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The first district-level data from the Periodic Labour Force Survey indicates that the share of youth not in jobs, education or training in nearly one in four districts across India is over 30%. Banasree Purkayastha looks at the hyper-local economic realities revealed by this data
l What does the report say about India’s youth?
THE ‘LABOUR MARKET Snapshot of Selected Districts’ report released by the National Statistical Office offers a peek into what India’s youth (ages 15–29) is doing by mapping NEET (not in employment, education, or training) metrics down to the individual district level. This age group accounts for around 27% of the country’s population. A recent Niti Aayog report had estimated India’s young NEET population in 2021 at 87 million.
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As much as 23.7% of districts recorded NEET rates above 30% in 2025, reflecting regions where a sizeable portion of the youth demographic is completely detached from both the active workforce and formal education/ skilling pipelines. However, 45.9% of districts report a 20% to 30% NEET range. Major technological and administrative hubs are much better at keeping youth productively occupied or enrolled in upskilling courses. Southern tech hubs lead with urban zones like Ernakulam in Kerala posting the lowest national NEET levels at 9.6%, with Coimbatore in Tamil Nadu following at 14.5%.
l What are the other key findings?
DISTRICTS DISPLAY MARKEDLY different combinations of labour-force participation rate (LFPR), worker population ratio (WPR), unemployment and youth disengagement. In the 15 years and above age group, among the 100 most populous districts, Surat in Gujarat at 68.6%, followed by Araria in Bihar (68.0%) and Salem in Tamil Nadu (67.8%), recorded the highest LFPR. Again, Surat at 67.8%, Araria (67.4%), and Banaskantha district in Gujarat (66.6%) registered the highest WPR. South Twenty-Four Parganas in West Bengal (0.9%), Araria (0.9%) and Ahmedabad (1.1%) exhibited the lowest unemployment rate. Women’s participation in the labour force also varies sharply across the country, though their participation crossed 40% in nearly 58% of districts.
l What is the methodology for the study?
THE STUDY REPRESENTS the first time official employment metrics have moved from broad state-level generalisations to targeted district-level analytics. Historically, the PLFS used NSS Regions (large clusters of districts) as its basic survey stratum, meaning the sample sizes were insufficient to draw accurate conclusions about individual districts. In January 2025, the district was designated as the primary basic stratum for the majority of India’s geography. To ensure district-level statistical accuracy, the sample size was significantly scaled up. The survey covered a footprint of 272,000 households distributed across 22,692 First Stage Units (FSUs) (which consist of villages in rural areas and Urban Frame Survey blocks in cities). The survey period of PLFS has been shifted from the July–June cycle (agricultural year) to the January–December cycle (calendar year) in conformity with international practices.
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l Are govt skilling programmes helping?
THE GOVERNMENT HAS been running several programmes to enhance the skills of the working age population. There are four flagship programmes under the Skill India Mission —Pradhan Mantri Kaushal Vikas Yojana (PMKVY), Jan Shikshan Sansthan (JSS), National Apprenticeship Promotion Scheme, and Craftsman Training Scheme in Industrial Training Institutes (ITIs). In February 2025, PMKVY 4.0, the apprenticeship programme and JSS were brought under a single central sector scheme for 2025-26. The Union Cabinet has also approved a five-year, Rs 60,000 crore scheme to upgrade 1,000 government ITIs through a hub-and-spoke model. However, there still remains a mismatch between skills and job availability. For instance, under PMKVY, 2.85 million youths had been trained and 1.96 million certified till September 23, 2026 as per its dashboard data, but the number of placements are only 200,932.
l How can the findings shape govt policies?
YOUTH EMPLOYMENT, SKILLING and employability are important areas of government policy and politics. District-level labour market statistics can help capture spatial variations across key parameters and provide more granular evidence for informed planning and policy formulation. For instance, a district with low unemployment and low labour force participation requires a different response from one with high participation but insufficient employment. Again, a high female participation rate does not reveal whether women have secure, adequately paid and productive work; district planning will still need information on occupation, earnings, employment status and hours worked. While the report does not attribute any causes to the differences between districts, it throws light on hyper-local economic realities.
TOPICSjob growthThis article was first uploaded on September twenty-four, twenty twenty-six, at nine minutes past five in the evening. © The Indian Express (P) Ltd