Most of the unemployment in India is structural in nature. Examine the methodology adopted to compute unemployment in the country and suggest improvements.

Why most unemployment is structural

• Agriculture still holds a large workforce while its share of output is much smaller; people are not idle every day, but they are not in productive non-farm jobs.
• Education and skills do not match factory, logistics, and care vacancies; graduates wait while machine operators are scarce.
• Manufacturing has not absorbed labour at East Asian speed; services hire the English-and-urban slice first.
• Gender, caste, and region lock many into local, unpaid, or casual work; a vacancy in another State is not a real option without housing and safety.
• Cyclical slumps add a layer. They do not explain why the same mismatch returns in a boom. Disguised unemployment in the family farm is the rural face of the same structure.

Methodology in India

• After the old National Sample Survey employment rounds, PLFS (National Statistical Office) is the regular household survey.
• Usual status (principal + subsidiary): a person is a worker if they worked for a major part of the last 365 days, or had a subsidiary economic activity of at least 30 days. The unemployment rate on this basis is the lowest, because a few months of work in the year count.
• Current Weekly Status (CWS): activity in the last 7 days. A person who worked at least one hour in that week is employed. This sits between usual status and daily status and is now the headline international-style rate in PLFS annual and quarterly urban releases.
• Current Daily Status (CDS): person-days in the week; unemployment is counted in half-days. This rate is the highest because underemployment (a worker idle three days) shows up.
• Labour force is those employed plus those seeking or available. Not in labour force (studies, unpaid domestic work) is not unemployment. That distinction matters for women.

Suggested improvements

• Publish underemployment and hours as prominently as the unemployment rate; CDS-type person-days should not stay a specialist footnote.
• Count gig, platform, and unpaid family work with clearer codes so informality is not hidden as self-employment.
• Raise frequency and sample for backward districts; urban quarterly PLFS is not enough for rural structure.
• Add a job-vacancy and skill-mismatch module (what employers cannot fill) beside household status.
• Align a time-use slice with PLFS so women’s unpaid work is not read as voluntary withdrawal.
• Use administrative traces (EPFO, e-SHRAM, GST payroll) as complements, not as a replacement for a household survey that still sees the informal majority.