Subject: Economy

The persistent challenge of structural unemployment in India is reflected in the recent Economic Survey 2024-25 which highlights the complex interplay between skills mismatch and job creation, despite the unemployment rate decreasing to 3.2% in 2023-24 from 6% in 2017-18.

Current Methodology for Computing Unemployment

NSSO/PLFS Approach

• Usual Principal and Subsidiary Status (UPSS): Considers principal activity status over a reference period of one year, providing long-term unemployment trends.
• Current Weekly Status (CWS): Measures employment status based on activities during the preceding week, capturing short-term fluctuations.

CMIE Methodology

• Employs daily surveys to classify unemployment.
• Considers individuals unemployed if they haven't secured work on the survey day or previous day.

Limitations of Current Methodologies

Data Collection Challenges

• Informal Sector Coverage: Difficulty in capturing employment data from the unorganized sector which employs 82% of the workforce.
• Seasonal Employment: Current methods inadequately capture seasonal and temporary employment patterns.

Definitional Issues

• Employment Definition: Varying definitions of employment status across different surveys lead to data inconsistencies.
• Skills Mismatch: Current methodologies don't effectively capture the qualitative aspects of employment, with only 8.25% graduates finding jobs matching their qualifications.

Suggested Improvements

Methodological Enhancements

• Implementation of real-time data collection through digital platforms.
• Integration of satellite-based surveys for better rural employment tracking.
• Adoption of blockchain technology for maintaining comprehensive employment records.

Coverage Expansion

• Include gig economy workers and platform-based employment in surveys.
• Develop specific metrics for measuring underemployment and disguised unemployment.
• Integration of skill-mapping data with employment surveys.

India's journey towards precise unemployment measurement requires a comprehensive overhaul of existing methodologies. The implementation of technology-driven solutions and standardized definitions across surveys will enhance data accuracy and policy effectiveness, as demonstrated by successful models like Estonia's e-governance system for labor market monitoring.