QUES . Most of the unemployment in India is structural in nature. Examine the methodology adopted to compute unemployment in the country and suggest improvements. UPSC 2023 GS MAINS PAPER 3, 250 words, 15 marks

HINTS:

What is structural unemployment?

Structural unemployment is a longer-lasting form of unemployment caused by fundamental shifts in an economy and exacerbated by extraneous factors such as technology, competition, and government policy. Structural unemployment occurs because workers lack the requisite job skills or live too far from regions where jobs are available and cannot move closer. Jobs are available, but there is a serious mismatch between what companies need and what workers can offer.

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What are the causes of structural unemployment in India?

֍ One of the primary causes of structural unemployment in India are technological changes. As industries have moved from one process to another and harnessed technological capabilities, many jobs and roles have become obsolete. Companies have also sought ways to leverage technology as cost-cutting measures, putting their workforce at risk as the business searched more efficient ways to operate. Evolution of AI, Block Chain, Big Data analytics, Quantum computing, etc. demand exceptionally different skill sets.

֍ There is weak industry-academia interlinkages to introduce job oriented courses. This means that industries and academic institutions do not collaborate on what skill sets to impart to the students so that they get the required skill set.

֍ Structural unemployment has also been caused by poor training or lack of education programs. As workers got replaced by more efficient processes, workers must adapt by learning new business practices. Should they fail to do so, they may perpetuate structural unemployment by not having an appropriate skillset.

֍ Competition and globalization has also led to structural unemployment in India. Companies choose to forgo hiring less skilled domestic workers in favor of skilled workers from outside. Although wage rates in India are less but poor skillset in workers have forced the companies to hire workers from outside India.

֍ Widespread poverty has led to lack of access to education and vocational skill. Moreover poverty also leads to undernourishment and malnourishment which hamper cognitive abilities and economic productivity.

֍ Structural unemployment has also occured because workers live too far from regions where jobs are available and cannot move closer. There is concentration of employment opportunities in urban areas. More than 75% of the non-agricultural jobs are in urban areas which hold around 35% of the population only.

What is the methodology adopted to compute unemployment in India?

In India, the primary provider of unemployment statistics is the National Statistical Office (NSO). The NSO employs sample surveys to estimate employment and unemployment figures.

Individuals are categorized under the:

1 . Usual Principal and Subsidiary Status (UPSS) approach, which classifies them as employed, unemployed, or not in the labour force. This classification is based on their primary activity during the 365 days leading up to the survey.

An individual’s principal status, whether employed, unemployed or out of the labour force, is based on the activity in which they spent relatively long time in the previous year. A person who is not a worker, according to the principal status, would still be counted as employed according to the UPSS if they were engaged in some economic activity in a subsidiary role for a period not less than 30 days . Thus, an individual unemployed for five months and working for seven months in the previous year would be considered a worker according to the principal status, while an individual unemployed for nine months but working for three months would be counted as employed as per the UPSS.

2 . Current Weekly Status (CWS) approach is used to classify individuals based on their activities during the reference week before the survey. This provides a real-time snapshot of their current employment status.

The CWS adopts a shorter reference period of a week. An individual is counted as being employed if they have worked for at least one hour on at least one day during the seven days preceding the date of survey.

UPSS unemployment rates will always be lower than CWS rates because there is a greater probability that an individual would find work over a year as compared to a week.

How unemployment rate is calculated?

The unemployment rate is derived by dividing the number of unemployed individuals by the total labour force, which includes both the employed and the unemployed.

Unemployment data is further segmented by age, gender, education, and urban/rural locations. This segmentation aids in analysing unemployment trends among various population segments.

What are the limitations with the unemployment rate calculation in India?

֍ Measuring unemployment in India is difficult due to the informal nature of jobs. Unlike developed economies, individuals do not hold one job year-round. An individual may be unemployed this week, but may have worked as a casual labourer last month, and as a farmer for most of the year. Are they to be counted as unemployed? Thus there is underreporting of unemployment because many individuals, especially in the informal sector, are not captured in these surveys.

֍ There is a delayed release of employment data.

֍ There is inadequate focus on rural areas. The PLFS predominantly focuses on urban areas for short-term analysis.

֍ There is a narrow definition of unemployment, as underemployment is not accounted.

֍ The sample size of the survey is very small in comparison with the real population size.

What are the measures needed to make unemployment rate calculation in India more effective?

֍ Improvements are needed to make unemployment data more up-to-date. Periodic surveys may not capture rapidly changing labour market dynamics effectively. Establishing a more frequent reporting mechanism will enable policymakers to make timely decisions to address employment issues as they emerge.

֍ The current methodology often underestimates employment in the informal sector, which is significant in India. Enhancements should focus on better capturing informal employment trends.

֍ To address structural unemployment, future methodologies should gather data on skill mismatches to provide insights into areas requiring workforce development.

֍ Implementing advanced data analytics and technology-driven tools for data collection, processing, and analysis can enhance the accuracy and efficiency of surveys

֍ Further regional emphasis is necessary to pinpoint unemployment variations across states and districts for more targeted policy interventions.

֍ Incorporating underemployment metrics can offer a more comprehensive view of employment challenges by assessing the quality and hours of work.

֍ All collected data and subsequent reports should be made publicly available in an easy-to-understand format.

Thus, the current methodologies for computing unemployment in India offer a starting point but have room for improvement. The improvements will contribute to a more accurate, timely, and comprehensive understanding of unemployment in India, supporting informed policy measures and interventions.

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