At the end of 2022, the Gini coefficient of wealth in India stood at ****. This was a slight increase from previous years. The trend since 2000 shows rising inequalities among the Indian population. What is Gini coefficient of wealth? The Gini coefficient is a measure of wealth inequality. The coefficient of the Gini index ranges from 0 to 1 with 0 representing perfect equality and 1 representing perfect inequality. Wealth and income distribution and inequality can however vary greatly. In 2023, South Africa topped the list of the most unequal countries in the world in terms of income inequality. Why do economic inequalities persist in India? By the end of 2022, the richest citizens in the country owned more than ** percent of the country’s wealth. Asia’s two richest men Mukesh Ambani and Gautam Adani are Indians. The number of high-net-worth individuals has continuously increased over the last decades. While millions of people escaped poverty in the country in the last few years, the wealth distribution between rich and poor remains skewed. Crony capitalism and the accumulation of wealth through inheritance are some of the factors behind this widening gap.

Graph and download economic data for GINI Index for India (SIPOVGINIIND) from 1977 to 2022 about gini, India, and indexes.

In 2021, the Gini coefficient for India stood at ****. The Gini coefficient, or the Gini index, measures the inequality of income distribution, whereas a higher value closer to one (or 100 percent) represent greater inequality.

The Gini index quantifies the degree of inequality in the distribution of income (or sometimes consumption) among individuals or households within an economy. It compares the actual income distribution to a perfectly equal one. This is visualized through the Lorenz curve, which charts the cumulative share of total income against the cumulative share of recipients, starting from the poorest. The Gini index is derived from the area between the Lorenz curve and the line representing absolute equality, measured as a percentage of the total area beneath that line. A Gini index of 0 indicates perfect equality, while 100 signifies complete inequality.

Gini Coefficient data was reported at 0.328 NA in 2021. This records a decrease from the previous number of 0.338 NA for 2020. Gini Coefficient data is updated yearly, averaging 0.339 NA from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 0.359 NA in 2017 and a record low of 0.316 NA in 1993. Gini Coefficient data remains active status in CEIC and is reported by Our World in Data. The data is categorized under Global Database’s India – Table IN.OWID.ESG: Social: Gini Coefficient: Annual.

In 2011, the Gini coefficient in rural India stood at 31.1, while urban India reached a higher score of 39. The Gini coefficient, or the Gini index, measures the inequality of income distribution, whereas a higher value closer to one (or 100 percent) represent greater inequality.

Comparing the 130 selected regions regarding the gini index , South Africa is leading the ranking (0.63 points) and is followed by Namibia with 0.58 points. At the other end of the spectrum is Slovakia with 0.23 points, indicating a difference of 0.4 points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from 0 (=total equality of incomes) to one (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

The average for 2021 based on 5 countries was 36.92 index points. The highest value was in Malaysia: 40.7 index points and the lowest value was in India: 32.8 index points. The indicator is available from 1963 to 2023. Below is a chart for all countries where data are available.

In a survey conducted from August 2023 to July 2024, ********* recorded the lowest Gini coefficient, indicating reduced consumption inequality in rural areas of India. The Gini coefficient had decreased across states compared to the previous year.

In a survey conducted from August 2023 to July 2024, it was found tha******** recorded the lowest Gini coefficient, indicating reduced consumption inequality in urban areas of India. The Gini coefficient had decreased across states compared to the previous year.

Goal 10: Reduce inequality within and among countriesOn average – and taking into account population size – income inequality increased by 11% in developing countries between 1990 and 2010.A significant majority of households in developing countries – more than 75% – are living today in societies where income is more unequally distributed than it was in the 1990s.Children in the poorest 20% of the population are still up to three times more likely to die before their fifth birthday than children in the richest quintiles.Social protection has been significantly extended globally, yet persons with disabilities are up to five times more likely than average to incur catastrophic health expenditures.Despite overall declines in maternal mortality in the majority of developing countries, women in rural areas are still up to three times more likely to die while giving birth than women living in urban centres.The Gini Coefficient of income inequality for India has risen from 33.4% in 2004 to 33.6% in 2011.This map layer is offered by Esri India, for ArcGIS Online subscribers, If you have any questions or comments, please let us know via content@esri.in.

Inde: Gini income inequality index: Pour cet indicateur, La Banque mondiale fournit des données pour la Inde de 1977 à 2021. La valeur moyenne pour Inde pendant cette période était de 33.84 index points avec un minimum de 31.6 index points en 1993 et un maximum de 35.9 index points en 2017.

South Africa had the highest inequality in income distribution in 2024, with a Gini score of **. Its South African neighbor, Namibia, followed in second. The Gini coefficient measures the deviation of income (or consumption) distribution among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, and a value of 100 represents absolute inequality. All the 20 most unequal countries in the world were either located in Africa or Latin America & The Caribbean.

Explore gender statistics data focusing on academic staff, employment, fertility rates, GDP, poverty, and more in the GCC region. Access comprehensive information on key indicators for Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

academic staff, Access to anti-retroviral drugs, Adjusted net enrollment rate, Administration and Law programmes, Age at first marriage, Age dependency ratio, Cause of death, Children out of school, Completeness of birth registration, consumer prices, Cost of business start-up procedures, Employers, Employment in agriculture, Employment in industry, Employment in services, employment or training, Engineering and Mathematics programmes, Female headed households, Female migrants, Fertility planning status: mistimed pregnancy, Fertility planning status: planned pregnancy, Fertility rate, Firms with female participation in ownership, Fisheries and Veterinary programmes, Forestry, GDP, GDP growth, GDP per capita, gender parity index, Gini index, GNI, GNI per capita, Government expenditure on education, Government expenditure per student, Gross graduation ratio, Households with water on the premises, Inflation, Informal employment, Labor force, Labor force with advanced education, Labor force with basic education, Labor force with intermediate education, Learning poverty, Length of paid maternity leave, Life expectancy at birth, Mandatory retirement age, Manufacturing and Construction programmes, Mathematics and Statistics programmes, Number of under-five deaths, Part time employment, Population, Poverty headcount ratio at national poverty lines, PPP, Primary completion rate, Retirement age with full benefits, Retirement age with partial benefits, Rural population, Sex ratio at birth, Unemployment, Unemployment with advanced education, Urban population

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

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Data and insights on Wealth Distribution in India - share of wealth, average wealth, HNIs, wealth inequality GINI, and comparison with global peers.

As of 2022, the top 10 percent Indian population group in terms of pre-tax income was estimated to hold over ** percent of total income in India, whereas the bottom ** percent group only made up just over ** percent of total income. This reflected an even greater income gap compared to 2000.

These datasets form the basis of an empirical inquiry into whether income inequality belongs in a macro model of voter turnout. Time series modeling suggests that the Gini coefficient enters nonlinearly in Canada and this finding is confirmed in a panel data model of Indian states.

Wage Inequality (based on Gini coefficient) among women in India (and regions): 2004-05 and 2011-12.

The data contains 5 different files, classified by topic. The file india_pov_c81_revise.dta contains variables on the number of dams in each district as well as information about the neighbouring districts. The data set also includes data on local poverty, such as a povertygap measure, the gini coefficient, mean per capita expenditure. The file india_ag_extend contains in addition, data on agricultural produc tion ( value, yield) for major crops and distinguishes between water-intensive and non-water-intensive crops. The file census.dta contains data on the population size and occupation. The file india_public_updown_doc.dta contains data on the availability of public goods such as water access, power facilities and road. The file malaria_code81.dta contains in addition a variable about malaria incidence.

ObjectiveTo assess the change in the level of educational inequality and the contribution of social factors and demographic factors.Data sourceThree rounds of National Sample Survey viz. 64th (2007–2008), 71st (2014), and 75th (2017-2018) have been used.MethodsEducation Gini is used to study the extent of educational inequality over the time period. Decomposition method is used for "within-group" and “between group” inequality. Tobit regression model is utilized to study factors influencing average years of schooling (AYS). Finally, regression-based Shapley decomposition method is used to identify factors contributing in educational inequality.ResultsThe level of AYS has improved over the period and reached to 7.7 years in 2018. Further, the level of educational inequality gone down between 2007 and 2018, but the Gini indices are still concentrated around 38%. Decomposition of the Gini and Shapley regression approach indicates that the within-group component and rural-urban division contribute the most to educational inequality. Tobit model signifies that digital exposure, household occupation, wealth quintile, and household size play a key role in determining educational attainment.ConclusionThe paper underscores the improvement of education in rural areas by focusing on school infrastructure, e-learning, educational quality, and parent involvement.