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?

  • I believe this to be a little bit too controverse, maybe rephrasing it to focus on one kind of taxes? It's broad and controverse and I don't yet see how this could be answered only with facts. The most you get opinions and links to scientific papers which tend to cover both sides of the medal… Dec 5, 2012 at 0:47
  • I'll narrow it down then to a specific tax. Dec 5, 2012 at 0:48
  • Narrowing it to a specific tax would definitely help, narrowing it to the policy that implemented the tax cut would be even better.
    – Tim Post
    Dec 5, 2012 at 8:10
  • 1
    Define stimulating the economy.
    – gerrit
    Mar 13, 2013 at 13:10
  • 2
    I call BS on this statement. To tie any particular law or tax to any particular economy change I think is totally beyond the abilities of even the most puissant and informed economists... regardless of their opinions on the matter. Jun 3, 2013 at 18:20

2 Answers 2


This was discussed on Skeptics.SE previously:

Do tax cuts stimulate an economy?

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.

GDP Growth Map From Wikipedia: World map showing real GDP growth rates for 2009; countries in brown were in recession.

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.

  • While interesting a nominally true, how does this answer the question? You need a TL;DR like "nobody really knows, because it's complicated". Your "short answer" is more of an invective. Dec 17, 2018 at 15:42
  • @JaredSmith, thanks for the suggestion. At this point in time I can't justify additional investment in editing it, but I think you have sufficient reputation to at least suggest a specific edit it you want. Dec 18, 2018 at 20:34
  • Nice analogy, however: for weather (and quantum mechanics) we have a situation where we see patterns on a larger scale (climate, classical physics, statistical thermodynamics). An interesting question is whether such macroscopic patterns exist for economics as well. One important difference here may be though, that we take natural laws being the same everywhere whereas tax laws and politics differ a lot between countries and groups of countries. Thus, even if there are such patterns, we may not be able to separate them from highly correlated confounders such as other political decisions. May 28, 2019 at 13:58

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