DGCA Fare Caps Expose Need for Data-Driven Aviation Regulation in India

Following fare surges during an operational crisis involving IndiGo in December 2025, the DGCA (Directorate General of Civil Aviation) and the Ministry of Civil Aviation imposed temporary price caps.

• This episode exposed regulatory gaps in aviation oversight despite India being the world’s third-largest aviation market.

Key Issues In India’s Aviation

• Data Deficit in Fare Regulation: The government cannot distinguish between genuine price increases driven by demand and predatory pricing (market abuse) because it lacks historical comparative fare data.
  • It tracks only passenger volumes (the number of travellers), not ticket prices or the fares paid.
• Crisis-Based Approach: Current regulation largely responds to price spikes rather than preventing distortions.
• Rising Market Concentration: Increasing duopoly risk raises concerns of anti-competitive pricing.

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Learning from the U.S. Model

• Institutional Mechanism: The Bureau of Transportation Statistics (BTS) maintains structured airline data.
• DB1B (Airline Origin and Destination Survey) Database: The regulators collect a 10% random sample of all tickets sold every quarter, analysing the route, airline, and actual price paid, thereby maintaining a digital fare trail since 1995.
• Regulatory Value: This enables a long-term analysis of pricing patterns, competition, and consumer welfare.

Reasons 10% Sampling Framework is Suitable for India

• Creates a Digital Trail: Captures actual fares paid, routes, and carrier details.
• Strengthens Regulatory Oversight: Shifts DGCA’s role from traffic monitoring to market behaviour analysis.
• Encourages Self-Regulation: Transparency incentivises airlines to design responsible pricing algorithms.
• Balances Transparency and Confidentiality: Monitors pricing outcomes without exposing proprietary algorithmic code.

Key Benefits of Data Oversight

• Monitoring Monopolies: Data would reveal if airlines are charging unfair prices on monopoly routes where only one carrier operates.
• Analysing Industry Shocks: It would help the government understand the impact of an airline’s shutdown (such as Go First) and whether remaining airlines are unfairly exploiting the resulting power vacuum.
• Detecting Algorithmic Manipulation: Oversight could distinguish between natural “demand spikes” (such as during Diwali) and artificial price manipulation driven by revenue management algorithms.

Addressing Concerns of the Industry

• Privacy Concerns: The Airlines often resist sharing data, claiming it would reveal their secret revenue algorithms to competitors.
  • However, a 10% random sampling framework focuses only on final ticket prices and route details, not on the internal pricing algorithms, thereby safeguarding airlines’ proprietary revenue management systems.
• Reduced Risk of Collusion: Publishing sampled data with a quarterly time lag prevents real-time price coordination among competitors while still enabling meaningful regulatory oversight.
• Feasible Compliance: Since only a limited fraction of ticket data is required, the reporting obligation remains proportionate and manageable given the scale of airline operations.

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Conclusion

India must transition from ad hoc interventions to a structured, data-first regulatory framework to ensure fair competition and sustained consumer protection.

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