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India’s Unemployment Rate from 1993 to 2023, by state

UID: EC-20241109-IN-02

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Source

NSSO Employment & Unemployment Survey Reports; NITI Aayog; and Periodic Labour Force Survey (PLFS), NSO.

Last Updated

November 12, 2024

Time Range

1993 – 2023

Periodicity

Annual

Overview

The unemployment rate is a key economic indicator that measures the percentage of the labour force actively seeking employment but unable to find work. It is calculated by dividing the number of unemployed individuals by the total labour force, including both employed and unemployed persons, then multiplying by 100. The labour force comprises individuals aged 16 and older who are either employed or actively looking for work.

The unemployment rate reflects the health of an economy. A high rate suggests economic distress, with more people struggling to find jobs, while a low rate indicates a robust economy with ample employment opportunities. However, it doesn’t capture underemployment or those who have stopped searching for work, known as “discouraged workers.” Governments and economists closely monitor this rate to guide economic policies, affecting wages, consumer spending, and overall economic growth.

Trends & Insights

The national unemployment rate rose from 12% (rural) and 45% (urban) in 1993-94 to 24% (rural) and 54% (urban) in 2022-23, indicating a persistent challenge in job creation relative to workforce growth. However, Urban unemployment consistently remained higher than rural unemployment across most of the states, possibly due to higher job expectations, skill mismatches, and the formal nature of urban employment. The urban-rural divide was particularly pronounced in states/UTs like Delhi, where urban unemployment peaked at 108% (overall) in 2018-19, while rural rates showed high volatility. There were notable gender differences in unemployment, with female unemployment rates typically reported higher than males, particularly in cities. The all-India urban female unemployment rate increased from 62% in 1993-94 to 75% in 2022-23, while for males, it increased from 40% to 47% in the same period. This suggests persistent barriers to female workforce participation and employment opportunities. Some states showed particularly concerning trends. Nagaland, for instance, consistently recorded high unemployment rates, reaching extreme levels of 258% (rural overall) in 2019-20. Similarly, northeastern states like Manipur and Tripura experienced high volatility in their unemployment rates, reflecting structural economic challenges in the region. Kerala presents an interesting case with relatively high unemployment rates despite its high literacy and human development indicators. In this highly developed state, the unemployment rates remained consistently above national averages, suggesting a mismatch between education output and job market requirements. The period from 2017-18 to 2022-23 showed exceptionally high unemployment rates across most of the states, with many experiencing their peak rates during this period. This could be attributed to various factors, including demonetization impacts, GST implementation, and, later, the COVID-19 pandemic’s economic effects. Union Territories like Lakshadweep and Andaman & Nicobar Islands showed extremely volatile unemployment rates, particularly among females, with figures sometimes exceeding 400%, indicating severe structural employment challenges in these regions. The unemployment rates in many states fell somewhat in recent years (2020–23).  However, the recovery was not uniform; while some states, like Nagaland and Manipur, consistently reported high unemployment, others, like Delhi, Gujarat, and Karnataka, recovered quickly. The data also reveals a concerning trend of higher unemployment among urban-educated youth, particularly among females, suggesting that higher education only sometimes translates into employment opportunities. This is clearly evident in states like Himachal Pradesh and Uttarakhand, where urban female unemployment rates remained persistently high. The regional disparities in unemployment rates highlight the need for state-specific employment generation strategies, particularly addressing gender gaps and urban-rural divides. The consistently higher rates in certain regions also suggest structural issues that require long-term policy interventions beyond simple job creation schemes.

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Citation

Please cite this article using proper attribution to 360 Analytika when referencing or sharing our content.

NSSO Employment & Unemployment Survey Reports; NITI Aayog; and Periodic Labour Force Survey (PLFS), NSO. (2024). India’s unemployment rate from 1993 to 2023, by state (360 Analytika, Ed.) [Dataset]. 360 Analytika. https://360analytika.com/indias-expenditure-on-relief-on-natural-calamities-by-state/

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