I've heard from many sources that the corporate tax rate has a detrimental effect on the economy, and that lowering it not only has the effect of stimulating the economy, but actually raises more revenue. Is this true?
This was discussed on Skeptics.SE previously:
To steal from Borror0's answer (emphasis mine):
Taxes do affect economic growth, but not equally. From the OECD paper, "Do tax structures affect aggregate economic growth? Empirical evidence from a panel of OECD countries":
The results of the analysis suggest that income taxes are generally associated with lower economic growth than taxes on consumption and property. ... Property taxes, and particularly recurrent taxes on immovable property, seem to be the most growth-friendly, followed by consumption taxes and then by personal income taxes. Corporate income taxes appear to have the most negative effect on GDP per capita.
These findings suggest that a revenue-neutral growth-oriented tax reform would be to shift part of the revenue base towards recurrent property and consumption taxes and away from income taxes, especially corporate taxes.
Economists disagree with each other on this, and will probably continue to disagree for millenia. My short answer is don't put a lot of faith in anyone who tries to describe financial markets using statistics or rules of thumb.
Because there are so many factors effecting economy, and different ways of measuring it, economic growth depends less on corporate tax rate than a large number of other factors.
Keynesian economists clearly argue that economic output is strongly influenced by aggregate demand (total demand in the economy). They also suggest that because aggregate demand is dependent on a complex set of factors they naturally behave in erratic ways. That aspect of Keynesian economic models is less controversial than some of the other predictions made by these models.
The notion of naturally erratic economic cycles in aggregate demand is consistent with modern Chaos Theory as the math of economies are nonlinear dynamic systems with feedback. As such, economic growth is sometimes highly sensitive to initial conditions resulting in the so-called Butterfly Effect.
There is an interesting similarity between weather prediction and economic projections. With the application of computer models and supercomputers, the ability to predict weather in the short term (1-5 days) has improved substantially, but longer term prediction is not reliable at even a 30 days. Different computer models diverge in their predictions, and none are "right" because the current conditions cannot be known with sufficient detail to predict when a storm will develop much more than a week in advance.
Economic systems like weather systems are instable. For that reason a simple assumption like "corporate income taxes have a negative effect on GDP per capita" can true in some situations, and false in others. Even complex computerized economic (or weather) models which might predict what will happen 90% of the time will be wrong 10% of the time, substantially wrong 1% of the time, and catastrophically wrong 0.1% of the time. (The percentages illustrated here are hypothetical, but the effect isn't.)
Black swan theory, developed by Nassim Nicholas Taleb, suggests that the likelihood of such rare but consequential events are generally vastly underestimated even by so-called experts in a field. Taleb became famous because he was accurate in his prediction of the 2007-2008 financial crisis. He took action based on his theory which netted massive profits when a much largner number of investors incurred substantial losses. That crisis lead to the Great Recession, a period of time when the general trend of GDP growth reversed in many countries simultaniously.
Taleb attributes some of his theory to the work famous mathematician Benoit Mandelbrot who's groundbreaking study on randomness in financial markets focused on the focused on the long history of cotton futures markets. Mandelbrot found that normal (Gaussian) statistics are inadequate to describe the behavior of financial markets.