-
CENTRES
Progammes & Centres
Location
PLFS 2025 offers structural upgrades, but still overlooks migrant workers, informal livelihoods, and gendered realities shaping India’s labour force.
Image Source: Ritesh Shukla/Stringer Getty Images
The household-based Periodic Labour Force Survey (PLFS) is a vital tool informing India’s economic policies. As a primary data source on employment and the labour market, it enables evidence-based policymaking for job creation, skill development, and social protection strategies in a rapidly transforming economy. It captures key indicators—such as Unemployment Rate (UR), Labour Force Participation Ratio (LFPR), and Worker Population Ratio (WPR) estimates—through two frameworks:
The 2025 PLFS revision aligns with the Union Budget’s (2025-2026) objective to promote India’s ‘employment-led development.’
PLFS was launched in 2017, replacing the quinquennial Employment-Unemployment Survey (EUS). Until 2024, its quarterly bulletins primarily covered urban areas. Subsequent changes introduced in 2025 provide high-frequency labour data with monthly estimates, rural inclusion in quarterly surveys, and estimates of both CWS and ps+ss in the annual reports, aiming to align with the International Labour Organisation (ILO) recommendations. It has enhanced sample size, more detailed location codes, occupational mapping, enterprise classifications, and granular district-level data. The updated survey’s methodological augmentations include increased digitalisation of data tools and quicker enumeration cycles.
Some notable structural changes in PLFS 2025 include:
Until 2024, PLFS was widely critiqued for its static sampling frame. After revising the survey’s chassis, its CWS methodology uses a 7-day reference period to capture multiple activities within informal and temporary jobs. However, it considers only two categories of work—one as the principal and the other as subsidiary activities. This flattened complexity does not recognise the ‘hybrid’ livelihoods of India’s urban informal economy.
After revising the survey’s chassis, its CWS methodology uses a 7-day reference period to capture multiple activities within informal and temporary jobs.
PLFS continues to employ a house-based sampling design, excluding migrants who are typically mobile, in transit, or temporarily housed near construction sites or in informal settlements. The PLFS 2025 sample design employed a rotational panel scheme, where each of the 12 selected households was surveyed four times over four consecutive months. The First Stage Units (FSUs) sample size now stands at 22,692, with 10,188 in urban areas for each year of the two-year panel—implying an overall sample size of approximately 272,304 households, up from 102,400 as of December 2024.
It designates the district as the primary geographical unit (basic stratum) and identifies million-plus cities within the district region as the stratum. The FSUs are selected by the Simple Random Sampling Without Replacement (SRSWOR[i]). It notionally divides large 2011 census villages and the Urban Frame Survey (UFS) blocks into smaller sub-units based on the number of households in each UFS block.
Despite these changes, PLFS falls short of accurately capturing the diversity and complexity of India’s workforce, with notable gaps in hybrid, mobile, and precarious labour. Can high-frequency, district-level indicators alone reflect the nature of work or access to social protection schemes? Do household-based surveys accurately locate short-term, seasonal and circular migration patterns unless they are ‘home-based’?
The PLFS still relies on binary classifications of ‘eligible’ and ‘not eligible’ instead of probing deeper into why workers lack proper working hours, Occupational Safety and Health (OSH) provisions, emergency support, and other forms of social protection. These gaps and the continuing definitional flaws overlook traditional shortcomings, such as the rampant undercounting of women in the workforce and the complexities faced by migrant workers. They also tend to absorb platform work into vague categories.
The ILO defines informality as employment without legal or social protections, including formal contracts, maternity leave, pensions or regulated working conditions and calls for gender-disaggregated data and better visibility for informal workers.
Furthermore, even though budgets acknowledge gig and platform work, PLFS does not. The ILO defines informality as employment without legal or social protections, including formal contracts, maternity leave, pensions or regulated working conditions and calls for gender-disaggregated data and better visibility for informal workers. Conversely, PLFS does not offer a specific definition of informal workers. It focuses on enterprise registration, contract status, provident fund/employees’ state insurance (PF/ESI) coverage, and the nature of employment—casual, regular salaried, or self-employed—missing the vital link between migration and informality. Such conflation of informality with enterprise results in ‘invisibilising’ vast segments of the workforce. Categories such as ‘own account workers’ or ‘helpers’ sanitise exploitative conditions masked as familial obligation or informal contracts.
International bodies offer alternatives. For example, ILOSTAT defines informal work based on legal status, duration-based classification, work-migration linkages, employment relationship, and enterprise type. WEIGO (Women in Informal Employment: Globalizing and Organizing) statistical briefs highlight how national surveys often misclassify women’s home-based and care work. The World Bank’s Jobs Diagnostics and IOM-UNESCO reports explore internal migration, platform work, and the gendered dynamics of informality.
In India, the Economic Advisory Council to the Prime Minister's 2024 report provides a detailed study on domestic migration. The Economic Survey sections on labour market shifts, rural-urban migration, and COVID-19-induced reverse migration. Ancillary, the Ministry of Labour and Employment’s Annual Report provide data on unorganised sector employment and social security scheme coverage. The OSH Code also offer significant insights. The ‘Report of the Working Group on Migration’ by the erstwhile Ministry of Housing and Urban Poverty Alleviation also tracks and provides migration trends. Yet, PLFS treats migrants merely as a residual or demographic category, reflecting misplaced governance priorities.
The World Bank’s Jobs Diagnostics and IOM-UNESCO reports explore internal migration, platform work, and the gendered dynamics of informality.
The Migration in India 2020–21 report briefly addressed these gaps. However, the report was not based on the regular PLFS survey design but relied on a special schedule added during the pandemic—from the July 2020 to the June 2021 round—which captured details on short-term migration, temporary reverse migration, changes in employment location, and remittance. PLFS 2022–23 and 2023–24 did not retain this temporary addition, failing to integrate mobility into its employment logic.
While PLFS does not exclude informal workers, it does so within a framework of controlled precarity. The state determines eligibility for labour protections, and household labour for ‘own consumption’ is recorded under a single code, reducing complex contributions to simplified categories. Moreover, the January-December 2025 Employment and Unemployment (First Visit) form reinforces family hierarchies by placing the head of household’s name upfront, reinforcing societal biases about who among the family is considered a worker and on whose terms.
The PLFS’s terminology—self-employment, unpaid family workers, helpers—sanitises exploitative conditions and familial obligations. Gendered reasons such as ‘marriage’ or ‘family relocation’ obscure women’s migration for gig work, caregiving or home-based enterprises. While instability, lack of negotiation and bargaining power, and exploitation characterise informality, PLFS records workers, including sanitation staff, as formally employed, overlooking their highly precarious status.
PLFS also fails to disaggregate data on job contracts or social security by gender, caste or migration status, normalising the absence of labour rights.
Crucially, PLFS also falls short in addressing workplace safety, overtime or harassment. It records work hours but not unpaid labour or coercive conditions. Women’s unpaid domestic labour is classified as ‘attended’ domestic duties or ‘engaged’ in an activity, rendering their economic contributions invisible. The ‘others’ category—used for begging and prostitution—illustrates how social stigma influences statistical categorisation. As noted by WEIGO and ILO, these exclusions undermine the data’s relevance to gendered labour realities.
PLFS also fails to disaggregate data on job contracts or social security by gender, caste or migration status, normalising the absence of labour rights. It continues to classify workers by their eligibility for benefits, such as social security and maternity/healthcare benefits, without linking them to labour law violations, minimum wages, and paid leave. The increased employment figures disregard the absence of employment rights and fail to consider how social protection entitlements lapse across social borders.
Moreover, it conflates the statutory and voluntary benefits—Employees’ Provident Fund or (EPFO) and Public Provident Fund (PPF)—without clarifying whether they are employer-provided, state-mandated or self-initiated. For migrant workers, who move between states and employers, portability, continuity and enforcement mechanisms are largely absent. Its binary ‘eligible or not’ framing conceals the structural and bureaucratic barriers they face. Concurrently, the lack of institutional mapping to vendor associations, unions, or Self-Help Groups (SHGs) obscures their avenues for protection and negotiation.
For migrant workers, who move between states and employers, portability, continuity and enforcement mechanisms are largely absent.
For India’s informal workforce, welfare eligibility often exists only on paper. The 1996 Building and Other Construction Workers Act (BOCW Act) and the 1948 Employees’ State Insurance Act (ESI Act) provisions technically cover them. Nonetheless, the overwhelming pile of unstructured implementation driven by poor registration, lack of awareness, and inadequate enforcement essentially translates to no benefits for the workers. Initiatives—including the E-Shram Portal, the provision of identity cards to informal workers, and the Ayushman Bharat Health Account (ABHA) health records for migrant workers—aim to provide recognition but often fail to address issues of portability and inclusion.
Given this current state of affairs, PLFS must move beyond binary classifications and heed the complex, fluid, and negotiated realities of India’s employment landscape. Until PLFS reflects the actual contours of India’s informal economy, labour statistics will remain misaligned with lived realities.
Dhaval Desai is a Senior Fellow and Vice President at Observer Research Foundation, Mumbai.
Durga Narayan is a Research Intern at the Observer Research Foundation.
[i] SRSWOR is a method sample building from a population where each unit in the population has an equal chance of being selected to ensure that the sample adequately represents the whole population. Once chosen the unit is not replaced back into the population. Thus, the same unit cannot be selected more than once.
The views expressed above belong to the author(s). ORF research and analyses now available on Telegram! Click here to access our curated content — blogs, longforms and interviews.
Dhaval is Senior Fellow and Vice President at Observer Research Foundation, Mumbai. His spectrum of work covers diverse topics ranging from urban renewal to international ...
Read More +
Durga Narayan is a Research Intern at the Observer Research Foundation. ...
Read More +
PREV
