Broadband Pricing in a Small Town
Meghana is the pricing manager of a private cable broadband provider in a small town where no other wired broadband operator exists. Household demand for her basic plan is estimated as: at ₹500 per month, 10,000 subscribers; at ₹550, 8,500; at ₹600, 6,500. Her marginal cost of serving an additional subscriber is ₹200 per month, and fixed costs are substantial. Separately, about 400 small shops buy a business plan; their demand is much less responsive, and at the current ₹800 per month they rarely switch. The regulator has warned against 'unreasonable' pricing but has not banned differential tariffs. A consultant advises a uniform 10 per cent price increase for all customers, arguing that total revenue must rise because demand is a necessity. Meghana asks whether the consultant's revenue claim is correct, and whether a separate business tariff is defensible.
1. Calculate total revenue at each household price. Estimate arc elasticity between ₹500 and ₹550, and between ₹550 and ₹600, and assess the consultant's claim that revenue must rise.
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TR = P × Q.
- ₹500 × 10,000 = ₹50,00,000
- ₹550 × 8,500 = ₹46,75,000
- ₹600 × 6,500 = ₹39,00,000
Arc elasticity 500–550: ΔQ = −1,500; average Q = 9,250; ΔP = ₹50; average P = ₹525. e = (−1,500/9,250) ÷ (50/525) ≈ −0.1622/0.0952 ≈ −1.70. Arc elasticity 550–600: ΔQ = −2,000; average Q = 7,500; ΔP = ₹50; average P = ₹575. e = (−2,000/7,500) ÷ (50/575) ≈ −0.2667/0.0870 ≈ −3.07.
Demand is elastic in both ranges, and revenue falls with each price increase. The consultant's claim that revenue must rise because broadband is a necessity is wrong: necessity does not guarantee low elasticity when mobile data is a substitute. Also, revenue maximisation is not the same as profit maximisation; the relevant comparison is marginal revenue with marginal cost of ₹200.
2. Is the consultant's uniform 10 per cent increase from ₹500 to ₹550 advisable? Use the elasticity estimates and marginal cost to judge, and explain why revenue maximisation is not the same as profit maximisation.
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At ₹500, the estimated elasticity is about −1.70. MR ≈ P(1 + 1/e) = 500(1 − 1/1.70) ≈ ₹206, which is close to MC = ₹200. At ₹550, MR ≈ 550(1 − 1/3.07) ≈ ₹371, above MC; that means the firm would gain by expanding output (lowering price) toward the region where MR = MC. The uniform 10 per cent rise from ₹500 to ₹550 lowers revenue from ₹50,00,000 to ₹46,75,000 and moves price away from the profit-maximising neighbourhood. So the increase is not advisable on the given estimates. Caveat: the elasticity estimates are based on only three points and may shift with mobile broadband competition; costs may also differ by customer type. But the consultant's blanket 'necessity' argument is not supported. A better approach is to test a small price change and monitor churn, rather than impose a uniform rise.
3. Evaluate the proposal to charge shops ₹900 while households pay ₹500. What economic conditions must hold for such third-degree price discrimination to work, and what regulatory or arbitrage risks arise?
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Third-degree price discrimination requires: market power; separable markets (households vs shops) with no arbitrage or resale; different price elasticities; and ideally cost differences or a legally defensible rationale. Shops' demand is described as much less responsive, so a higher business tariff can raise revenue from that segment. But if shop demand is inelastic (|e| < 1) at ₹800, raising price increases revenue and reduces quantity, which also lowers variable cost; profit may rise. Risks: the regulator may treat a large household–business gap as 'unreasonable' if costs are similar; shops may resell or downgrade to household plans; business customers may switch to mobile or relocate; and a high price may invite entry. The tariff is defensible only if the bank can show a cost basis (business service, installation, support) or a genuine demand difference, and if contracts prevent leakage. A modest, published business premium with a clear service difference is safer than an aggressive one.