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India's PLFS to capture gig workers, unpaid labour from 2027

India's labour statistics agency plans to broaden the Periodic Labour Force Survey from 2027, introducing dedicated measurement of gig workers and unpaid household labour. The expansion reflects the need for more comprehensive employment data in an evolving economy.

LSN India · 23 October 2026

India's PLFS to capture gig workers, unpaid labour from 2027

India's principal labour statistics instrument will undergo a substantial overhaul to capture growing segments of the workforce that have largely remained outside formal measurement frameworks. The Periodic Labour Force Survey, conducted by the National Statistical Office under the Ministry of Statistics and Programme Implementation, will introduce a separate sampling stratum dedicated to digital platform workers beginning in 2027.

The expanded survey will incorporate new questioning modules designed to quantify unpaid household work, caregiving responsibilities, and labour underutilisation across the country. These additions reflect growing recognition that conventional employment metrics fail to capture the full scope of economic activity in India's labour market, particularly as digital platforms reshape work arrangements and informal sector dynamics.

The NSO's revamped approach addresses longstanding gaps in labour data collection. Platform-based workers—including those engaged through ride-sharing, delivery, and freelance digital services—represent a significant and rapidly expanding segment of India's workforce. Current survey methodologies, designed around traditional employment relationships, have struggled to accurately enumerate and characterise this population.

The inclusion of unpaid work categories seeks to document labour contributions that remain statistically invisible despite their economic and social significance. Women's engagement in unpaid domestic labour and caregiving work represents substantial economic value currently absent from official statistics. The survey enhancements will provide policymakers with more granular data for informed labour market interventions and social protection policy design.