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Dynamic Analysis and Scoring
Testimony before the House Committee on the Budget
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Note: The full oral transcript is below. The full written testimony is available in its entirety in the Portable Document Format (PDF).
Chairman Nussle, Ranking Member Spratt, and members of the committee. Thank you for inviting me to present my views on dynamic analysis and scoring.
With three economists on this panel, I think it is safe to say that we would all like more attention paid to the economic effects of public policies. The big question is whether dynamic scoring or dynamic analysis is the best way to bring such analysis to bear on public programs. My conclusion is that, given the current state of economic knowledge, including macroeconomic feedback effects (dynamic scoring) in revenue estimates is not feasible or desirable. However, dynamic analysis is useful as a complement to policymaking.
Federal tax and spending policies have an effect on the economy and citizens' well-being. Obviously, we should measure those effects as accurately as we can simply as a matter of responsible budgeting. What's more, the effects of policies on the economy clearly should be considered as a factor in assessing their desirability. All else equal, pro-growth policies are better, although there is often a trade-off between economic efficiency and other goals, such as fairness; growth is only one factor to consider.
By longstanding practice, official revenue estimates are dynamic in a microeconomic sense. They account for all the measurable behavioral responses that can be anticipated consistent with an assumption that macroeconomic aggregates-including labor supply, saving, and gross domestic product-are held constant.
What about macroeconomic effects? Most economists would agree that a major tax reform in which loopholes were eliminated and tax rates lowered, holding overall revenues constant, would increase economic growth, although there would be a wide range of estimates of how much.
But most tax proposals considered by Congress would not fit in this no-brainer category of growth enhancers. Most recent tax bills contain a hodgepodge of good and bad provisions-at least in terms of their effects on growth-including targeted tax breaks that arguably weaken the economy and create new opportunities for tax sheltering.
The biggest problem, though, is that recent tax bills have produced significant revenue losses with no indication of how those losses will be offset. Without knowing that, it is impossible to assess the economic effects, or even to measure whether the economy will be stronger or weaker in the long run.
Analyses by CBO, JCT, and Treasury have all concluded that the way current tax cuts are paid for can fundamentally alter the conclusions about their growth effects. It is impossible to predict whether the tax cuts will ultimately be good or bad for the economy unless you know how they will be paid for.
And, by the way, tax cuts do not pay for themselves. All credible analyses of the recent tax cuts reach that conclusion. For example, the Treasury Department's recent study concluded that, under the best of circumstances, the macroeconomic feedback effects of the President's tax cuts would offset no more than 10 percent of the revenue loss. And, depending on financing, the feedback could be negative.
Since it is impossible for official scorers to predict how the deficits will be closed, they cannot produce a single point estimate (a dynamic score) for the long-term effect of deficit-financed tax cuts. There is a related issue in the short run. The effectiveness of tax cuts depends on whether and how the Federal Reserve responds.
Economists can provide some useful insights about the potential range of economic effects of tax policies, especially in the long run, but it is important to understand that macroeconomic models are more valuable for demonstrating the channels through which policy can affect the economy than for providing numerical estimates. Many fundamental parameters-including how people respond to incentives to work or save more-are highly uncertain. We do not understand well how people form expectations about the future in the context of uncertainty. Because of limitations of computational power, the models necessarily have to vastly simplify reality-tens of thousands of products, goods, and services are represented by at most a few representative sectors. The range of differences of individuals in terms of preferences, education, income, family structure, and age is similarly condensed. The mind-numbing complexity of the tax code, which creates costs for businesses and individuals and opportunities for tax sheltering disappears in the models.
Nobody knows how important these simplifications are. While careful researchers like Professor Diamond work tirelessly to calibrate their models to reality as well as they can, there is tremendous uncertainty about the statistical properties of the model's long-term predictions.
Despite its limitations, dynamic analysis is potentially a useful complement to policy making. The models tell us that certain kinds of policies rank higher than others. Similarly, microeconomic analysis of the efficiency effects of targeted taxes and subsidies would be a useful component of the policy process.
Note: The full written testimony is available in its entirety in the Portable Document Format (PDF).