Critical Examination of Employment Data in India: A Focus on the KLEMS Database (GS Paper 3, Economy)
Context and Overview:
- The article in the Indian Express scrutinizes the use of the KLEMS database for assessing job creation in India.
- This database, developed through an international collaboration and supported by institutions such as the Delhi School of Economics and ICRIER, has been increasingly used to substantiate claims about employment growth.
- The database, now housed at the Reserve Bank of India (RBI), compiles comprehensive economic data, including capital, labor, energy, materials, and services, from 1980 to 2024.
Methodology and Data Sources in KLEMS:
- Data Compilation: The KLEMS database utilizes data from multiple national surveys such as the Employment-Unemployment Surveys (EUS), Periodic Labour Force Surveys (PLFS), National Account Statistics, and the Annual Survey of Industries.
- Interpolation and Projections: Due to the absence of annual data from the National Statistical Office, the KLEMS database relies on interpolated data to fill in gaps. Worker-population ratios (WPR) derived from EUS and PLFS are applied to total population figures, which are either interpolated from Census data or projected by the National Population Commission.
- Population Projections: The methodology uses population projections from the Ministry of Health and Family Welfare (MoHFW). However, these projections apply uniform growth rates to both rural and urban populations, potentially leading to inaccuracies. Rural areas typically experience slower population growth compared to urban areas, which could skew the data.
Issues with Population Projections and Workforce Estimates:
- Inflated Figures: The uniform application of growth rates to rural and urban populations might result in inflated employment numbers, particularly in rural areas where growth is generally slower. This could overestimate the actual employment figures, especially in recent years.
- Quality of Employment: The KLEMS database's methodology includes workers engaged in subsidiary employment, many of whom are unpaid family workers. This inflates employment figures without reflecting the quality or stability of the jobs, raising concerns about the reliability of the data for assessing genuine employment growth.
Impact on Employment Data:
- Employment Trends: The KLEMS database indicates significant employment increases in agriculture, services, and manufacturing sectors from 2018-19 to 2022-23. This increase is partly attributed to the projected rise in population and employment, despite unchanged WPR.
- Data Discrepancies: The inclusion of subsidiary employment and reliance on projected population data can misrepresent the true employment scenario. This discrepancy between the database’s reported figures and actual employment quality and availability leads to skepticism about the reported job creation claims.
Comparison with Other Employment Data Sources:
- State Bank of India (SBI) Analysis: Economists at SBI compared KLEMS data with the Annual Survey of Unincorporated Sector Enterprises (ASUSE), which reported a significantly lower employment figure of 10.96 crore compared to the inflated 56.8 crore reported by KLEMS. The discrepancies between these figures highlight potential overestimations in KLEMS data.
- Reliability of Surveys: The comparison points to the limitations of enterprise-based surveys like ASUSE in accurately capturing employment compared to household surveys, which are generally considered more reliable. Additionally, data from MSME registrations or EPFO subscriptions may not accurately reflect new job creation.
Key Points to Consider:
- Methodological Accuracy: The assumptions and projections used in the KLEMS database need careful scrutiny to ensure that they do not lead to inflated employment figures.
- Quality vs. Quantity: It's crucial to differentiate between the number of jobs and the quality or stability of those jobs when assessing employment growth.
- Diverse Data Sources: Cross-referencing data from various sources can help mitigate the risk of relying on potentially flawed estimates.
This critical examination underscores the need for robust and transparent methodologies in employment data collection and analysis, which are essential for informed policymaking and economic planning.
Conclusion:
- The article argues that the KLEMS database, despite its comprehensive scope, may lead to misleading conclusions about employment growth due to methodological limitations and data inconsistencies.
- Overreliance on this data for policy-making and economic analysis may result in an overestimation of job creation, particularly in terms of the quality of employment.
- Policymakers and analysts should exercise caution and consider multiple data sources to get a more accurate picture of employment trends and economic health.
