The role of numbers in policy analysis is to reduce the dispute about whether to approve a specific policy change. That role will be served only if the process for estimating the numbers is not itself subject to dispute.
The central point of my brief remarks is that any change in the process for estimating the revenue effects of tax changes should be broadly understood and approved—preferably by the key members of both parties in each house and by the administration. Such a change should be considered the equivalent of a change in the bylaws of a club or a change in the scoring rules in an athletic league. Such changes should be approved only by the support of most of the affected groups, not by only those who expect to benefit most from the change in the short term.
Some other comparisons may help illustrate the issues bearing on the choice between static and dynamic revenue estimates: Static estimating is an application of arithmetic. Many politicians are not very good at arithmetic, but it does not evoke much partisan dispute. Dynamic estimating is based on some model of economic behavior, a model that reflects some theory of how people behave and estimates of how they respond to specific types of changes in the conditions they face. Some of the characteristic differences between parties involve differences on just these issues.
In that case, static estimating is somewhat like democracy—it may be the best deal we can make with our neighbors.
But we should try to convince our neighbors if there is reason we can do better. And dynamic estimates can be much more accurate than static estimates. In general, people will do more of some activity if the after-tax returns are increased and less of this activity if after-tax returns are reduced, and that is the basis for the higher potential accuracy of the dynamic estimates. We would probably make better tax policy decisions even on the basis of crude dynamic assumptions—for example, that tax increases increase revenue and that tax reductions reduce revenue by only half that estimated by static models.
But we should be able to make even more accurate estimates. There are still some differences in the estimates of the magnitude and timing of the responses to tax changes, but some of these differences can be resolved by focusing on the same scope of responses. For prime age males, for example, the response of hours worked to a change in after-tax wages appears to be close to zero; the effect of tax rates on taxable earnings, however, is higher, reflecting the response of taxable earnings to tax-induced effects on occupation, location, and tax avoidance. Similarly, the response of the savings rate to the after-tax interest rate appears to be close to zero; the effect of tax rates on taxable interest payments, however, is higher, reflecting the tax-induced effect on the type of investment. The full behavioral response to change in taxes is often substantially higher than the first stage response, especially in the long run.
May I suggest, however, that the revenue estimators stop short of including the potential demand-side effects of tax changes. First, there continues to be a major disagreement among macroeconomists as to whether tax changes have any significant effect on aggregate demand. (On that issue, my position is that most changes in fiscal policy have no significant effect on aggregate demand, but I acknowledge that many of my professional colleagues believe otherwise.) And second, any demand-side effects can be offset by changes in monetary policy. For these reasons, I suggest, estimates of the dynamic effects of tax changes on tax revenues should be based on supply-side models, not on the older form of Keynesian macromodels.
The next steps toward making sense of this issue, I suggest, are the following:
First, put to rest the wholly false, albeit common, charge that the unexpected increases in the federal deficit in the early 1980s were due to misleading dynamic supply-side revenue forecasts. In fact, all of the budget forecasts by both the administration and Congress were based on static revenue estimates; moreover, the OMB and CBO budget forecasts in 1981 were remarkably similar. The federal deficits of the early 1980s proved to be substantially higher than expected for several reasons—the unusually deep recession of 1981-1982, a faster-than-expected decline in inflation, and a failure to maintain spending restraint beyond the first Reagan budget. All of the budget forecasts during this period substantially underestimated the deficit, but not because they were based on supply-side models.
Second, those who favor higher taxes should acknowledge that increases in the top marginal income tax rates generate little increased revenue; a given increase in tax rates at this level is a larger proportionate reduction in the after-tax rate, and high income taxpayers have more opportunities for legal tax avoidance. Similarly, those who favor lower taxes should acknowledge that some tax cuts reduce revenues by more than the state estimates. The $500 tax credit for children proposed in the House Republican Contract, for example, would generate larger dynamic revenue losses to the extent that it increases birth rates or reduces the participation of women in the paid labor force. These examples illustrate that dynamic revenue forecasts do not necessarily favor the preferred policies of either party.
Third, the Joint Committee on Taxation should open up its estimating methods and invite peer review. May I suggest that you start this process by asking the respected National Bureau of Economic Research to sponsor studies and a conference on the JCT methodology and on the most important next steps to improve the revenue forecasts. Leading public finance economists should be asked to comment on the JCT methodology and report to Congress, maybe at hearings before this committee, on their evaluations and recommendations
And finally, pending completion of this review, no change in the JCT methodology is appropriate. A substantial consensus among leading public finance economists, I suggest, is probably necessary to broaden the support for proposed changes to this methodology across parties in Congress and with the administration. And, as I introduced my testimony, more accurate revenue forecasts from the best possible dynamic model would help resolve differences on tax policy only if the methodology by which the forecasts are generated is endorsed by most of the major participants in the policy debate.