Most of the unemployment in India is structural in nature. Examine the methodology adopted to compute unemployment in the country and suggest improvements.


05:23 AM

The question “Most of the unemployment in India is structural in nature. Examine the methodology adopted to compute unemployment in the country and suggest improvements." was asked in the Mains 2023 GS Paper 3.  Let us look at the model answer to this question.

Answer: Structural unemployment is a category of unemployment caused by differences between the skills possessed by the unemployed population and the jobs available in the market. Structural unemployment is a long-lasting condition that is caused by fundamental changes in the economy. According to ILO, 53% of businesses in India are not able to recruit due to the skill Gap. This implies that most of the unemployment in India is structural in Nature.

Reason for structural unemployment

  • Disguised unemployment in agriculture: Most of the people involved in agriculture do not have adequate skill to take over jobs in another sector.
  • Poverty: Lack of access to education and vocational skill.
  • The fast emergence of new and disruptive technology: Evolution of AI, Block Chain, Big Data analytics, Quantum computing, etc. demand exceptionally different skill sets.
  • Concentration of Employment opportunities: More than 75% of the non-agricultural jobs are in urban areas which hold around 35% of the population only.
  • Health status of the demography: 14% of India’s population is undernourished, according to ‘The State of Food Security and Nutrition in the World, 2020’ report, this impacts cognitive ability and economic productivity.
  • 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.

Measurement of Unemployment

The extent of unemployment is measured by three different concepts used by the National Sample Survey Organization.

  • Current daily status: It is calculated in the number of days or person years. It indicates the number of people who did not find work for one or more days in a week. This is considered as the most comprehensive measure of unemployment.
  • Current weekly status: It is the number of people who did not find even an hour of work in a week.
  • Usual status or chronic unemployment: It is the number of people who remained unemployed for the major part of the year.

Method used: The methodology adopted to compute unemployment in India involves the implementation of two major surveys:

  • Periodic Labour Force Survey (PLFS): Conducted by the National Statistics Office (NSO), this survey provides annual and quarterly estimates of employment and unemployment characteristics. It measures short-term dynamics in labour force participation and employment status in urban areas, and key parameters like labour force participation rate(LFPR).
  • All-India Quarterly Establishment-based Employment Survey (AQEES): Conducted by the Labour Bureau, this survey offers quarterly updates on employment in both organized and unorganized sectors of selected industries. It comprises the Quarterly Employment Survey (QES) for establishments employing 10 or more workers and the Area Frame Establishment Survey (AFES) for those employing 9 or less workers.

Issues with present method:

  • Underreporting of Unemployment: Many individuals, especially in the informal sector, are not captured in these surveys.
  • Inadequate Focus on Rural Areas: The PLFS predominantly focuses on urban areas for short-term analysis.
  • Dynamic Nature of Employment: The nature of employment is evolving with the rise of gig economy and freelance work.
  • Narrow definition of unemployment, Underemployed not accounted.
  • The sample size of the survey is very small in comparison with the real population size.


  • Enhancing Survey Frequency: Conducting more frequent surveys, especially in dynamic sectors, would provide more timely and relevant data for policy-making.
  • Skill Development: Assessing the skills possessed by the unemployed and comparing them with the demands of the job market can help in addressing structural unemployment.
  • Engagement with Stakeholders: Collaborating with industry associations, educational institutions, and vocational training providers can facilitate a better understanding of the skill requirements in various sectors.
  • Use of Technology: Implementing advanced data analytics and technology-driven tools for data collection, processing, and analysis can enhance the accuracy and efficiency of surveys.
    • Example, Labor Market Information System (LMIS)
  • Promote Entrepreneurship in MSMEs

Thus, it is imperative that certain structural reforms will be needed which will have more focus on Manufacturing and skill development to cater this issue related with the structural employment as India will have highest demographic dividend in 2042.