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Laffercurve

The Laffer Curve is an economic idea that shows the relationship between tax rates and the tax revenue a government collects. It suggests that revenue is zero at a 0% tax rate, rises as rates increase, reaches a peak and then falls if rates become too high.

It is named after the economist Arthur Laffer.

From the Money Master HQ dictionary, founded by Shihan Sheriff (FCMA, VP of Finance at Nomod, CFO at Esanjo Ventures). How these definitions are written.

What it means

The logic is straightforward. At a 0% rate the government collects nothing, and at a 100% rate nobody has a reason to earn taxable income, so it collects nothing then too.

Somewhere between the two, there must be a rate that raises the most money. The reason revenue can fall at high rates is that people and companies change their behaviour.

They may work fewer hours, move income abroad, find legal ways to reduce tax or stop investing. When the tax base (the amount of income or profit that can be taxed) shrinks enough, a higher rate on a smaller base can bring in less than a lower rate on a bigger one.

The curve is a concept rather than an exact map. Nobody knows precisely where the peak is, and it differs between countries, taxes and time periods.

Economists disagree about whether particular tax systems are on the rising or falling side of the curve. For business leaders, the idea shows up in debates about corporate tax rates, wealth taxes and incentives.

A company deciding where to locate may compare effective tax rates, and governments sometimes cut rates to attract investment, hoping the extra activity makes up for the lower rate. Whether that works in a given case depends on how responsive people and companies are to tax changes.

It is worth remembering that the Laffer Curve does not say that all tax cuts pay for themselves. It says only that, past a certain point, higher rates can be counterproductive.

Most of the practical disagreement is about where that point lies. Policy makers often use the curve as a starting point for a conversation, not as a forecast.

They combine it with estimates of how sensitive taxpayers are to changes, usually called elasticity. A sector with mobile workers or highly mobile profits is likely to respond more strongly than one where activity is tied to a place.

In practice

Real-world examples.

1

Example

A country's finance ministry considers raising the top income tax rate. Its analysts model how many high earners might reduce work or relocate, and estimate whether the extra rate would increase or reduce total revenue. The final figure will be part of the budget forecast.

2

Example

A city council debates a hotel tax. The finance director warns that if the tax becomes too high, visitors may choose neighbouring cities and total tax collected could fall. He recommends avoiding a rate high enough to push visitors away.

3

Example

A multinational compares corporate tax rates across three countries when deciding where to build a regional headquarters. It notes that one country with a lower rate attracts much more business activity. Its advisers note that high rates elsewhere may be pushing activity out of the other two countries.

Formula

Calculation

Tax revenue = tax rate x tax base Worked example (illustrative figures): a government taxes a sector with a base of $500 billion at 20%. It then tests higher rates, which cause the base to shrink as activity falls or moves elsewhere. Step 1: At 20% with a $500 billion base, revenue = 0.20 x 500 = $100 billion. Step 2: At 40% with the base falling to $300 billion, revenue = 0.40 x 300 = $120 billion. Step 3: At 60% with the base falling to $150 billion, revenue = 0.60 x 150 = $90 billion. Revenue rises from $100 billion to $120 billion, then falls to $90 billion, even though the rate keeps rising. The peak in this example lies somewhere near 40%, which is how the hump-shaped curve gets its form.

Case study

Seen in the real world.

The fictional country of Valdoria had a corporate tax rate of 45%, and its treasury noticed that collections were falling year after year. Several large companies had moved their headquarters to neighbouring countries with lower rates.

A new finance minister proposed cutting the rate to 30%. Her advisers estimated that the lower rate would lead to more business activity and a bigger tax base, although revenue might dip in the first year.

In this illustrative story, collections fell slightly in year one and then recovered above the earlier level as firms returned. The minister used the Laffer Curve to explain the change, but she also admitted that the result depended on many other factors and was not guaranteed. Critics argued that the recovery owed as much to a strong global economy as to the tax change.

Watch out

Common mistakes.

  • Believing that the curve proves tax cuts always raise revenue, when it only says that very high rates can reduce it.
  • Treating the peak as a fixed number, when it varies by country, tax type and period.
  • Ignoring that tax revenue also depends on the size of the economy, enforcement and the rules on deductions.

Questions

People also ask.

Who is the Laffer Curve named after?

It is named after the American economist Arthur Laffer, who popularised the idea in the 1970s.

Why would revenue fall at high rates?

Because people and companies may work less, avoid tax or move activity elsewhere, which shrinks the tax base.

Does the curve apply to company taxes?

Yes, it is used for income, corporate and other taxes, although the shape and peak differ for each.

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Last updated · October 8, 2026
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