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Laffer Curve

Reviewed by Sweta | Updated on Jan 05, 2021



Laffer curve was developed by the economist, Arthur Laffer. The theory analyses the relationship between tax rates and the tax revenue collected by the government. The theory relies on the argument that cutting tax rates increases the total tax revenue for a government.

Significance of Laffer Curve

  1. There is an optimum tax rate, which maximises total government tax revenue. A hike in the rate beyond the optimal rate would act as a disincentive for business activities and investment activities.

  2. In a case where the taxes are too high along the Laffer curve, then a cut in the tax rate will encourage economic activities and increase tax revenue. Higher tax rates decrease the incentive to invest, carry on business expansion and revenue-generating activities.

  3. The underlying assumptions and the economical idea is that people will adjust their economic behaviour in the light of tax incentives given by the government.

  4. The Laffer curve analyses the impact of tax rates from 0% to 100%. At a 0% tax rate, tax revenue would obviously be zero. As tax rates increase from low levels, tax revenue collected would increase.

Eventually, if the tax rates reach 100 per cent, at the far right on the Laffer curve, people would choose not to work. Therefore, it is necessary that at some point in the range where tax revenue is positive, the optimum point must be reached.

Industry Impact

  1. The argument of the Laffer curve—more the money taken out of business, lesser they are willing to invest in the business.

  2. In the case of tax rates, if the effect is large enough, then an increase beyond a point would decrease the total tax revenue. There is a threshold limit beyond which the incentive to produce more decreases.

  3. The Laffer Curve had been used earlier as a basis for giving tax cuts in the 1980s but was criticised on practical grounds in view of its simplistic assumptions, and on economic grounds stating that increasing government revenue might not always be optimal.

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