Living in denial about unemployment
Relevance: GS Paper I & II
Why in News?
Public confusion over the extent of unemployment is a result of the differences in the various databases used.
More About the News:
- Recently, citing a Reserve Bank of India (RBI) report indicating the creation of 8 crore jobs over the past 3-4 years, the Prime Minister accused the Opposition of spreading misinformation about unemployment. He also highlighted upcoming infrastructure projects expected to generate further employment.
- This was not just a rebuttal to concerns about rising unemployment affecting the ruling party, but also a response to critiques from financial institutions like Citigroup, which in July underscored the inadequacy of job creation in India.
RBI and SBI Reports:
- RBI's 'India KLEMS Database': Released on July 7, it details economic metrics across 27 industries, using data from official sources like the Periodic Labour Force Survey (PLFS) and the Annual Survey of Unincorporated Sector Enterprises (ASUSE). It does not independently estimate employment but relies on existing data.
- SBI Report: Disputed findings from other financial institutions, claiming 8.9 crore jobs were created in manufacturing and services between FY14 and FY23, with 6.6 crore during FY04-FY14, excluding agriculture. It highlighted discrepancies with private employment surveys and noted a total labor force of 59.7 crore.
- CMIE's Contradictory Data: In July, the Centre for Monitoring Indian Economy (CMIE) reported a rise in the unemployment rate to 9.2% in June 2024 from 7% the previous month, contradicting official claims of substantial job creation.
- Ground Reality: Despite these reports, ground-level observations indicate persistent unemployment. Large numbers of applicants for limited job openings in sectors like law enforcement and railways highlight the challenges faced by educated youth. This situation questions the narrative of a 'demographic dividend' and suggests a more complex reality for many individuals.
Public confusion regarding unemployment stems from discrepancies in various databases used for estimating employment figures.
Let's delve into these databases:
- KLEMS Database: The KLEMS data, recently referenced, serves as a tool to measure productivity growth in the Indian economy. It relies on official data sources such as the Periodic Labour Force Survey (PLFS) and the Annual Survey of Unincorporated Sector Enterprises (ASUSE) conducted by the National Sample Survey Office (NSSO). Despite using these official sources, the KLEMS data does not independently estimate employment but rather incorporates existing figures. Therefore, presenting KLEMS data as a standalone source of employment information can be misleading, as it draws from other government surveys.
- Unorganised Sector Data: The variance in employment estimates across different sources is primarily due to the intricate structure of the Indian economy and the challenges in gathering reliable data. India encompasses both organized and unorganized sectors, with the latter employing 94% of the workforce. Data collection for the unorganized sector, which includes approximately 11 crore farms and 6.5 crore MSME units, is particularly challenging, given its size and periodic data availability. Surveys like the Census and ASUSE, crucial for estimating employment in this sector, have faced gaps due to outdated information; for instance, the last Census was conducted in 2011.
- Impact of Economic Shocks: The period from 2016 to 2024 witnessed significant economic shocks, demonetization, GST implementation, the NBFC crisis, and the COVID-19 pandemic impacting the structure of the economy, especially the unorganized sector. These shocks led to closures of businesses, migration patterns, and changes in urban and rural demographics, rendering older data less reliable for current sampling purposes. The ASUSE surveys, although attempting to account for these changes, may overestimate the number of establishments and their employment due to shifts in rural-urban ratios and the composition of small versus large enterprises.
- PLFS vs. CMIE: The differences between the PLFS and CMIE data sources are significant and stem from varying definitions of employment. PLFS, a widely cited official data source, includes individuals as employed even if they do not receive income from their work, such as those providing unpaid labor or engaged in unproductive activities. This broad definition results in a higher reported labor force participation rate of 50%-55% in recent years. In contrast, CMIE adheres to the International Labour Organization's definition, counting only those earning income from work as employed, leading to a lower reported participation rate of 40%-45%. This discrepancy translates into a substantial difference of approximately 90 million individuals between the two estimates.
- Questions on Survey Methodologies: The question arises whether nearly everyone is engaged in some form of activity, such as homemakers contributing work. Additionally, PLFS includes the underemployed and disguised unemployed, suggesting very low unemployment rates. In contrast, CMIE highlights the number of individuals who have stopped actively seeking work, a form of unemployment not recognized by official data.
Conclusion:
The conflicting reports on employment highlight the challenges in accurately measuring and understanding the state of employment in India. Reliance on different data sources and methodologies creates a fragmented picture, often used for political narratives. There is a pressing need for more reliable, frequent, and comprehensive data collection, especially in the unorganized sector, to inform better policy decisions and address the real issues of unemployment and underemployment and manage public dissatisfaction.
