In 2022, the majority of Indian adults had a wealth of 10,000 U.S. dollars or less. On the other hand, about 0.1 percent were worth more than one million 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 1.4 billion people, it was the second most populous country in the world. Of that 1.4 billion, about 28.5 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 77 percent of the national wealth. Billionaire fortune has increase sporadically in the last years whereas minimum wages have remain stunted.

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

In 2022, Mumbai was home to the highest number of millionaires, followed by India’s capital New Delhi, and the IT capital - Bengaluru. This comes as no surprise since all three cities have the largest share of high net worth households along with a booming economic outlook. Overall, India had around 187 billionaires as of March 2023, and ranked third globally in terms of its ultra-net-worth individuals.

A growing wealth gap

Despite this, India also has a very high wealth inequality with millions of people living below the poverty line. In fact, according to the last census, the state of Maharashtra (with Mumbai as its capital city) had the highest number of slums across the country with over 2.5 million households. Furthermore, according to a 2015 study on the geography of the super-rich, Bangalore was ranked first in terms of the inequality between its rich and poor, with the wealth of the city’s billionaires being 646,407 times that of the average per capita GDP in the city. Mumbai came second in this listing, while Delhi was ranked fifth.

It's a rich man's world

As of 2018, the richest 10 percent of Indians owned 77.4 percent of the country’s wealth. The Indian economy was also seen to be one of the fastest growing economies across the world. This indicates the level of unequal distribution of wealth in the country. This is a matter of grave concern and has several implications in terms of the country’s development and progress.

In the financial year 2021, the average annual saving of rich households in India was over 606 thousand Indian rupees, a stark contrast to destitute category which saved only five thousand Indian rupees. The middle-class saved almost 130 thousand Indian rupees annually. During the year, a rich household spent almost 25 times that of a destitute household, eight times that of an aspirer household, and almost three times that of a middle-class household.

According to 2021 Forbes data, the richest man in India is business magnate Mukesh Ambani with a net worth of about 84.5 billion U.S. dollars.

Wealth distribution in India

India’s wealth is very unevenly distributed, with the wealthiest one percent of inhabitants owning more than half of the wealth. Currently, the majority of Indians own less than 10,000 U.S. dollars in wealth and assets and over 80 percent of Indian households have an average monthly income of 20,000 Indian rupees (about 286 U.S. dollars) or less – and even less in rural areas. Poverty is among the most common worries of Indian people and a prevalent problem in the country, despite a growing economy.

India’s growing economy benefits many, but not all

Most Indians live in rural areas, where agriculture is still the main provider. In fact, agriculture was an important economic driver for a long time, until services gained traction (and now generates almost half of India’s GDP). Mukesh Ambani, India’s richest entrepreneur, is one of the beneficiaries of this development, since his company, Reliance Industries, owns businesses mostly in the services sector.

Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund data was reported at 4,298,255.006 INR mn in Jan 2025. This records a decrease from the previous number of 4,427,613.663 INR mn for Dec 2024. Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund data is updated monthly, averaging 2,442,855.965 INR mn from Jan 2021 (Median) to Jan 2025, with 49 observations. The data reached an all-time high of 4,427,613.663 INR mn in Dec 2024 and a record low of 784,618.488 INR mn in Jan 2021. Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund data remains active status in CEIC and is reported by Association of Mutual Funds in India. The data is categorized under India Premium Database’s Financial Market – Table IN.ZC009: Mutual Funds Statistics: Association of Mutual Funds in India (AMFI): Average Net Assets Under Management.

India’s per capita net national income or NNI was around 200 thousand rupees in financial year 2025. The annual growth rate was 8.6 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.

Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund在2025-01达4,298,255.006INR mn，相较于2024-12的4,427,613.663INR mn有所下降。Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund数据按月度更新，2021-01至2025-01期间平均值为2,442,855.965INR mn，共49份观测结果。该数据的历史最高值出现于2024-12，达4,427,613.663INR mn，而历史最低值则出现于2021-01，为784,618.488INR mn。CEIC提供的Mutual Funds: Average Net Assets Under Management: Open Ended Schemes: Growth/Equity Oriented: Flexi Cap Fund数据处于定期更新的状态，数据来源于Association of Mutual Funds in India，数据归类于India Premium Database的Financial Market – Table IN.ZC009: Mutual Funds Statistics: Association of Mutual Funds in India (AMFI): Average Net Assets Under Management。

India Financial Assets and Liabilities: Households: Flow: Net / Net Financial Savings data was reported at 5,059,377.893 INR mn in Mar 2023. This records an increase from the previous number of 2,794,601.269 INR mn for Dec 2022. India Financial Assets and Liabilities: Households: Flow: Net / Net Financial Savings data is updated quarterly, averaging 4,250,169.272 INR mn from Jun 2018 (Median) to Mar 2023, with 20 observations. The data reached an all-time high of 6,791,743.901 INR mn in Mar 2021 and a record low of 2,386,135.644 INR mn in Jun 2019. India Financial Assets and Liabilities: Households: Flow: Net / Net Financial Savings data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Monetary – Table IN.KAJ001: Financial Assets and Liabilities: Household: Flow.

This dataset is about book subjects and is filtered where the books includes Rich Indians : Native people and the problem of wealth in American history, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the Census of Population.For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, please refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote2referrerFootnote 3Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote3referrerFootnote 4The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote4referrerFootnote 5Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.Return to footnote5referrerFootnote 6Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For more information on Aboriginal variables, including information on their classifications, the questions from which they are derived, data quality and their comparability with other sources of data, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016 and the Aboriginal Peoples Technical Report, Census of Population, 2016.Return to footnote6referrerFootnote 7'Aboriginal identity' includes persons who are First Nations (North American Indian), Métis or Inuk (Inuit) and/or those who are Registered or Treaty Indians (that is, registered under the Indian Act of Canada) and/or those who have membership in a First Nation or Indian band. Aboriginal peoples of Canada are defined in the Constitution Act, 1982, section 35 (2) as including the Indian, Inuit and Métis peoples of Canada.Return to footnote7referrerFootnote 8'Single Aboriginal responses' includes persons who are in only one Aboriginal group, that is First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote8referrerFootnote 9Users should be aware that the estimates associated with this variable are more affected than most by the incomplete enumeration of certain Indian reserves and Indian settlements in the 2016 Census of Population. For additional information, refer to the Aboriginal Peoples Reference Guide, Census of Population, 2016.Return to footnote9referrerFootnote 10'Multiple Aboriginal responses' includes persons who are any two or all three of the following: First Nations (North American Indian), Métis or Inuk (Inuit).Return to footnote10referrerFootnote 11'Aboriginal responses not included elsewhere' includes persons who are not First Nations (North American Indian), Métis or Inuk (Inuit), but who have Registered or Treaty Indian status and/or Membership in a First Nation or Indian band.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Indian Lake, TX, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Indian Lake, TX reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Indian Lake households based on income levels.

Key observations

• For Family Households: In Indian Lake, the majority of family households, representing 18.81%, earn $60,000 to $74,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $30,000 to $34,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Indian Lake, the majority of non-family households, accounting for 36.89%, have income $15,000 to $19,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $30,000 to $34,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

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

Income Levels:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Indian Lake, TX (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Indian Lake, TX
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Indian Lake, TX
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Indian Lake, TX

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 Lake median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Indian Shores, FL, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Indian Shores, FL reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Indian Shores households based on income levels.

Key observations

• For Family Households: In Indian Shores, the majority of family households, representing 25.07%, earn $200,000 or more, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $20,000 to $24,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Indian Shores, the majority of non-family households, accounting for 15.83%, have income $100,000 to $124,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $20,000 to $24,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

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

Income Levels:

• 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
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Indian Shores, FL (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Indian Shores, FL
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Indian Shores, FL
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Indian Shores, FL

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 Shores median household income. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian Head. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian Head, the median income for all workers aged 15 years and older, regardless of work hours, was $45,083 for males and $52,068 for females.

Contrary to expectations, women in Indian Head, women, regardless of work hours, earn a higher income than men, earning 1.15 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

- Full-time workers, aged 15 years and older: In Indian Head, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,553, while females earned $66,786

Contrary to expectations, in Indian Head, women, earn a higher income than men, earning 1.05 dollars for every dollar earned by men. This analysis showcase a consistent trend of women outearning men, when working full-time or part-time in the town of Indian Head.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Head median household income by race. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian River County. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian River County, the median income for all workers aged 15 years and older, regardless of work hours, was $43,511 for males and $30,373 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Indian River County. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecounty of Indian River County.

- Full-time workers, aged 15 years and older: In Indian River County, among full-time, year-round workers aged 15 years and older, males earned a median income of $58,744, while females earned $50,207, resulting in a 15% gender pay gap among full-time workers. This illustrates that women earn 85 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the county of Indian River County.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Indian River County.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 River County median household income by race. You can refer the same here

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian Hills. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian Hills, the median income for all workers aged 15 years and older, regardless of work hours, was $112,074 for males and $57,664 for females.

These income figures highlight a substantial gender-based income gap in Indian Hills. Women, regardless of work hours, earn 51 cents for each dollar earned by men. This significant gender pay gap, approximately 49%, underscores concerning gender-based income inequality in the city of Indian Hills.

- Full-time workers, aged 15 years and older: In Indian Hills, among full-time, year-round workers aged 15 years and older, males earned a median income of $175,313, while females earned $90,391, leading to a 48% gender pay gap among full-time workers. This illustrates that women earn 52 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Indian Hills, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Hills median household income by race. You can refer the same here

In the financial year 2021, the average annual expenditure of rich households in India was over 2 million Indian rupees, a stark contrast to destitute category which spent 83 thousand Indian rupees. A rich household spent almost 25 times that of a destiture household, eight times that of an aspirer household, and almost three times that of a middle-class household.

In 2024, the average monthly salary was 36.7 thousand Indian rupees in Mumbai city of India. The average monthly salary in the capital city of Delhi was around 36.6 thousand Indian rupees. In comparison, the average monthly salary was over 28 thousand Indian rupees in Madurai during the same year.

As of 2022, the top 10 percent Indian population group in terms of pre-tax income was estimated to hold over 57 percent of total income in India, whereas the bottom 50 percent group only made up just over 15 percent of total income. This reflected an even greater income gap compared to 2000.

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 Rich Hill. 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 Rich Hill, the median household income for the households where the householder is White increased by $7,657(20.27%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $37,770 in 2013 and $45,427 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in Rich Hill, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• 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 Rich Hill.
• 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 Rich Hill median household income by race. You can refer the same here