline. That is, there is no explicit association of growth effects that offset conventional costs as is proposed for dynamic scoring. Indeed, if baseline revenues are higher because of induced growth effects, the revenue estimate will be larger, not smaller. To make this point more concrete, suppose a tax cut of 1 percent of GDP is projected to increase GDP by 1 percent. The Administration approach will cause revenue costs to be a negligible 1 percent higher. Dynamic scoring of the tax legislation at a 25 percent tax rate would cause revenue costs to be 25 percent smaller. This scoring process by the Administration has in common only that the effects of budget revisions are estimated to affect the economy for purposes of the baseline, but is clearly not the same as dynamic scoring. The White House has stated its opposition to dynamic scoring (Donovan, 2015).

JANE GRAVELLE is a Senior Specialist in Economic Policy for the Congressional Research Service at the Library of Congress (e-mail:


These views do not reflect the views of the Congressional Research Service.


Congressional Budget Office (CBO). (2003). How CBO Analyzed the Macroeconomic Effects of the President's Budget, July 2003. Found at

Donihue, M. R., & Kitchen, J. (1999). The Troika Process: Economic Models and Macroeconomic Policy in the USA, May 1999. Found at

Donovan, S. (2015). “Dynamic Scoring” is Not the Answer. Retrieved on January 26, 2015, from

Joint Committee on Taxation (JCT). (2005). Macroeconomic Analysis of Various Proposals to provide $500 Billion in Tax Relief, JCX-4-05, March 1, 2005. Found at

Joint Committee on Taxation (JCT). (2014). Technical Explanation, Estimated Revenue Effects, Distribution Analysis, and Macroeconomic Analysis of the Tax Reform Act of 2014. A Discussion Draft of the Chairman of the House Committee on Ways and Means to Reform the Internal Revenue Code, JCS-1-14, November 18, 2014. Found at


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