Via the TaxProf Blog, a new Congressional Research Service report tackles the question of the effects of corporate tax reform on government revenues (specifically if there is a “laffer curve”). This bit excerpted on Paul Caron’s blog caught my eye:

The analysis in this report suggests that many of the concerns expressed about the corporate tax are not supported by empirical data. Claims that behavioral responses could cause revenues to rise if rates were cut do not hold up on either a theoretical basis or an empirical basis. Studies that purport to show a revenue maximizing corporate tax rate of 30% (a rate lower than the current statutory tax rate) contain econometric errors that lead to biased and inconsistent results; when those problems are corrected the results disappear. Cross-country studies to provide direct evidence showing that the burden of the corporate tax actually falls on labor yield unreasonable results and prove to suffer from econometric flaws that also lead to a disappearance of the results when corrected, in those cases where data were obtained and the results replicated. Similarly, claims that high U.S. tax rates will create problems for the United States in a global economy suffer from a misrepresentation of the U.S. tax rate compared to other countries and are less important when capital is imperfectly mobile, as it appears to be.

Could it be that the CRS is familiar with bias and inconsistency? And lo and behold, from inside the PDF:

In their study, Brill and Hassett use panel data for the OECD countries from 1981 to 2003.30 They use regression analysis (OLS) to estimate the effects. Brill and Hassett find that the corporate tax rate has at first a positive effect on corporate tax revenues as a percentage of GDP and then a decreasing effect—the effect looks like an inverted U, the shape of the classic Laffer curve. All of their coefficient estimates are statistically significant. However, they do not account for problems often encountered with the use of panel data, and their coefficient estimates would appear to be biased and inconsistent.