Gig Economy in India: Recognition Without Representation

Context:
India's labour market has been undergoing a significant transformation with the rise of gig and platform-based employment. While policy recognition and welfare measures have started acknowledging this new form of work, India’s primary labour data source, the Periodic Labour Force Survey (PLFS), has not yet evolved to capture the gig workforce adequately. This gap raises concerns about representation, welfare coverage, and effective policymaking.

Structural Shift in the Workforce

• India is witnessing a shift from traditional employment to gig and platform-based work.

• Sectors like food delivery, ride-hailing, digital freelancing, and home services have emerged as key areas of informal employment.

• According to a 2022 NITI Aayog report, India’s gig workforce is projected to reach 23.5 million by 2029–30.

• Recognising this shift, the 2025 Union Budget extended social protection to gig workers.

Legal Recognition through the Code on Social Security, 2020

• The Code on Social Security, 2020 defines gig workers as those engaged in income-earning activities outside formal employer-employee relationships.

• Platform workers are those using digital platforms to offer services for payment.

• Section 2(35) of the Code provides definitions but fails to differentiate gig workers from the self-employed or casual labourers.

• Clause 141 mandates the formation of a Social Security Fund for gig and unorganised workers.

• Under Section 6, the National Social Security Board is responsible for designing and implementing welfare schemes.

• The effectiveness of these legal provisions depends heavily on the availability of detailed and accurate labour statistics.

Limitations of the Periodic Labour Force Survey (PLFS)

• While the PLFS includes all income-generating activities, it does not specifically identify gig or platform workers.

• Gig workers are often categorised under broad terms such as self-employed, own-account workers, or casual labour, which obscures their unique employment conditions.

• Aspects like multiple platform employment, income fluctuations, platform dependency, and absence of formal contracts remain unreported.

• This statistical invisibility leads to the underestimation of gig work and limits access to targeted welfare.

Misclassification and its Consequences

• The PLFS design does not differentiate between traditional workers (like shopkeepers) and platform-based gig workers (like food delivery personnel).

• Both are listed under the same self-employed category despite differences in income sources, work risks, and job security.

• Gig work is characterised by no written contracts, absence of employer benefits, dependency on algorithms and ratings, and uncertain income.

• Such nuances are not captured, weakening the quality of data used in labour-related policymaking.

Recognition Without Statistical Representation

• Government initiatives like e-Shram registration, digital ID issuance, and Ayushman Bharat PM-JAY coverage have attempted to formalise gig workers' access to welfare.

• However, these efforts are not supported by corresponding updates in labour statistics, making it difficult to track impact or monitor exclusions.

• The 2025 revision of PLFS brought in larger sample size, monthly estimates, and broader rural coverage.

• Despite these improvements, it still does not include a dedicated category for gig or platform workers.

The Way Forward: Reforming Labour Statistics

• India’s labour statistics must reflect the changing nature of work to ensure inclusive and effective policy responses.

• Classification codes within PLFS should be revised to separately identify gig and platform workers.

• Special surveys or time-use modules should be introduced to record task-based work.

• Digital data from service platforms can be used to complement official statistics.

• Integration of beneficiary data from welfare schemes like e-Shram into national databases is essential for coverage and impact assessment.

Conclusion

India's gig and platform workforce is growing rapidly and demands structured recognition within the country’s labour data systems. Legal and policy frameworks are in place, but without accurate and detailed statistics, gig workers remain underrepresented. Bridging this data gap is essential for ensuring fair and inclusive access to social security and informed policymaking in the evolving employment landscape.