In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

In the post-Covid financial year of 2021, the poorest ** percent of households witnessed income levels shrink by ** percent from levels in financial year 2016. The pandemic resulted in the gap between the richest and the poorest ** percent from *** times in financial year 2016 to ** times in financial year 2021. In the financial year 2023, the gap narrowed down to ***** times.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Indian Trail: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 184(1.41%) households where the householder is under 25 years old, 4,951(37.86%) households with a householder aged between 25 and 44 years, 5,924(45.30%) households with a householder aged between 45 and 64 years, and 2,019(15.44%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the town of Indian Trail, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Indian Trail median household income by age. You can refer the same here

In the financial year 2021, the number of super-rich households earning more than ** million Indian rupees went up to **** million from **** million in the financial year 2016. This was an annual growth of **** percent. The number is expected to grow to over **** million in the financial year 2031 and ** million households in the financial year 2047. This will be the fastest growth across all income categories. On the other hand, destitute classified Indian households with earnings of less than *** thousand annually decreased only marginally to ***** million in financial year 2021 from **** million in 2016. However, it is estimated that the number of destitute households will fall to just *** million by the financial year 2047.

India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

About this dataset

Context

The dataset tabulates the median household income in Indian Village. It can be utilized to understand the trend in median household income and to analyze the income distribution in Indian Village by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Indian Village, IN Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Indian Village, IN: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Indian Village, IN
• Indian Village, IN households by income brackets: family, non-family, and total, in 2022 inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Indian Village median household income. You can refer the same here

India’s per capita net national income or NNI was around *** thousand rupees in financial year 2025. The annual growth rate was *** percent as compared to the previous year. National income indicators   While GNI (Gross National Income) and NNI are both indicators for a country’s economic performance and welfare, the GNI is related to the GDP plus the net receipts from abroad, including wages and salaries, property income, net taxes and subsidies receivable from abroad. On the other hand, the NNI of a country is equal to its GNI net of depreciation. In 2020, India ranked second amongst the Asia Pacific countries in terms of its gross national income. This has been possible due to a favorable GDP growth in India. Measuring wealth versus welfare   National income per person or per capita is often used as an indicator of people's standard of living and welfare. However, critics object to this by citing that since it is a mean value, it does not reflect the real income distribution. In other words, a small wealthy class of people in the country can skew the per capita income substantially, even though the average population has no change in income. This is exemplified by the fact that in India, the top one percent of people, control over 40 percent of the country’s wealth.

Dataset extracted from the post Latest Error Free Income Tax Slabs in India 2024-25: What Changed & What to Choose on Smart Investello.

In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about *** percent were worth more than *********** dollars that year. India The Republic of India is one of the world’s largest and most economically powerful states. India gained independence from Great Britain on August 15, 1947, after having been under their power for 200 years. With a population of about *** billion people, it was the second most populous country in the world. Of that *** billion, about **** million lived in New Delhi, the capital. Wealth inequality India suffers from extreme income inequality. It is estimated that the top 10 percent of the population holds ** percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

Income tax statistics: When we talk about income simultaneously, we consider income tax. Every country in this world apart from a few countries tax payable countries. There are many types of taxes that a person has to pay in his employment period. Be it a business or any individual doing a normal job, they are never exempted from paying income tax unless the income doesn’t fall under the predetermined slab. In these Income tax statistics, we will get an idea of what income tax is, how it is different in every country, and many other insights. It is not only the duty of the individual to pay taxes but also corporations that run their business within specified legal boundaries. What Refers To Income Tax? The word tax refers to the amount paid to the government on the income earned by any individual by means of business or employment within the local boundaries. It is not mandatory to pay taxes until the individual reaches the predetermined tax slab. Income tax is a part of the government’s revenue used to spend on public services or utilities. The income is used only for the good of the public within the specified boundaries (Source: Investopedia.com)

Between the financial year 2016 and 2021, the number of super-rich households in India earning more than ** million Indian rupees recorded an annual growth of **** percent. The growth is expected to continue in the next decade at **** percent. This will be the fastest growth across all income categories. The share of destitute households is expected to decline by almost * percent between financial 2021 and 2031.

Disposable Personal Income in India increased to 296383300 INR Million in 2023 from 273364818.90 INR Million in 2022. This dataset provides - India Total Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

India Households: Gross Disposable Income data was reported at 131,525,002.483 INR mn in 2018. This records an increase from the previous number of 119,566,177.097 INR mn for 2017. India Households: Gross Disposable Income data is updated yearly, averaging 98,430,689.082 INR mn from Mar 2012 (Median) to 2018, with 7 observations. The data reached an all-time high of 131,525,002.483 INR mn in 2018 and a record low of 70,347,611.519 INR mn in 2012. India Households: Gross Disposable Income data remains active status in CEIC and is reported by Central Statistics Office. The data is categorized under Global Database’s India – Table IN.AI002: NAS 2011-2012: National and Personal Disposable Income.

According to a survey conducted in 2015 across India, over ** percent of the surveyed households had an average monthly income up to 10,000 Indian rupees. This percentage varied among the rural and urban areas, where over ** percent of the rural households and ** percent of the urban households earned up to 10,000 Indian rupees monthly. India had a high rate of rural to urban migration, as Indian cities provided better standards of living and employment opportunities.

Multiple income generators

For most of the population, income is earned in form of wages or salary, rent from residential or commercial property, interest from financial investments, and profits from family businesses. Most Indian households have multiple earning members to support consumption expenses on a day to day basis. During the surveyed year, around ** percent of the households had a single earner, mostly the head of the family, followed by about ** percent of households with two earning members.

Employment scenario

There are a lot of uncertainties in the job market in India. Non-availability of jobs matching education and skills was one of the main reasons for unemployment among Indian graduates. Underemployment was also a problem, and it was higher in urban areas than rural ones. Even though a majority of the population was self-employed, most jobs taken by workers had no written job contracts in both the salaried and casual employment sectors.

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

This dataset contains the total personal income tax and corporate tax collections and section-wise revenue foregone due to incentives, exemptions and deductions for all the categories of taxpayers viz., Corporate Sector; Non-Corporate Sector (Firms, Association of Persons, Body of Individuals etc.); and Individuals/ Hindu Undivided Families.

Note: 1. For Corporate sector, total revenue forgone is calculated by deducting the Net Additional Tax due to MAT. 2. Revenue Impact for 2023-24 are Projected.

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Brazil. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In Brazil, the median household income for the households where the householder is White increased by $8,641(21.63%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $39,951 in 2013 and $48,592 in 2023.
• Black or African American: Even though there is a population where the householder is Black or African American, there was no median household income reported by the U.S. Census Bureau for both 2013 and 2023.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in Brazil.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Brazil median household income by race. You can refer the same here

This dataset contains 30,000 records representing job market and salary trends across India’s top companies, popular tech and non-tech roles, multiple cities, and experience levels. It is designed to help researchers, analysts, and machine-learning practitioners analyze salary patterns, hiring demand, geographic trends, remote-work adoption, and career progression dynamics in the Indian job ecosystem.

Each row represents a job-related snapshot tied to a specific date, making the dataset suitable for trend analysis, forecasting, and workforce analytics. Salaries have been generated using realistic ranges for each job category in India, and demand indicators reflect hiring trends seen across major urban centers such as Bangalore, Hyderabad, Pune, and Delhi.

This dataset is useful for: Salary prediction (regression modeling) Job market demand forecasting Skill-driven salary analysis Remote work adoption analytics City-wise hiring and compensation gaps Experience-level salary progression Time-series trend analysis Workforce planning and HR analytics ML projects using categorical + time-series data

All company names, job roles, cities, and experience ranges are based on real Indian labor market dynamics, making the dataset relevant, practical, and highly useful for exploratory analysis and machine learning.

COLUMN DESCRIPTIONS

Record_Date The date of the job market observation. Useful for time-series trend modeling.

Company_Name The Indian company offering the job role (e.g., TCS, Infosys, Reliance, Accenture India, Amazon India).

Job_Role The position or designation (e.g., Software Engineer, Data Analyst, Product Manager).

Experience_Level Experience bracket required for the role (e.g., 1–3 years, 5–8 years).

City Location of the job such as Bangalore, Pune, or Hyderabad.

Salary_INR Annual salary offered for that job role (in Indian Rupees).

Demand_Index A 0–100 indicator representing hiring demand for that role/location.

Remote_Option_Flag 1 if the job supports remote/hybrid work, 0 if on-site only.

Salary_Trend_Pct Month-to-month salary percentage change for similar roles.

India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 2.010 Intl $/Day in 2011. This records an increase from the previous number of 1.610 Intl $/Day for 2004. India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 1.810 Intl $/Day from Dec 2004 (Median) to 2011, with 2 observations. The data reached an all-time high of 2.010 Intl $/Day in 2011 and a record low of 1.610 Intl $/Day in 2004. India IN: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

This data is about Economic Survey National Income for the period 1950-2020. Data from Ministry of Finance, India.Follow datasource.kapsarc.org for timely data to advance energy economics research.