Scientific Foundations of Dynamic Scoring of Tax Bills
September 14, 2006
The U.S. House Committee of the Budget held hearings yesterday on the controversial topic of whether tax and spending bills should be “dynamically scored”—that is, whether estimates of their budget impacts should take into account how law affects larger economic variables like GDP growth rates.
Douglas Holtz-Eakin of the Council on Foreign Relations was one of those presenting testimony. Here’s an interesting clip from his presentation. In it, he explains how current Congressional Budget Office and Joint Committee on Taxation estimates of the costs of tax and spending bills are not really “static” as is often claimed by commentators. Instead, they take many behavioral factors into account. Dynamic scoring would simply extend that to larger macroeconomic factors as well. And while dynamic scoring may be difficult to implement in practice, it’s probably worth the effort, as it would force policymakers to take into account the effects of policy on the overall U.S. economy:
Dynamic Scoring is Good Science Budget “scores” are estimates of the change in the federal unified budget that would result from the passage of specific statutory language. All proposals are measured relative to a single, fixed baseline outlook for the budget which is, in turn, built upon a projection for the United States economy. A key feature of current scoring is that in evaluating legislation, the aggregate amount of economic activity – total production and income – is assumed to be unchanged from its baseline values.
It is this feature that has led some observers to refer to current scoring procedures as “static.” Unfortunately, this label has caused certain critics to mistakenly conclude that current procedures do not recognize the incentive effects of legislation – that firms, workers, investors, and households continue their economic lives as if nothing had changed. Nothing could be further from the truth. For example, in scoring the impact of the Medicare Modernization Act (MMA), congressional analysts necessarily had to incorporate the decision of firms to offer insurance contracts for the cost of outpatient pharmaceuticals and bid for customers, the willingness of seniors to purchase such insurance, changes in the amount of drugs prescribed and purchased, take-up of low-income subsidies, and a myriad other decisions by households, firms, and governments. However, in keeping with current practice, the overall level of gross domestic product and national income was assumed to be unchanged.
Dynamic scoring would expand the range of economic impacts to include the pace of economic growth – that is, estimating the change in the aggregate level of economic output and income. This has some desirable features. In estimating the impact of the legislation, analysts would (a) consider the direct impacts on program costs and tax receipts; (b) evaluate the effects on incentives to work, save, invest and conduct economic affairs; (c) estimate the resulting change in the overall level of economic activity; (d) compute the impact of this higher or lower level of economic activity on program costs and tax receipts; and (e) calculate the net impact of the legislation on the unified budget. The key difference is step (d), which is in turn built upon (c).
A virtue of dynamic scoring is that it extends analysis of budget policy to include economic policy dimensions. Specifically, dynamic scoring requires that analysts incorporate into their evaluation of legislation all the economic feedbacks at the individual, household, firm, and national level. For this reason, it has the potential to distinguish between those policies which are equal in their budget cost, but very different in their economic incentives. Indeed, one of the most attractive aspects of dynamic scoring is its promise of allowing policymakers to distinguish between economically efficient tax and spending policies that promote growth, and those that work to reduce the living standards of future generations.
Read the full testimony here. In our recent podcast interview with Holtz-Eakin, he made a similar point about the scientific foundations of dynamic analysis. See also our previous post on the costs and benefits of dynamic scoring.
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