Latest Critique of Dynamic Scoring Ring Hollow Against Actual Results

The latest critique of dynamic scoring comes from Edward D. Kleinbard, former staff director of Congress’s Joint Committee on Taxation (JCT). In a recent opinion piece in the New York Times, Kleinbard argues that dynamic scoring is impractical because “dynamic modeling relies on many simplifying assumptions…and different models’ predicted feedback effects vary wildly, depending on the values selected for those uncertain assumptions.” The resulting uncertainty increases the “risk of a political thumb on the scale.

Kleinbard’s charge against dynamic scoring rings a bit hollow considering that the JCT performed dynamic analysis of two major pieces of legislation during his tenure on the committee. The first analysis showed that temporary tax cuts were not a panacea, had limited effect on boosting long-term economic growth, and fell far short of paying for themselves. The second dynamic analysis provided an early warning of the potential damage that Obamacare’s tax hikes could have on the economy. Our economy might be better off today had lawmakers paid heed to these JCT studies.

JCT’s Dynamic Analysis of Temporary Tax Cuts

The JCT’s macroeconomic analysis of the “American Recovery and Reinvestment Tax Act of 2009” provided lawmakers with some valuable insights into the limited value of temporary tax cuts. For individuals, the bill included the “’making work pay’ tax credit of 6.2 percent of earnings up to $500 per single filers and $1,000 for joint filers.” For businesses, the bill included a one-year bonus depreciation and allowed for a five-year carryback on net operating losses.

Using their Macroeconomic Equilibrium Growth (MEG) model, JCT determined that the net economic effect of these temporary tax cuts were, not surprisingly, temporary.

“At the peak of the stimulus effect, in the fourth quarter of 2010, consumption is increased by .8 percent, real Gross Domestic Product (“GDP”) is increased by 0.5 percent, and employment by .6 percent relative to what they would have been without the tax stimulus. The growth effects of the stimulus decline quickly once most of the tax changes have expired….”

The model also showed that the resulting growth from the tax cut did generate a “revenue feedback of 12 percent, relative to the cost of the tax provisions as estimated using conventional revenue analysis,” but well short of paying for themselves.

While JCT ran these simulations using different assumptions, none of these results are in the least surprising or subject to debate among economists—temporary tax cuts have little impact on long-term economic growth.

JCT”s Dynamic Analysis of the First Draft of Obamacare

Lawmakers should have paid even closer attention to JCT’s dynamic modeling of “America’s Affordable Health Choices Act of 2009,” otherwise known as the House-passed version of Obamacare. While many of the specifics of this first draft of the Affordable Care Act would change by the time the final bill reached President Obama’s desk, the House bill contained all the basic elements of the final plan—a host of revenue raisers to fund subsidies for the uninsured.

The tax increases totaled $790 billion tax hike over ten years, including: a surtax on high-income taxpayers; taxes on individuals who failed to purchase insurance on their own; and, taxes on employers who failed to insure their employees. The subsidies, which totaled $840 billion over ten years, included an “affordability credit” to help families with incomes below 400 percent of the poverty rate purchase insurance through the new health insurance exchanges.

JCT economists ran three simulations of the major components of the bill using two assumptions of the response of the Federal Reserve to the policy changes; First, assuming an active Fed in response to any demand shocks and, second, assuming a neutral Fed, or no response to demand changes.

Below are two tables showing the economic effects of the tax and subsidy provisions. Table 1 shows that the tax increases alone would have reduced GDP by as much as 1.5 percent, lowered the capital stock and employment, and actually reduced federal receipts because of the lower growth.

Table 2 shows that the tax subsidies would have only modestly moderated the negative economic effects of the tax hikes. All the major economic indicators—GDP, the capital stock, employment, and federal receipts—are still lower than what the level of the economy would have been under current law (i.e. without the health care law). The third simulation (not shown here), included the bill’s changes to Medicare and Medicaid. The results are largely the same as the first two simulations except for some residual effects of the higher deficits resulting from the increased entitlement spending.

While Kleinbard makes a big deal out of the assumptions that modelers must make and the debate over how interest rates may or may not respond to policy changes, this is a red herring. Despite the different assumptions that JCT economists used in their simulations, the results all pointed in the same direction—negative. As the results of these dynamic analyses showed, the magnitude of the estimated effects of the policies may differ, but the signs of the estimates are all the same. And that is the most critical information that lawmakers need to know to enact good tax policy and don’t get with conventional scoring.

In his conclusion, Kleinbard loses any remaining impartiality by calling dynamic scoring a “Trojan horse” delivered by “political factions convinced that tax cuts are the panacea for all economic ills.”

This is where he is most wrong. Dynamic scoring is not a plot to cut taxes without paying for them, rather it is an important tool for raising the tax IQ of members of Congress so that they understand the different effects that various tax increases or tax cuts have on the economy. The ultimate goal is to enact tax policies that improve the lives of all Americans, which won’t happen if we continue to protect Washington’s status quo.