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Unemployment Rate
बेरोजगारी की दर
- Youth Unemployment Rate: Shows how many 15–29 year-olds can’t find work. If engineering or B.Com graduates end up in unrelated, low-pay jobs, it means skills don’t match market needs. Sharp youth joblessness usually signals gaps in skilling and industry growth. Example: A state adds IT parks but companies can’t find job-ready coders → high youth unemployment persists.
- Overall Unemployment Rate: Share of the total workforce actively looking for work but not getting it. When this stays high for years, it points to deeper issues like slow investment or weak MSMEs. Example: Large factories shut down and new ones don’t open → overall joblessness rises.
- Labour Force Participation Rate (LFPR): Tells how many working-age people are working or seeking work. Low LFPR for women often reflects safety, childcare, or cultural barriers, not just a lack of jobs. Example: No safe transport → many women stay out of the workforce despite wanting to work.
- Skilled Employment Growth: Tracks formal jobs in sectors like IT, auto, pharma, hospitality. It shows whether education + training are leading to real, better-paying work. Example: A new auto cluster hires hundreds of diploma holders → skilled jobs rise.
- Government Job Creation: Measures how many sanctioned posts (teachers, nurses, police) get filled. Regular, transparent recruitment boosts services and incomes. Example: Filling 20,000 teacher vacancies improves schools and local employment together.
- MGNREGA Usage (rural distress proxy): Higher demand means weak local job markets; sudden spikes indicate shocks (drought, pandemic). It’s support—but chronic high demand signals lack of alternatives. Example: A drought year → villagers take up MGNREGA when farms can’t employ.
- Job-Scheme Impact (placements): Training counts only if it leads to jobs. We check enrollments, completions, and actual placements. Example: 5,000 trained, 4,000 placed → strong scheme; 5,000 trained, 300 placed → weak impact.
