Glossary term

Arc Elasticity

Arc elasticity measures the average responsiveness of one variable to another between two points, often using the midpoint method.

Updated

May 17, 2026

Read time

3 min read

What Is Arc Elasticity?

Arc elasticity measures the average responsiveness of one variable to another between two points. In economics, it is often used to measure how quantity demanded or supplied changes over a range of prices rather than at one exact point.

The most common version is midpoint price elasticity of demand. It uses average price and average quantity as the base, which keeps the result the same whether the price moves up or down between the two points.

Key Takeaways

  • Arc elasticity measures elasticity over a range between two points.
  • It is often calculated with the midpoint method.
  • The measure is useful when price and quantity changes are not tiny.
  • It differs from point elasticity, which measures responsiveness at a specific point.
  • Businesses use elasticity to think about pricing, demand, revenue, and market sensitivity.

How Arc Elasticity Works

Elasticity compares percentage changes. The challenge is that the percentage change can differ depending on whether the starting point or ending point is used as the base. Arc elasticity solves that by using the average of the two points as the base.

For example, if price rises and quantity demanded falls, arc elasticity estimates the average demand sensitivity across that price range. It does not say demand has the same elasticity at every point along the curve.

This is useful when the observed change is large enough that a simple starting-point percentage can distort the result. The midpoint method treats the two points symmetrically, so moving from price A to price B gives the same elasticity magnitude as moving from price B back to price A.

Arc Elasticity Formula

Arc Elasticity=Q2Q1(Q1+Q2)/2P2P1(P1+P2)/2Arc\ Elasticity = \frac{\frac{Q_2 - Q_1}{(Q_1 + Q_2)/2}}{\frac{P_2 - P_1}{(P_1 + P_2)/2}}

Q1 and Q2 are the quantities at the two points. P1 and P2 are the prices at the two points. The numerator measures the percentage change in quantity using the average quantity. The denominator measures the percentage change in price using the average price.

Arc Versus Point Elasticity

Measure

What it measures

Best use

Arc elasticity

Average responsiveness between two points

Larger observed price or quantity changes

Point elasticity

Responsiveness at a specific point

Small changes around a known demand curve point

Midpoint method

Common way to calculate arc elasticity

Avoiding direction-dependent percentage changes

Pricing and Policy Uses

Arc elasticity helps businesses and analysts evaluate pricing decisions. If demand is elastic over a range, a price increase may reduce quantity enough to hurt revenue. If demand is inelastic, the same price increase may raise revenue, at least over that range.

Policy analysts also use elasticity to understand tax effects, subsidy effects, demand for energy, healthcare use, and consumer behavior. The measure turns a price or policy change into an estimate of response.

Elasticity can also help explain why some companies have more pricing power than others. A business selling a product with less elastic demand may be better able to pass through higher input costs, while a business facing elastic demand may lose customers quickly after price increases.

What the Estimate Can Miss

Arc elasticity is an average across two points. It can hide differences inside the range. Demand might be less elastic at lower prices and more elastic at higher prices, or the reverse.

The result also depends on clean data and a reasonable assumption that the observed change is mainly tied to the variable being measured. In real markets, income, competitors, supply shocks, and consumer preferences can move at the same time.

The Bottom Line

Arc elasticity measures average responsiveness between two points, often using the midpoint method. It is useful for pricing and policy analysis, but it should be read as a range-based estimate rather than a precise statement about every point on a curve.

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