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The authors thank Tamim Bayoumi, Ranjit Teja, and participants at an IMF seminar for helpful comments. All errors remain the authors’ responsibility.
For instance, such a model would need to take into account the incentive effects of higher or lower marginal tax rates on labor supply, production, and investment—all of which are still being debated in the literature. An example is provided by Creedy and Gemmell (2004) who estimate revenue elasticities for both income and consumption taxes in the United Kingdom, using individual taxpayer data. Creedy and Gemmell (2005) refine the analysis by endogenizing the labor supply decision and thus distinguishing the “tax-wage elasticity” from the “tax-income elasticity.”
The choice of the base year is not critical for these calculations, which depend on year-to-year percent changes in tax revenue, and not on revenue levels.
These estimates are based on detailed revenue simulations, using micro data from actual tax returns combined with macroeconomic impact studies. They are prepared by the Office of Management and Budget (OMB) or the Joint Committee of Taxation (JCT), with input from the Internal Revenue Service.
Tempalski (2006) cites one of the largest errors—the Crude Oil Windfall Profit Tax Act of 1980—which was estimated to raise $21 billion in 1984, but only turned out to yield $4 billion due to a decline in oil prices. In this particular case, we used the estimates contained in Lazzari (1990). For some recent tax legislation, we used ex ante estimates provided by the Joint Committee on Taxation in order to have data on overall revenue consistent with the impact broken down by category; however, the differences are not large.
For convenience, GDP has been used as a tax base to adjust revenue in (17). It seems more accurate to use tax bases for individual revenue categories, but the differences are likely to be too small to justify the extra effort.
Revenue and other nominal variables have been deflated by the GDP deflator and are expressed in logs. All other variables are expressed as ratios. See the data appendix for a complete description.
The elasticity of individual income taxes to personal income, which is usually greater than one due to the progressivity of the income tax system and real bracket creep, will be discussed in the next subsection.
The coefficient on capital gains in the first subsample turns positive when income distribution is excluded, but it is not statistically significant.
Other variables were tried but found not to have a significant impact, including stock prices, equity market capitalization (neither of which is surprising given the presence of capital gains and income distribution), house prices, the output gap, labor market variables, and an interaction term for inflation with a dummy for the period before the tax system was indexed. We also searched for a short-run impact from the variables that were tried but rejected in the long-run equation.
Using corporate profits as defined by the IRS yielded similar results, suggesting that the difference between the definition of profits for national accounts versus tax purposes is not an issue. The output gap is expressed as actual output in percent of potential, with a positive gap indicating the economy being above full capacity.
The measure of income distribution includes capital gains; excluding these, the income share of the top 1 percent of taxpayers has risen 2.7 percentage points from 2002 to 2005. The data are an updated version of those first presented in Piketty and Saez (2003).
Capital gains are held constant from 2002 because they affect revenue with a lag in our equations, both because of the lapse in time between realization and payment of the tax, and because the data are on a calendar year rather than fiscal year basis.
The income distribution is affected by fluctuations in capital gains, as around 80 percent go to taxpayers with adjusted gross income of over $200,000 (Balkovic 2006, 2007). Using the Piketty and Saez (2003) data, we calculated that about half of the increased income share of the top one percent was due to capital gains and half from other sources. This variable also affects revenue with a lag because it is on a calendar year basis.
This includes the discrepancy between the baseline scenario and the actual outcome.
In this model, the effects of a positive and negative shock are of equal size and opposite in sign, but only the negative shock is presented.
The standard deviations of the GDP shares of capital gains and corporate profits over the 1987-2006 period are 1.5 and 1.7 percentage points, respectively.