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

Model Answer: 

Structural Unemployment in India: Analysis and Measurement

Structural unemployment, resulting from a mismatch between job requirements and available skills, is a significant challenge in India. This answer examines the nature of unemployment in India, the methodology used to measure it, and suggests improvements.

Evidence of Structural Unemployment

• Skill mismatch: Many graduates lack industry-relevant skills, leading to unemployment despite job openings.
• Technological shifts: Automation and digitalization are displacing traditional jobs, particularly in manufacturing and low-skilled services.
• Economic transformation: The shift from agriculture to services has left many workers without transferable skills.

Current Methodology for Measuring Unemployment

The primary tool for measuring unemployment in India is the Periodic Labour Force Survey (PLFS) conducted by the National Statistical Office. Key aspects include:

1. Indicators:
– Labour Force Participation Rate (LFPR)
– Worker Population Ratio (WPR)
– Unemployment Rate (UR)

2. Measurement approaches:
– Usual Status (US): Employment status over the preceding 365 days
– Current Weekly Status (CWS): Employment status during the 7 days preceding the survey

3. Sample and frequency:
– Annual surveys for rural areas
– Quarterly surveys for urban areas

Limitations of Current Methodology

1. Informal sector: Difficulty in capturing accurate data from the vast informal economy.
2. Underemployment: Inadequate measurement of underemployment and disguised unemployment.
3. Timeliness: Annual rural surveys may not reflect rapid economic changes.
4. Gig economy: Challenges in categorizing and measuring new forms of employment.

Suggested Improvements

1. Enhanced survey design:
• Increase frequency of rural surveys to quarterly
• Expand sample size for more granular data

2. Improved metrics:
• Develop specific indicators for underemployment and disguised unemployment
• Create metrics to better capture gig economy and informal sector employment

3. Technology integration:
• Implement real-time data collection using mobile and web-based platforms
• Utilize big data analytics to complement traditional survey methods

4. Sectoral focus:
• Conduct targeted surveys for rapidly evolving sectors (e.g., IT, e-commerce)
• Collaborate with industry bodies for sector-specific employment trends

Conclusion:
Accurate measurement of unemployment is crucial for effective policymaking in India. Addressing current methodological limitations and implementing improvements will enable a more comprehensive understanding of labour market dynamics, facilitating targeted interventions to address structural unemployment.