Unemployment in India: A Structural Conundrum
India, with its diverse and vast economy, faces structural unemployment challenges rooted in factors like technological changes, socio-economic transformations, and changes in business practices. Most of these challenges arise from the mismatch of skills with the requirements of a modernizing economy.
Methodology to Compute Unemployment in India:
- Periodic Labour Force Survey (PLFS): Conducted by the National Sample Survey Office (NSSO), PLFS replaced the erstwhile quinquennial employment-unemployment surveys. It provides quarterly data for urban areas and annual data for rural areas. Unemployment is computed based on the Usual Status (adjusted), Weekly Status, and Daily Status methods.
- Census Data: Held decennially, the Census provides data related to workforce participation and unemployment, although it is not as frequent or detailed as specialized surveys.
- Employment Exchanges: While not exhaustive, data from government employment exchanges provide insights into unemployment, especially urban unemployment.
Issues with the Current Methodology:
- Lack of Timely Data: The data is often published with considerable time lags, making it less relevant for immediate policy decisions.
- Under-representation: Informal sector employment, forming a significant portion of India’s workforce, is not effectively captured.
- Over-reliance on Self-reporting: Subjectivity in individual responses can sometimes skew the actual scenario.
- Real-time Data Collection: Leveraging technology can help gather real-time data, allowing for timely interventions.
- Skill Mapping: Regular surveys mapping skills and industries can provide insights into where skill development initiatives are required, addressing structural unemployment head-on.
- Collaboration with Private Job Portals: Private employment portals have vast datasets on employment, skill requirements, and job vacancies. Collaborative efforts can provide a more comprehensive view.
- Regional and Sectoral Analysis: Instead of a blanket nationwide approach, regional and sectoral analyses can provide more nuanced insights, guiding targeted policy decisions.
- International Best Practices: Studying and implementing best practices from countries with similar challenges can be insightful.
- According to the PLFS report for 2019-20, the unemployment rate stood at 5.8% in rural areas and 9.7% in urban areas.
- The pandemic exacerbated the unemployment scenario with CMIE data suggesting that the unemployment rate peaked at around 23% in April and May 2020.
In conclusion, while India’s structural unemployment poses significant challenges, a more robust, timely, and nuanced data collection methodology can drive better-informed policy decisions to address the issue effectively.