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Statistics of Unemployment in India | Unemployment Rate in India
The statistics of unemployment in India are a crucial indicator of the country’s labor market dynamics and economic performance. As of the latest available data, the unemployment rate in India was estimated to be 8% in 2024(February), according to the official figures released by the Ministry of Labour and Employment. However, it’s important to note that these statistics have been the subject of debate, with some experts arguing that the actual unemployment rate could be higher due to underemployment and informal labor market dynamics not fully captured in the official data.
The unemployment rate is calculated as the percentage of the labor force that is actively seeking employment but is unable to find work. This includes both urban and rural areas and encompasses various demographic groups, including youth, women, and rural workers. Additionally, the statistics of unemployment in India also consider factors such as education levels, skills, and regional disparities in job availability.
The unemployment rate in India is a complex and pressing issue that has significant social and economic implications. With a population of over 1.3 billion people, India faces the daunting challenge of providing employment opportunities for a large and growing workforce.
However, it’s important to note that this official figure has been a subject of debate, with some experts arguing that the actual unemployment rate could be higher due to underemployment and informal labor market dynamics. One of the key factors contributing to the high unemployment rate in India is the gap between the skills possessed by the workforce and the skills demanded by the job market. Many young people entering the job market lack the necessary skills and qualifications to secure employment in the formal sector, leading to a mismatch between supply and demand in the labor market. Additionally, the rapid pace of automation and technological advancement has also led to job displacement in certain sectors, further exacerbating the unemployment problem.
Furthermore, the COVID-19 pandemic has had a profound impact on the unemployment rate in India. The nationwide lockdown and economic disruptions resulted in widespread job losses, particularly in the informal and low-skilled sectors. Many migrant workers were forced to return to their home villages after losing their livelihoods in urban areas, further straining the job market. Addressing the issue of unemployment in India will require a multi-faceted approach that includes targeted skills development programs, investment in education and vocational training, and the promotion of entrepreneurship and small-scale industries. Additionally, there is a need for policies that can stimulate job creation and attract investment in key sectors of the economy. Tackling the unemployment challenge is crucial for India’s sustainable development and inclusive growth.
Unemployment Figures in India :
| Year | Unemployment Rate (%) |
|---|---|
| 2024 | 8 (February 2024) |
| 2023 | 8.03 |
| 2022 | 7.33 |
| 2021 | 5.98 |
| 2020 | 8.00 |
| 2019 | 5.27 |
| 2018 | 5.33 |
| 2017 | 5.36 |
| 2016 | 5.42 |
| 2015 | 5.44 |
| 2014 | 5.44 |
| 2013 | 5.42 |
| 2012 | 5.41 |
| 2011 | 5.43 |
| 2010 | 5.55 |
| 2009 | 5.54 |
| 2008 | 5.41 |
India Jobless Rate Statewise 2024 : India Unemployment Rate 2024
| Unemployment Rate in India State-wise | |
| State | % of Unemployment Rate in India |
| Haryana | 37.4 |
| Rajasthan | 28.5 |
| Bihar | 19.1 |
| Jharkhand | 18 |
| Jammu and Kashmir | 14.8 |
| Tripura | 14.3 |
| Sikkim | 13.6 |
| Goa | 9.9 |
| Andhra Pradesh | 7.7 |
| Himachal Pradesh | 7.6 |
| Assam | 4.7 |
| Haryana | 3.74 |
| Chhattisgarh | 3.4 |
| Madhya Pradesh | 3.2 |
| Maharashtra | 3.1 |
| Karnataka | 2.5 |
| Gujrat | 2.3 |
| Odisha | 0.9 |
India Jobless Rate Statewise 2023 : India Unemployment Rate 2023
The Center for Monitoring Indian Economy (CMIE) has reported a rise in India’s unemployment rate to 8.30%, the highest level in 16 months, up from 8.00% in November. According to CMIE data, the urban unemployment rate increased to 10.09% in December from 8.96% in November, while rural areas experienced a slight decrease from 7.55% to 7.44%. In 2022, Haryana recorded the highest state unemployment rate at 37.4%, while Odisha had the lowest rate at 0.9%. The CMIE statistics released on March 1, 2023, offer a detailed breakdown of unemployment across different states in India for December 2022, providing insights into the varying employment challenges faced by these regions.
| Month | India Rate | Urban Rate | Rural Rate |
| Dec 2022 | 8.30 | 10.09 | 7.44 |
| Nov 2022 | 8.03 | 8.92 | 7.61 |
| Oct 2022 | 7.92 | 7.34 | 8.19 |
| Sep 2022 | 6.43 | 7.71 | 5.83 |
| Aug 2022 | 8.28 | 9.57 | 7.68 |
| Jul 2022 | 6.83 | 8.22 | 6.17 |
| Jun 2022 | 7.83 | 7.32 | 8.07 |
| May 2022 | 7.14 | 8.24 | 6.63 |
| Apr 2022 | 7.83 | 9.22 | 7.18 |
| Mar 2022 | 7.57 | 8.28 | 7.24 |
| Feb 2022 | 8.11 | 7.57 | 8.37 |
| Jan 2022 | 6.56 | 8.14 | 5.83 |
| State | Unemployment Rate (Dec 2023) |
| Andhra Pradesh | 7.7 |
| Assam | 4.7 |
| Bihar | 19.1 |
| Chhattisgarh | 3.4 |
| Delhi | 20.8 |
| Goa | 9.9 |
| Gujarat | 2.3 |
| Haryana | 37.4 |
| Himachal Pradesh | 7.6 |
| Jammu & Kashmir | 14.8 |
| Jharkhand | 18.0 |
| Karnataka | 2.5 |
| Kerala | 7.4 |
| Madhya Pradesh | 3.2 |
| Maharashtra | 3.1 |
| Meghalaya | 2.7 |
| Odisha | 0.9 |
| Puducherry | 4.7 |
| Punjab | 6.8 |
| Rajasthan | 28.5 |
| Sikkim | 13.6 |
| Tamil Nadu | 4.1 |
| Telangana | 4.1 |
| Tripura | 14.3 |
| Uttar Pradesh | 4.3 |
| Uttarakhand | 4.2 |
| West Bengal | 5.5 |
India Jobless Rate Statewise 2022 : India Unemployment Rate 2022
| STATE | JAN 2022 | FEB 2022 | MAR 2022 | APR 2022 | MAY 2022 | JUN 2022 | JUL 2022 | AUG 2022 | SEP 2022 | Oct 2022 | Nov 2022 |
| Andhra Pradesh | 6.2 | 7.1 | 9.2 | 5.3 | 4.4 | 4.5 | 5.8 | 6 | 4.8 | 5.4 | 9.0 |
| Assam | 8.5 | 10.2 | 7.7 | 1.2 | 8.2 | 17.2 | 3.7 | NA | 0.4 | 8.1 | 13.2 |
| Bihar | 13.3 | 13.9 | 14.4 | 21.1 | 13.3 | 14 | 18.8 | 12.8 | 11.4 | 15.0 | 17.3 |
| Chhattisgarh | 3 | 1.7 | 0.6 | 0.6 | 0.8 | 1.2 | 0.8 | 0.4 | 0.1 | 0.9 | 0.1 |
| Delhi | 14.1 | 9.3 | 8.9 | 11.2 | 13.6 | 10.2 | 8.9 | 8.2 | 9.6 | 6.7 | 12.6 |
| Goa | 11.6 | 12 | 12.7 | 15.5 | 13.4 | 5.5 | 13.7 | 13.7 | 10.9 | NA | 13.6 |
| Gujarat | 1.2 | 2.5 | 1.8 | 1.6 | 2.1 | 3 | 2.2 | 2.6 | 1.6 | 1.7 | 2.5 |
| Haryana | 23.4 | 30.9 | 26.5 | 34.5 | 24.6 | 30.5 | 26.9 | 37.3 | 22.9 | 31.7 | 30.6 |
| Himachal Pradesh | 13.8 | 11.8 | 11.7 | 0.2 | 9.6 | 10.7 | 6.3 | 7.3 | 8.6 | 9.7 | 8.8 |
| Jammu & Kashmir | 15.2 | 13.2 | 25 | 15.6 | 18.3 | 17.2 | 20.2 | 32.8 | 23.2 | 22.6 | 22.4 |
| Jharkhand | 8.9 | 15 | 14.5 | 14.2 | 13.1 | 12.1 | 14 | 17.3 | 12.2 | 17.1 | 14.3 |
| Karnataka | 2.9 | 2 | 1.8 | 2.7 | 4.3 | 3.7 | 3.5 | 3.5 | 3.7 | 2.8 | 1.8 |
| Kerala | 5 | 5 | 6.7 | 5.8 | 5.8 | 5.3 | 4.9 | 6.1 | 6.4 | 4.8 | 5.9 |
| Madhya Pradesh | 3 | 2.8 | 1.6 | 1.6 | 1.7 | 0.5 | 1.9 | 2.6 | 0.8 | 0.8 | 6.9 |
| Maharashtra | 4.2 | 4.3 | 4 | 3.1 | 4.2 | 4.8 | 3.7 | 2.2 | 4 | 4.3 | 3.6 |
| Meghalaya | 1.5 | 1.4 | 2 | 2.2 | 4.1 | 2.3 | 1.5 | 2 | 2.3 | 3.5 | 2.3 |
| Odisha | 1.8 | 1 | 9.7 | 1.5 | 2.6 | 1.2 | 0.9 | 2.6 | 2.9 | 1.1 | 1.6 |
| Puducherry | 7.8 | 3.7 | 4.2 | 5.6 | 5.6 | 0.8 | 2.8 | 5.2 | 3.9 | 2.6 | 2.9 |
| Punjab | 9.3 | 9 | 6.9 | 7.2 | 9.2 | 8.5 | 7.7 | 7.4 | 7.2 | 9.1 | 7.8 |
| Rajasthan | 18.9 | 32.4 | 24.5 | 28.8 | 22.2 | 29.9 | 19.6 | 31.4 | 23.9 | 31.3 | 25.0 |
| Sikkim | NA | NA | NA | 8.7 | 7.5 | 12.7 | 6.5 | NA | NA | 3.9 | 5.7 |
| Tamil Nadu | 5.3 | 3.2 | 4.1 | 3.2 | 3.1 | 2.1 | 3 | 7.2 | 4.1 | 3.0 | 3.8 |
| Telangana | 0.7 | 12.9 | 6.5 | 9.9 | 9.4 | 10 | 5.8 | 6.9 | 8.6 | 8.8 | 6.0 |
| Tripura | 17.1 | 9.8 | 14.1 | 14.6 | 17.4 | 9.4 | 13 | 16.3 | 17 | 10.6 | 14.4 |
| Uttar Pradesh | 3 | 2.7 | 4.4 | 2.9 | 3.1 | 2.8 | 3.3 | 3.9 | 4 | 4.1 | 4.1 |
| Uttarakhand | 3.5 | 4.6 | 3.5 | 5.3 | 2.9 | 8.7 | NA | NA | 0.5 | 3.3 | 1.2 |
| West Bengal | 6.4 | 6.3 | 5.6 | 6.2 | 5.8 | 5.2 | 6.3 | 7.4 | 3.3 | 5.8 | 5.4 |
| India | 6.6 | 8.1 | 7.6 | 7.8 | 7.1 | 7.8 | 6.8 | 8.3 | 6.4 | 7.9 | 8.0 |
Last 10 Year Unemployment Rate of India :
| S.No | Year | Unemployment Rate in % |
|---|---|---|
| 1 | 2023 | 10.05Â (as of Oct) |
| 2 | 2022 | 7.33 |
| 3 | 2021 | 5.98 |
| 4 | 2020 | 8.00 |
| 5 | 2019 | 5.27 |
| 6 | 2018 | 5.33 |
| 7 | 2017 | 5.36 |
| 8 | 2016 | 5.42 |
| 9 | 2015 | 5.44 |
| 10 | 2014 | 5.44 |
Unemployment Rate in India VSÂ Unemployment Rate in the World :
| Country | Unemployment Rate |
| Nigeria | 9.79% |
| Egypt | 9.33% |
| Kyrgyz Republic | 9.10% |
| Ukraine | 8.88% |
| Angola | 8.53% |
| Honduras | 8.51% |
| Bolivia | 8.51% |
| Uzbekistan | 7.16% |
| Mongolia | 7.08% |
| India | 5.98% |
| Nicaragua | 5.96% |
| El Salvador | 5.94% |
| Kenya | 5.74% |
| Sri Lanka | 5.40% |
| Bangladesh | 5.23% |
| Timor-Leste | 5.07% |
| Ghana | 4.70% |
| Indonesia | 4.41% |
| Pakistan | 4.35% |
| Bhutan | 4.33% |
| Moldova | 3.96% |
| Cameroon | 3.87% |
| Papua New Guinea | 2.75% |
| Philippines | 2.41% |
| Vanuatu | 2.18% |
| Myanmar | 2.17% |
| Vietnam | 2.17% |
| Lao PDR | 1.26% |
| Solomon Islands | 1.03% |
| Cambodia | 0.61% |
India Unemployment Rate From 1960 – 2022 :
| Year | Unemployment Rate (%) | Annual Change |
|---|---|---|
| 2022 | 4.82% | -1.56% |
| 2021 | 6.38% | -1.48% |
| 2020 | 7.86% | 1.35% |
| 2019 | 6.51% | -1.14% |
| 2018 | 7.65% | -0.08% |
| 2017 | 7.73% | -0.08% |
| 2016 | 7.81% | -0.08% |
| 2015 | 7.89% | -0.09% |
| 2014 | 7.98% | -0.08% |
| 2013 | 8.06% | -0.08% |
| 2012 | 8.14% | -0.08% |
| 2011 | 8.22% | -0.09% |
| 2010 | 8.30% | -0.08% |
| 2009 | 8.38% | -0.08% |
| 2008 | 8.46% | -0.07% |
| 2007 | 8.54% | -0.08% |
| 2006 | 8.62% | -0.08% |
| 2005 | 8.70% | 0.16% |
| 2004 | 8.54% | 0.17% |
| 2003 | 8.37% | 0.17% |
| 2002 | 8.20% | 0.18% |
| 2001 | 8.02% | 0.17% |
| 2000 | 7.85% | 0.17% |
| 1999 | 7.68% | 0.17% |
| 1998 | 7.51% | 0.17% |
| 1997 | 7.34% | 0.17% |
| 1996 | 7.17% | 0.17% |
| 1995 | 7.00% | 0.17% |
| 1994 | 6.83% | -0.01% |
| 1993 | 6.84% | 0.00% |
| 1992 | 6.84% | 0.00% |
| 1991 | 6.84% | 6.84% |
| 1990 | 0.00% | 0.00% |
| 1989 | 0.00% | 0.00% |
| 1988 | 0.00% | 0.00% |
| 1987 | 0.00% | 0.00% |
| 1986 | 0.00% | 0.00% |
| 1985 | 0.00% | 0.00% |
| 1984 | 0.00% | 0.00% |
| 1983 | 0.00% | 0.00% |
| 1982 | 0.00% | 0.00% |
| 1981 | 0.00% | 0.00% |
| 1980 | 0.00% | 0.00% |
| 1979 | 0.00% | 0.00% |
| 1978 | 0.00% | 0.00% |
| 1977 | 0.00% | 0.00% |
| 1976 | 0.00% | 0.00% |
| 1975 | 0.00% | 0.00% |
| 1974 | 0.00% | 0.00% |
| 1973 | 0.00% | 0.00% |
| 1972 | 0.00% | 0.00% |
| 1971 | 0.00% | 0.00% |
| 1970 | 0.00% | 0.00% |
| 1969 | 0.00% | 0.00% |
| 1968 | 0.00% | 0.00% |
| 1967 | 0.00% | 0.00% |
| 1966 | 0.00% | 0.00% |
| 1965 | 0.00% | 0.00% |
| 1964 | 0.00% | 0.00% |
| 1963 | 0.00% | 0.00% |
| 1962 | 0.00% | 0.00% |
| 1961 | 0.00% | 0.00% |
| 1960 | 0.00% | 0.00% |
Causes of Unemployment in India :
Unemployment is a significant socio-economic challenge in India with far-reaching implications for individuals, families, and the overall development of the country. Several underlying factors contribute to the complex issue of unemployment in India, and understanding these causes is essential for formulating effective policies and interventions to address the problem.
1. Population Growth and Demographic Dividend: India’s large and rapidly growing population presents both opportunities and challenges. While the demographic dividend – the potential economic boost from a youthful population – can be advantageous, it also means that the labor force is expanding at a considerable rate. The economy must generate a sufficient number of jobs to absorb this growing workforce, which is a daunting task.
2. Skills Mismatch: A significant cause of unemployment in India is the mismatch between the skills possessed by the workforce and the skills demanded by the job market. Many job seekers lack the necessary qualifications and training required by the formal sector, leading to underemployment or unemployment. The rapid pace of technological advancement further exacerbates this issue, as traditional skills become obsolete, and new skills are in high demand.
3. Informal Sector and Underemployment: A large proportion of the Indian workforce is employed in the informal sector, which often lacks job security, benefits, and legal protections. Many workers in this sector are underemployed, meaning they work fewer hours than they desire or are engaged in low-productivity activities. As a result, the underutilization of human capital contributes to the unemployment challenge.
4. Slow Pace of Industrialization: India’s transition to a more industrialized economy has been slower compared to other developing countries. The lack of robust industrialization and a heavy reliance on agriculture contribute to limited job creation in urban areas, leading to rural-urban migration and urban unemployment.
5. Agricultural Distress: Agriculture is a significant source of livelihood for a substantial portion of the Indian population. However, the sector is characterized by low productivity, seasonal employment, and vulnerability to natural disasters. Agricultural distress and limited non-farm employment opportunities in rural areas lead to disguised unemployment and contribute to overall unemployment figures.
6. Public Sector Employment Challenges: The public sector, traditionally considered a stable source of employment, has been facing challenges due to fiscal constraints and a shift towards privatization and downsizing. As a result, the public sector’s capacity to absorb a large number of job seekers has diminished, impacting overall employment opportunities.
7. Economic Slowdown and Cyclical Unemployment: Periods of economic slowdown and recession lead to a decrease in demand for goods and services, resulting in reduced production and layoffs. This cyclical unemployment is a temporary phase but can have long-term repercussions on individuals and the economy.
8. Gender Disparities: Gender-based disparities in employment opportunities and participation rates contribute to overall unemployment figures. Women, especially in rural areas, face challenges in accessing formal employment and often engage in unpaid or underpaid work.
Impact of Unemployment in India :
Unemployment has far-reaching social, economic, and psychological implications for individuals, families, and the overall development of a country. In the context of India, where a significant portion of the population relies on employment for sustenance and economic security, the impact of unemployment is profound and multifaceted.
1. Economic Impact : Unemployment leads to a decrease in household income and purchasing power, which in turn affects overall consumer spending and economic growth. When individuals are unemployed, they have less disposable income to spend on goods and services, leading to reduced demand in the economy. This can further exacerbate the economic slowdown, affecting businesses, industries, and the overall GDP growth. Unemployment also results in a loss of human capital and productivity. When skilled individuals are unable to find suitable employment, their talents and capabilities are underutilized, leading to an overall loss of productive potential for the economy. This underutilization of human capital hinders innovation, creativity, and overall economic development.
2. Social Impact : Unemployment can have profound social consequences, including increased poverty, inequality, and social unrest. Families that rely on the income of an unemployed member may struggle to meet their basic needs, leading to financial stress, food insecurity, and inadequate access to healthcare and education. The psychological impact of unemployment can also manifest in increased stress, anxiety, and mental health challenges for individuals and their families. Long-term unemployment can lead to social exclusion and a sense of alienation for individuals who feel disconnected from the workforce and the broader society. This can further perpetuate cycles of poverty and marginalization, particularly in vulnerable communities and regions.
3. Demographic Impact : Unemployment and underemployment can significantly impact different demographic groups in India. For example, youth unemployment is a pressing issue, with young people facing challenges in accessing meaningful employment opportunities despite their aspirations and qualifications. This can lead to disillusionment, social unrest, and brain drain as talented individuals seek opportunities abroad. Women in the workforce also face unique challenges related to unemployment, including gender-based discrimination, limited access to formal employment, and lower labor force participation rates. Addressing gender disparities in unemployment is crucial for promoting gender equality and women’s empowerment in the workforce.
4. Political Impact : Unemployment and economic disenfranchisement can have political ramifications, leading to disillusionment with the government and institutions. High levels of unemployment can contribute to social and political unrest, as disenfranchised individuals seek avenues to express their grievances and demand change. This can impact social cohesion, political stability, and the overall governance of the country. Addressing the Impact of Unemployment Tackling the impact of unemployment in India requires a comprehensive and multi-pronged approach. Investing in education, skills development, and vocational training can enhance the employability of the workforce and align skill sets with the demands of the job market. Promoting entrepreneurship, small-scale industries, and innovation can create new avenues for job creation and economic growth. Social safety nets, such as unemployment benefits, access to healthcare, and social welfare programs, can provide crucial support for individuals and families during periods of unemployment. Additionally, efforts to address regional disparities, promote inclusive growth, and empower vulnerable populations are essential for mitigating the impact of unemployment and fostering a more equitable society.
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FAQs :
Q: How is unemployment rate in India calculated?
A: The unemployment rate in India is typically calculated as the percentage of the labor force that is actively seeking employment but is unable to find work. This calculation accounts for both urban and rural areas and considers various demographic groups.
Q: What are the sources of official unemployment data in India?
A: Official unemployment data in India is primarily sourced from government agencies such as the Ministry of Labour and Employment, as well as research organizations like the Center for Monitoring Indian Economy (CMIE) that conduct regular surveys and studies on employment trends.
Q: How frequently is unemployment data in India updated?
A: Unemployment data in India is usually updated at regular intervals, with some sources providing monthly, quarterly, or annual updates. The frequency of updates may vary depending on the organization or government agency releasing the data.
Q: What are the key demographic groups affected by unemployment in India?
A: Unemployment in India affects various demographic groups, including youth, women, rural workers, and individuals with different educational backgrounds. Understanding the specific challenges faced by these groups is crucial for addressing the complexities of unemployment.
Q: How does unemployment data in India impact policymaking and economic analysis?
A: Unemployment data in India plays a significant role in informing policymaking, economic analysis, and decision-making processes. It provides insights into labor market dynamics, regional disparities, and the overall health of the economy, guiding efforts to address unemployment challenges.
Q: Are there alternative measures of unemployment used in India?
A: In addition to the official unemployment rate, alternative measures such as underemployment, informal sector participation, and labor force participation rates are also considered to provide a more comprehensive understanding of employment dynamics in India.
Q: What are the limitations of unemployment data in India?
A: Like any statistical measure, unemployment data in India has limitations, including potential underreporting, difficulty capturing informal sector employment, and challenges in accounting for seasonal or cyclical variations in employment. Understanding these limitations is crucial for interpreting the data accurately.