Chapter 2: Elasticity of Demand – Concepts, Calculations, and Sectoral Applications

 

Chapter 2: Elasticity of Demand – Concepts, Calculations, and Sectoral Applications

2.1 Introduction to Elasticity

Elasticity is a key concept in economics used to measure the responsiveness of one variable to changes in another. In this chapter, we focus primarily on the price elasticity of demand (PED), income elasticity, cross elasticity, and time elasticity. These measurements help businesses, policymakers, and economists make informed decisions.

2.2 Types of Elasticity’s

2.2.1 Price Elasticity of Demand (PED)

Price Elasticity of Demand measures how much the quantity demanded of a good changes in response to a change in its price.

Point Elasticity of Demand (PED): Point elasticity measures the responsiveness of quantity demanded to a small change in price at a specific point on the demand curve. It is calculated using the formula:

Point PED = (dQ / dP) × (P / Q)

Where:

·         dQ/dP is the derivative or slope of the demand function,

·         P is the initial price,

·         Q is the initial quantity.

This formula is useful when a functional relationship is known, especially in mathematical modeling.

Arc Elasticity of Demand: Arc elasticity is used when calculating the elasticity between two distinct points on a demand curve. The formula is:

Arc PED = (ΔQ / ΔP) × [(P₁ + P₂) / (Q₁ + Q₂)]

Where:

·         ΔQ = Q₂ – Q₁ (change in quantity),

·         ΔP = P₂ – P₁ (change in price),

·         P₁ and P₂ are initial and final prices,

·         Q₁ and Q₂ are initial and final quantities.

Midpoint Elasticity (Average Arc Elasticity): Midpoint elasticity avoids the directional bias and gives a consistent value regardless of whether price is increasing or decreasing:

Midpoint PED = [(Q₂ – Q₁) / ((Q₁ + Q₂)/2)] ÷ [(P₂ – P₁) / ((P₁ + P₂)/2)]

Or:

Midpoint PED = (ΔQ / Average Q) ÷ (ΔP / Average P)

Where:

·         Average Q = (Q₁ + Q₂)/2,

·         Average P = (P₁ + P₂)/2

2.2.2 Income Elasticity of Demand

Income elasticity measures how demand changes as consumer income changes. It is expressed as:

Income Elasticity = (% Change in Quantity Demanded) / (% Change in Income)

·         A positive value (>1) indicates a luxury good,

·         A value between 0 and 1 indicates a necessity,

·         A negative value indicates an inferior good.

2.2.3 Cross Elasticity of Demand

Cross elasticity measures the responsiveness of demand for one good to a change in the price of another good.

Cross Elasticity = (% Change in Quantity Demanded of Good A) / (% Change in Price of Good B)

·         Positive value: substitutes (e.g., tea and coffee)

·         Negative value: complements (e.g., printer and ink)

2.2.4 Time Elasticity

Time elasticity reflects how demand or supply responds over time. Demand may be inelastic in the short term but elastic in the long run as consumers find alternatives or adjust habits.

 2.3 Sect oral Tables and Analysis

 

Sector	Elasticity Type	Typical Elasticity Value	Comments
Fuel (Petrol/Diesel)	Price	Inelastic (0.2–0.4)	Essential, few substitutes
Luxury Goods	Income	Highly Elastic (>1.5)	Demand rises sharply with income
FMCG (Soap, Shampoo)	Price	Relatively Inelastic (0.5)	Regular usage, habitual consumption
Food Staples	Price	Inelastic (0.1–0.3)	Basic necessity
Electronics	Price	Elastic (1.2–2.0)	Discretionary, often postponeable
Mechanical Tools	Price	Medium Elastic (0.8–1.2)	Industrial use but has alternatives

2.4 Case Study: Petrol Price Hike – Rural vs. Urban Responsiveness

Let’s consider a real-world example. When petrol prices increase by 15%, how do rural and urban consumers respond?

·         Urban Response: People shift to public transport, carpooling, or electric vehicles. Elasticity might be around –0.5.

·         Rural Response: Fewer alternatives; continued usage of tractors, motorbikes. Elasticity close to –0.2.

Thus, policy targeting fuel subsidies or EV adoption must consider geographic elasticity.

2.5 Sector Focus: Electronics and Mechanical Products

2.5.1 Electronics Sector

·         Example: A 10% fall in the price of smartphones increases demand by 20%.

·         PED = –2 → Highly elastic

·         Implication: Firms can use price discounts during festive seasons to boost volumes.

Midpoint calculation example:

·         P₁ = ₹20,000, P₂ = ₹18,000

·         Q₁ = 1,000 units, Q₂ = 1,200 units

ΔQ = 200, ΔP = –2,000 Avg Q = 1,100, Avg P = 19,000 Midpoint PED = (200/1100) ÷ (–2000/19000) ≈ –1.73

This high elasticity suggests aggressive pricing strategies may be fruitful.

2.5.2 Mechanical Tools Sector

·         Example: A 5% rise in the price of power drills reduces demand by 4%.

·         PED = –0.8 → Moderately elastic

Arc calculation:

·         P₁ = ₹5,000, P₂ = ₹5,250

·         Q₁ = 500 units, Q₂ = 480 units

ΔQ = –20, ΔP = 250 Arc PED = (–20/250) × (10,250 / 980) ≈ –0.83

Marketing managers may bundle products rather than reduce prices.

2.6 Experimental Application: Campus Retail Testing

Business students can run campus shops to experiment with elasticities:

·         Offer discounts on mechanical calculators

·         Increase prices on stationery and measure drop in sales

·         Use Excel sheets to graph demand curves and compute arc elasticity

2.7 Graphical Representation 

Here's the graph showing the relationship between Price and Quantity Demanded. As expected, the demand curve slopes downward — indicating that as price decreases, quantity demanded increases.

 

 

Here's the graph comparing Rural vs. Urban Demand Elasticity. It shows how both segments respond differently to price changes — with urban consumers typically exhibiting a more elastic response

Here's the graph comparing Price Elasticity of Demand for FMCG vs. Electronics. It shows that:

·         FMCG products have higher elasticity — a small price drop leads to a larger increase in demand.

·         Electronics show relatively inelastic behavior — demand rises more slowly with price drops.

  

2.8 Practical Exercises

1.      Calculate arc elasticity for luxury watch prices increasing from ₹25,000 to ₹28,000 and quantity dropping from 300 to 240.

2.      Find midpoint PED for a food processor priced from ₹7,500 to ₹6,800 with quantity sold rising from 150 to 180.

3.      Compare urban vs. rural elasticity for LPG cylinders.

4.      Create sectoral tables for construction tools.

5.      Estimate income elasticity for Bluetooth speakers.

6.      Plot graphs using Excel and interpret slope.

2.9 Conclusion

Elasticity helps in strategic decision-making across marketing, production, and public policy. Whether selling electronics or managing rural fuel distribution, understanding elasticity reveals hidden consumer behavior patterns. Midpoint and arc formulas help avoid misleading interpretations, and sector-specific elasticity can inform targeted interventions.

Further studies can integrate elasticity with behavioral economics, big data from online purchases, and experimental trials in simulated environments.