Question

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

Answer 1

Structural unemployment in India refers to a mismatch between the skills that workers possess and the skills demanded by employers. This type of unemployment arises due to changes in the economy, technological advancements, and shifts in consumer demand, leading to certain skills becoming obsolete while new skills are in demand. Addressing structural unemployment requires both understanding the current state of unemployment and adopting appropriate methodologies to measure and mitigate it.

Current State of Unemployment in India

1. Skill Mismatch:

   • Rapid technological changes, such as automation and digitalization, have created demand for new skills that many workers do not possess.
   • Traditional sectors like agriculture employ a significant portion of the workforce but contribute less to GDP, indicating underemployment and low productivity.

2. Educational Disparities:

   • The education system often does not align with industry needs, producing graduates without the necessary skills for available jobs.
   • Vocational training and skill development programs are insufficiently integrated into the education system.

3. Regional Disparities:

   • Uneven economic development across regions leads to migration and unemployment in urban areas while rural areas suffer from underemployment.

4. Informal Sector Dominance:

   • A large proportion of the workforce is employed in the informal sector, where jobs are often low-paying, temporary, and lack social security.

Methodology Adopted to Compute Unemployment in India

The primary sources of unemployment data in India are:

1. Periodic Labour Force Survey (PLFS):

   • Conducted by: National Statistical Office (NSO).
   • Frequency: Annual and quarterly reports.
   • Scope: Provides estimates of labor force participation rate, worker population ratio, unemployment rate, and distribution of workers by industry and occupation.
   • Methodology: Surveys households to collect information on employment status using usual status (activity status over the past year), current weekly status, and current daily status.

2. Census and National Sample Survey (NSS):

   • Conducted by: NSO every ten years for the Census and periodically for NSS.
   • Scope: Offers insights into demographic and employment characteristics.

3. Employment Exchanges:

   • Data Source: Registers unemployed individuals seeking jobs.
   • Limitations: Not all job seekers register, and data may not reflect the true unemployment rate.

Improvements and Suggestions

To better address and measure structural unemployment in India, the following improvements can be considered:

1. Enhancing Skill Development:

   • Curriculum Alignment: Align educational curricula with industry needs to ensure graduates possess relevant skills.
   • Vocational Training: Expand and improve vocational training programs to equip workers with new skills demanded by the job market.
   • Continuous Learning: Promote lifelong learning and upskilling initiatives to help workers adapt to changing job requirements.

2. Data Collection and Analysis:

   • Real-Time Data: Implement digital platforms for real-time data collection and analysis of employment trends.
   • Granular Data: Collect more granular data on regional and sectoral employment to identify specific areas with skill mismatches.

3. Promoting Formal Sector Employment:

   • Incentives: Provide incentives for businesses to formalize their workforce, improving job quality and security.
   • Social Security: Enhance social security measures for informal sector workers to ensure better protection and transition to formal employment.

4. Regional Development:

   • Infrastructure Investment: Invest in infrastructure and industries in underdeveloped regions to create job opportunities and reduce migration pressures on urban areas.
   • Local Industry Support: Encourage local industries and entrepreneurship through policy support and financial assistance.

5. Policy Interventions:

   • Targeted Programs: Develop targeted programs to assist workers in transitioning from declining industries to growing sectors.
   • Public-Private Partnerships: Foster collaboration between government, industry, and educational institutions to create a skilled workforce.

6. Technology Utilization:

   • AI and Big Data: Use AI and big data analytics to predict labor market trends and tailor training programs accordingly.
   • Online Platforms: Utilize online platforms for job matching, career counseling, and skill development resources.

Conclusion

Structural unemployment in India presents significant challenges, but with targeted strategies and improvements in data collection and analysis, the country can better address skill mismatches and enhance employment opportunities. By aligning education with industry needs, promoting formal sector employment, and investing in regional development, India can create a more dynamic and inclusive labor market that meets the demands of a rapidly changing economy.