| Introduction: Contextual Introduction Body: What are the challenges faced by the unorganized sector in India in the context of employment data collection? Conclusion: Way Forward |
The conflicting reports and statements about employment in India, as illustrated in the recent debate between Prime Minister Narendra Modi and various financial institutions, highlight significant challenges in employment data collection, especially in the context of the unorganized sector.
Challenges Faced by Unorganized Sector in the Context of Employment Data Collection
- Diverse Data Sources and Methodologies: Different organizations use varied methodologies and data sources to estimate employment. For example, the RBI’s KLEMS database uses official data from the Employment and Unemployment Surveys (EUS) and the Periodic Labour Force Survey (PLFS), while the CMIE adopts the International Labour Organization’s definition, leading to different estimates of employment and unemployment.
- High Informality in the Unorganized Sector: The unorganized sector, which employs a majority of India’s workforce, operates without formal records. This lack of documentation makes it challenging to capture accurate employment data.
- Impact of Economic Shocks: Economic shocks like demonetization, GST implementation, the NBFC crisis, and the COVID-19 pandemic have significantly impacted the unorganized sector. These shocks have led to the closures of many small units, the migration of workers, and changes in the size and composition of towns and villages.
- Discrepancies in Definitions of Employment: The PLFS and CMIE differ in their definitions of employment. PLFS includes those working without income, such as unpaid family labor, leading to higher labor force participation rates. In contrast, CMIE considers only those earning an income from work as employed, resulting in lower participation rates. This discrepancy creates confusion and varied interpretations of employment data.
- Geographical Dispersion: The unorganized sector is spread across urban and rural areas, often in remote and inaccessible regions. Conducting surveys and collecting data in such dispersed locations is logistically challenging and resource-intensive.
- Technological Barriers: Limited access to and use of technology in the unorganized sector can hinder data collection efforts that rely on digital tools and platforms. Many workers may not have the skills or resources to participate in online surveys.
Conclusion
The vast size and dynamism of the unorganized sector make it difficult to get a handle on the number of workers, their wages, working conditions, and skill sets. This lack of data makes it difficult for the government to formulate effective policies aimed at improving working conditions, social security coverage, and skilling initiatives for this crucial segment of the workforce.
