Adam Smith in his seminal work, The Wealth of Nations, observed that “the real price of everything, what everything really costs to the man who wants to acquire it, is the toil and trouble of acquiring it”. This observation underscores the critical importance of employment generation, especially in a country like India, where millions strive to earn a living through hard work.
Recent data paints a mixed picture of progress. According to the Periodic Labour Force Surveys (PLFS), if employment is defined as any engagement in gainful productive activity, the growth in employment since 2017-18 has been notable. The total number of workers in the Indian economy increased from 458 million in 2017-18 to 563 million in 2022-23, reflecting significant growth. Additionally, the National Statistical Office (NSO) released estimates from quarterly surveys for urban areas for January-March 2024, confirming these trends. The workforce participation rate for urban males aged above 15 years increased from 67.7% in January-March 2022 to 69.8% in January-March 2024. For urban females, the participation rate rose from 18.3% to 23.4% over the same period.
Based on PLFS data, the unemployment rate decreased from 4.2% in 2021 to 3.6% in 2022, and further to 3.1% in 2023. The PLFS is considered one of the most reliable sources for employment data in India. However, improvements in the robustness of this data collection are necessary.
The main intention behind introducing the PLFS in 2017 was to provide more frequent and timely data on India’s labour market, addressing the inadequacies of previous quinquennial surveys. Unlike enterprise-based surveys, the PLFS focuses on household-based data collection, capturing the nuances of individual and informal sector employment. This approach offers a comprehensive and up-to-date understanding of labour force participation, employment status, and the nature of work, thereby enhancing the ability of policymakers to make informed decisions and address the dynamic changes in India’s labour market.
However, there is a need to (1) reduce the time lag of PLFS, (2) increase the frequency of the survey and (3) improve the methodology. Several empirical studies have critiqued the methodology of PLFS. In a study published in the Economic & Political Weekly, Jatav and Jajoria (2020) delved into the methodological shifts introduced with the PLFS and its implications for socio-economic inequality estimates in India. They highlight the fundamental flaws in the PLFS’s sampling methodology, notably the replacement of the detailed economic status-based stratification used in the quinquennial Employment and Unemployment Surveys (EUS) with an overly simplistic criterion based on the educational attainment of household members. This methodological shift is argued to be irrational and technically incorrect, as it fails to capture the multifaceted nature of socio-economic status, leading to biased and unreliable data outcomes. The PLFS’s use of education as a proxy for economic status overlooks critical factors such as household income and asset ownership, which were integral to the EUS’s stratification process.
The authors provide a technical critique of the inconsistencies arising from the PLFS’s sampling design, particularly the unrealistic shifts observed in socio-economic strata and the distortions in key labour market indicators. The study points out that the PLFS data indicates a significant increase in unemployment and NEET (Not in Employment, Education, or Training) rates, especially among the youth aged 18-29, which can be attributed to the flawed sampling method. Furthermore, the PLFS’s modified sample selection method results in a non-linear and inconsistent distribution of households by income classes, contrasting the expected linear relationship seen in EUS data. This inconsistency is exacerbated by the exclusion of detailed queries on household assets, land ownership, and economic activities in the PLFS, which limits its ability to accurately capture socio-economic disparities. The paper concludes that the PLFS’s methodological flaws undermine its reliability, necessitating a thorough review and rectification of its sampling techniques to ensure more accurate and inclusive socio-economic data.
Manna and Mukhopadhyay (2023) extend this critique by exploring alternative stratification variables for the PLFS to enhance the accuracy and reliability of its data. They argue that the current stratification variable, the number of household members with secondary or higher education, does not adequately reflect socio-economic status. Instead, they propose using variables such as the number of household members aged 15 years and above or the number of members aged 15-59 years, which show higher correlation coefficients with key PLFS variables like the number of persons in the labour force and the number of employed. The methodology adopted in their analysis involves deriving sample allocations based on proportional and optimum allocation methods and comparing them with the current PLFS allocations.
Their findings suggest that the existing allocations in rural areas, which disproportionately assign more households to the stratum with one educated member, should be adjusted. Specifically, they recommend reducing the allocation for this stratum from four to two households per village and increasing the allocation for the stratum with no educated members from two to four households. Additionally, their analysis reveals that stratifying by the number of household members aged 15 and above, or 15-59 years, would provide a more accurate representation of the socio-economic status and improve the reliability of the survey data. This approach would align the stratification process more closely with the actual distribution of socio-economic characteristics in the population, addressing the biases introduced by the current educational criterion.
Apart from the larger methodological issues, when one is talking about employment, it is prudent to explore the inter-state variations in unemployment numbers. The unemployment rate for 15 years and above is highest in Jammu & Kashmir (11%) and Kerala (10.7%) in the Q4 of 2023-24. These states are closely followed by Rajasthan (9.6%), Himachal Pradesh (9.1%) and Telangana (8.8%).
However, the more serious issue lies in the staggering unemployment rates among the youth aged 15-29. Leading this list, Kerala’s youth unemployment stands at 31.8%, followed by Telangana (26.1%), Rajasthan (24%), Odisha (23.3%), Uttarakhand (22%), and Bihar (21.5%).
This persistent and high youth unemployment can be attributed to factors such as a fraction of youth enrolled in higher education programmes, preparation for government exams, skill gaps, or salary expectation mismatches. These factors, while significant, only scratch the surface of a deeper, systemic problem affecting the quality and type of jobs available.
Further, higher levels of education in some of these states are pushing up unemployment rates. The reluctance of educated youths to engage in manual or trade sector jobs, which are often filled by migrant workers, highlights a critical mismatch between job availability and the aspirations of the local workforce. Additionally, the increase in women pursuing higher education, while positive in many respects, has contributed to the unemployment figures as they seek quality employment that meets their qualifications.
There is also an issue of the private sector not creating enough jobs. Closely linked to this is the problem of skill mismatch. Educational institutions often fail to equip graduates with the practical skills and industry-specific knowledge required by employers, resulting in a considerable gap between the skills of job seekers and the needs of the job market. Rapid technological advancements exacerbate this issue, as the workforce struggles to keep pace with changes in industries like IT and automation. Consequently, even when jobs are created, a significant portion of the workforce remains unemployable due to a lack of relevant skills, hindering overall economic progress.
The recent remarks by Chief Economic Advisor V. Anantha Nageswaran on employment have been widely discussed and, in some cases, misunderstood. Speaking at the launch of the “India Employment Report 2024”, Nageswaran emphasised that it is not feasible for the government to single-handedly address all social and economic challenges, including unemployment. He clarified that the primary responsibility for job creation lies with the private sector, not the government. However, the government has to create a conducive environment to create employment. The government in the last 10 years has worked towards creating this environment. One should acknowledge that more needs to be done. But at the same time, the private sector needs to do its bit too.
(Bibek Debroy is an Economist and Aditya Sinha is a public policy professional.)
Disclaimer: These are the personal opinions of the author
