In 2024, the median household income in the United States was 83,730 U.S. dollars. This reflected an increase from the previous year. Household income The median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varied from state to state. In 2024, Massachusetts recorded the highest median household income in the country, at 113,900 U.S. dollars. On the other hand, Mississippi, recorded the lowest, at 55,980 U.S. dollars.Household income is also used to determine the poverty rate in the United States. In 2024, 10.6 percent of the U.S. population was living below the national poverty line. This was the lowest level since 2019. Similarly, the child poverty rate, which represents people under the age of 18 living in poverty, reached a three-decade low of 14.3 percent of the children. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.52 in 2024. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality, while a score of one indicates complete inequality.

Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2024 about CA, households, median, income, and USA.

United States US: Income Share Held by Highest 10% data was reported at 30.600 % in 2016. This records an increase from the previous number of 30.100 % for 2013. United States US: Income Share Held by Highest 10% data is updated yearly, averaging 30.100 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 30.600 % in 2016 and a record low of 25.300 % in 1979. United States US: Income Share Held by Highest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

United States US: Income Share Held by Highest 20% data was reported at 46.900 % in 2016. This records an increase from the previous number of 46.400 % for 2013. United States US: Income Share Held by Highest 20% data is updated yearly, averaging 46.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 41.200 % in 1979. United States US: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

About this dataset

Context

The dataset illustrates the median household income in Middle township, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Middle township increased by $10,616 (13.20%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.

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 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Middle township median household income. You can refer the same here

This data package includes the underlying data files to replicate the data and charts presented in Is the United States undergoing a manufacturing renaissance that will boost the middle class? by Robert Z. Lawrence, PIIE Policy Brief 24-12.

If you use the data, please cite as: Lawrence, Robert Z. 2024. Is the United States undergoing a manufacturing renaissance that will boost the middle class? PIIE Policy Brief 24-12. Washington, DC: Peterson Institute for International Economics.

United States US: Income Share Held by Lowest 10% data was reported at 1.700 % in 2016. This stayed constant from the previous number of 1.700 % for 2013. United States US: Income Share Held by Lowest 10% data is updated yearly, averaging 1.800 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 2.300 % in 1979 and a record low of 1.700 % in 2016. United States US: Income Share Held by Lowest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

California State Income Limits reflect updated median income and household income levels for acutely low-, extremely low-, very low-, low- and moderate-income households for California’s 58 counties (required by Health and Safety Code Section 50093). These income limits apply to State and local affordable housing programs statutorily linked to HUD income limits and differ from income limits applicable to other specific federal, State, or local programs.

United States US: Income Share Held by Lowest 20% data was reported at 5.000 % in 2016. This records a decrease from the previous number of 5.100 % for 2013. United States US: Income Share Held by Lowest 20% data is updated yearly, averaging 5.300 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 6.400 % in 1979 and a record low of 5.000 % in 2016. United States US: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Context

In this problem, we will be examining the "state" dataset, which has data from the 1970s on all fifty US states. For each state, the dataset includes the population, per capita income, illiteracy rate, murder rate, high school graduation rate, average number of frost days, area, latitude and longitude, division the state belongs to, region the state belongs to, and two-letter abbreviation.

Content

This dataset has 50 observations (one for each US state) and the following 15 variables:

Population - the population estimate of the state in 1975 Income - per capita income in 1974 Illiteracy - illiteracy rates in 1970, as a percent of the population Life.Exp - the life expectancy in years of residents of the state in 1970 Murder - the murder and non-negligent manslaughter rate per 100,000 population in 1976 HS.Grad - percent of high-school graduates in 1970 Frost - the mean number of days with minimum temperature below freezing from 1931–1960 in the capital or a large city of the state Area - the land area (in square miles) of the state state.abb - a 2-letter abreviation for each state state.area - the area of each state, in square miles x - the longitude of the center of the state y - the latitude of the center of the state state.division - the division each state belongs to (New England, Middle Atlantic, South Atlantic, East South Central, West South Central, East North Central, West North Central, Mountain, or Pacific) state.name - the full names of each state state.region - the region each state belong to (Northeast, South, North Central, or West)

Acknowledgements

MITx ANALYTIX

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.

United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data was reported at 23.572 % in 2016. This records a decrease from the previous number of 23.988 % for 2015. United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data is updated yearly, averaging 15.223 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 24.284 % in 2014 and a record low of 11.189 % in 1983. United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Exports. Merchandise exports to low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Latin America and the Caribbean region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

This report provides a systematic review and empirical evidence related to the experiences of middle-income countries and economies participating in the Programme for International Student Assessment (PISA), 2000 to 2015. PISA is a triennial survey that aims to evaluate education systems worldwide by testing the skills and knowledge of 15-year-old students. To date, students representing more than 70 countries and economies have participated in the assessment, including 44 middle-income countries, many of which are developing countries receiving foreign aid. This report provides answers to six important questions about these middle-income countries and their experiences of participating in PISA: What is the extent of developing country participation in PISA and other international learning assessments? Why do these countries join PISA? What are the financial, technical, and cultural challenges for their participation in PISA? What impact has participation had on their national assessment capacity? How have PISA results influenced their national policy discussions? And what does PISA data tell us about education in these countries and the policies and practices that influence student performance? The findings of this report are being used by the OECD to support its efforts to make PISA more relevant to a wider range of countries, and by the World Bank as part of its on-going dialogue with its client countries regarding participation in international large-scale assessments.

The GDL Area Database (www.globaldatalab.org/areadata) presents socioeconomic, health, and demographic development indicators at the level of sub-national areas (provinces, states, prefectures, and the like) within low and middle income countries to the global community. The indicators are created by aggregating data from household survey datasets.

United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data was reported at 0.875 % in 2016. This records a decrease from the previous number of 0.944 % for 2015. United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data is updated yearly, averaging 1.715 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 5.651 % in 1975 and a record low of 0.753 % in 2003. United States US: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Exports. Merchandise exports to low- and middle-income economies in Middle East and North Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Middle East and North Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Net-Income Time Series for Elme Communities. Elme Communities is committed to elevating what home can be for middle-income renters by providing a higher level of quality, service, and experience. The Company is a multifamily real estate investment trust that owns and operates approximately 9,400 apartment homes in the Washington, DC metro and the Atlanta metro regions, and owns approximately 300,000 square feet of commercial space.

United States US: Income Share Held by Fourth 20% data was reported at 22.600 % in 2016. This records a decrease from the previous number of 22.700 % for 2013. United States US: Income Share Held by Fourth 20% data is updated yearly, averaging 22.700 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 23.600 % in 1986 and a record low of 22.300 % in 2000. United States US: Income Share Held by Fourth 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

About this dataset

Context

The dataset illustrates the median household income in Brownsville, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Brownsville increased by $6,339 (14.97%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 10 years and declined for 3 years.

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 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Brownsville median household income. You can refer the same here

Please find my Tableau viz for this dataset here: https://public.tableau.com/app/profile/jamie.collins5558/viz/CentralBankReserves/Dashboard1 Feel free to copy, or use as a template/inspiration for your own visualisations.

This dataset provides a comprehensive snapshot of central bank reserves, including foreign exchange (FX) reserves, total reserves, and gold holdings, for 165 countries. It includes detailed metrics such as gold reserves in tonnes and millions (USD), the percentage of total reserves held in gold, and the 20-year change in gold holdings. The dataset also categorises countries by region and economic grouping (e.g., high income, upper middle income, lower middle income, low income), offering a valuable resource for analysing global financial trends, reserve management strategies, and the role of gold in national economies.

• Country: The name of the country (e.g., Afghanistan, United States of America).
• Region: The geographical region of the country (e.g., Central Asia, Western Europe, Latin America & Caribbean).
• Economic grouping: The World Bank income classification of the country (e.g., High income, Upper middle income, - - -- Lower middle income, Low income).
• FX Reserves: Foreign exchange reserves in millions of USD (e.g., 68448.33 for Algeria). Some values are marked as "AWAITED" where data is unavailable.
• Total Reserves: Total reserves (including FX and gold) in millions of USD (e.g., 83007.11 for Algeria). Some values are marked as "AWAITED."
• Gold Reserves Tonnes: Gold reserves held by the central bank in metric tonnes (e.g., 173.56 for Algeria). Some values are marked as "AWAITED."
• Gold Reserves Millions: The value of gold reserves in millions of USD (e.g., 14558.78 for Algeria). Some values are marked as "AWAITED."
• Holdings %: The percentage of total reserves held in gold (e.g., 17.54 for Algeria). Some values are marked as "AWAITED."
• 20yr change: The change in gold holdings (in tonnes) over the past 20 years (e.g., -0.09 for Algeria). Positive values indicate an increase, while negative values indicate a decrease.

Key Statistics Countries Covered: 165 - Regions Represented: Includes Central Asia, Western Europe, Latin America & Caribbean, Middle East & North Africa, Sub-Saharan Africa, South East Asia, East Asia, South Asia, Australasia / Oceania, and North America. - Economic Groupings: High income (e.g., United States, Japan), Upper middle income (e.g., Brazil, China), Lower middle income (e.g., India, Egypt), and Low income (e.g., Afghanistan, Haiti). - Largest Gold Reserves: The United States holds the largest gold reserves at 8,133.46 tonnes, valued at $682,276.85 million, accounting for 74.97% of its total reserves. - Highest Gold Holdings %: Bolivia has the highest percentage of reserves in gold at 95.59%, despite holding only 22.53 tonnes. - Largest 20-Year Increase in Gold: The Russian Federation increased its gold holdings by 1,945.79 tonnes over 20 years, followed by China with a 1,684.55-tonne increase. Potential Use Cases

This dataset is ideal for a variety of analytical and research purposes, including:

• Economic Analysis: Investigate the relationship between a country’s economic grouping and its reserve composition, particularly the reliance on gold versus foreign exchange.
• Financial Stability Studies: Analyse how countries with higher gold holdings percentages (e.g., Bolivia, Uzbekistan) manage financial stability compared to those with lower percentages (e.g., Chile, South Korea).
• Historical Trends: Use the 20-year change in gold holdings to study trends in reserve management strategies, such as China and Russia’s significant increases in gold reserves.
• Geopolitical Insights: Explore how regions like Central Asia (e.g., Kazakhstan, Uzbekistan) or Middle East & North Africa (e.g., Qatar, Saudi Arabia) differ in their reserve strategies, potentially reflecting geopolitical priorities.
• Data Visualisation: Create maps, bar charts, or scatter plots to visualise global gold reserves, regional differences, or the correlation between income levels and gold holdings. Notes for Users
• Missing Data: Some countries have "AWAITED" in place of numerical values for FX reserves, total reserves, gold reserves, and holdings percentages. Users may need to handle these missing values (e.g., by excluding them, imputing values, or sourcing additional data).
• Gold Valuation: The "Gold Reserves Millions" column reflects the value of gold reserves in USD, based on the gold price as of 2024. Users should note that gold prices fluctuate, and historical comparisons may require adjustment for price changes.
• 20-Year Change: The "20yr change" column provides the change in gold holdings in tonnes from 2005 to 2025. Negative values indicate a reduction in gold reserves (e.g., Switzerland reduced by 314.35 tonnes), while positive values indicate an increase (e.g., India increased by 521.31 tonnes).