Urban unemployment data mask gender gap, quality of work

unemployment rate is not a nuanced policy tool
Informed policymaking needs alternative unemployment measures that capture underemployment, job quality, and long-term unemployment.

The urban unemployment rate has dropped to a five-year low in the country, shows the latest Periodic Labour Force Survey data. On a quarter-on-quarter basis, the jobless rate in urban India fell slightly in October-December quarter of financial year 2023-24 to 6.5% from 6.6% in the previous period, signalling continued improvement in the labour markets.

The unemployment rate reached a peak of 12.6% in the April-June quarter of FY22, at the height of the coronavirus outbreak, but has since been declining steadily in urban areas. The urban jobless rate for individuals above 15 has recorded the lowest figure since the National Statistical Office (NSO) began tracking in 2018.

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Urban unemployment higher among women

Despite some success in reducing urban unemployment, the country has struggled to achieve parity in labour force participation between men and women. The latest data indicates that unemployment rates for men declined to 5.8% from 6% in the previous quarter, while for women, it remained stagnant at 8.6%. India continues to see low female participation in the workforce, with only 37% of women in formal employment in 2023.

The unemployment rate for the young population, those in the age group of 15-29, also fell to 16.5% in Q3 from 17.3% in Q2. This age group, typically representing first-time job seekers, is a critical indicator of labour market robustness.

Studies reveal a worrying paradox — higher education can correlate with higher unemployment for women, demanding deeper investigation into societal and economic factors at play. Beyond unemployment rates, questions linger about job quality and inclusivity. Are skill mismatches, gender bias, or structural issues at play? Addressing these questions with qualitative studies and deeper analyses is crucial for formulating effective policies, particularly for women and marginalised groups.

There has been an increase in the labour force participation rate (LFPR) in urban areas, which reflects the percentage of people either working or seeking work. The latest quarterly survey showed a slight rise in LFPR to 49.9% in the December quarter from 49.3% in the September quarter, with increases observed for both males and females, as their LFPR rose to 74.1% and 25%, respectively. With more job seekers entering the market, employment opportunities for both men and women have improved, as evidenced by the increase in the share of salaried jobs to 47.3% and 53%, respectively, in the December quarter.

The rise of self-employment

A significant number of job seekers have found work through self-employment, including roles as unpaid helpers in household enterprises or owning an enterprise. The share of self-employment in urban areas rose slightly to 40.6% in Q3 from 40.4% in Q2. The rise of self-employment, while providing opportunities, raises concerns about security and potential underemployment. While NSO data is valuable, it may not fully capture the “gig economy” or disguised unemployment, necessitating further investigation into their prevalence and impact.

The services sector, the largest employer in urban areas, saw an increase in worker participation to 62% in Q3 from 61.5% in the previous quarter, while the share of workers in the secondary (manufacturing) sector slightly declined.

Previously, the National Sample Survey Organisation would release employment and unemployment data based on household socio-economic surveys once every five years, which proved inadequate in capturing the actual employment picture. In response, NSO launched India’s first computer-based survey in April 2017 to measure labour force participation dynamics at three-month intervals for urban areas. The availability of labour force data at frequent intervals is crucial for understanding labour market trends more accurately and efficiently, serving as a valuable resource for policymakers and the government.

Furthermore, questions remain regarding whether official unemployment data accounts for all types of unemployment, such as disguised unemployment, underemployment, and gig workers, raising concerns about the holistic nature of NSO data. The shift to quarterly PLFS surveys improved data availability, but limitations remain. Recent research suggests NSO data do not delve into job quality, leaving questions about sustainability and social security unanswered.