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 the United States (MEHOINUSA646N) from 1984 to 2024 about households, median, income, and USA.

In 2025, just over 45 percent of American households had an annual income that was less than 75,000 U.S. dollars. On the other hand, some 16 percent had an annual income of 200,000 U.S. dollars or more. The median household income in the country reached almost 84,000 U.S. dollars in 2024. Income and wealth in the United States After the economic recession in 2009, income inequality in the U.S. is more prominent across many metropolitan areas. The Northeast region is regarded as one of the wealthiest in the country. Massachusetts, New Hampshire, and Maryland were among the states with the highest median household income in 2024. In terms of income by race and ethnicity, the average income of Asian households was highest, at over 120,000 U.S. dollars, while the median income among Black households was around half of that figure. What is the U.S. poverty threshold? The U.S. Census Bureau annually updates the poverty threshold based on the income of various household types. As of 2023, the threshold for a single-person household was 15,480 U.S. dollars. For a family of four, the poverty line increased to 31,200 U.S. dollars. There were an estimated 38.9 million people living in poverty across the United States in 2024, which reflects a poverty rate of 10.6 percent.

. U.S. Bureau of Labor Statistics provides Average Weekly Earnings in USD. Monthly Earnings include Private Non Agricultural sector only.


Further information about United States Monthly Earnings

• In the latest reports, US Population reached 341 million people in Dec 2024
• Unemployment Rate of US increased to 4 % in Sep 2025
• The country's Labour Force Participation Rate remained the same rate at 62 % in Sep 2025

Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2024 about personal income, personal, median, income, and USA.

Average and median market, total and after-tax income of individuals by visible minority group, Indigenous group and immigration status, Canada and provinces.

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Aug 2025 about disposable, personal income, personal, income, real, and USA.

Asian households measured the highest median household income among racial and ethnic groups in the United States. In 2024, Asian household incomes reached a median of 121,700 U.S. dollars. On the other hand, Black households had the lowest median income of 56,020 U.S. dollars. Overall, median household incomes in the United States stood at 83,730 U.S. dollars that year.Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, African American, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. nearing nine percent unemployed, according to the Bureau of Labor Statistics in 2024. Hispanic individuals (of any race) were most likely to go without health insurance as of 2024.

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.

This dataset shows the number of Mean Monthly Household Gross Income of Top 20%, Middle 40% and Bottom 40% of Households by Ethnicity 2002 - 2019, Malaysia.Source : DEPARTMENT OF STATISTICS MALAYSIA

In the United States, the median income in 2023 was at 65,540 U.S. dollars for Hispanic households. This is a large increase from 1990 when the median income was 47,600 U.S. dollars for Hispanic households (in 2023 U.S. dollars).

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

Graph and download economic data for Real Disposable Personal Income: Per Capita (A229RX0) from Jan 1959 to Aug 2025 about disposable, personal income, per capita, personal, income, real, and USA.

In the United States, the median income in 2023 was at 112,800 U.S. dollars for Asian households. This is a large increase from 2002 when the median income for Asian households was 84,770 U.S. dollars (in 2023 U.S. dollars).

In 2024, the national gross income per capita in Brazil amounted to around 9,950 U.S. dollars, an increase from 9,310 dollars per person in the previous year. Gross national income (GNI) is the aggregated sum of the value added by residents in an economy, plus net taxes (minus subsidies) and net receipts of primary income from abroad. Excluding countries and territories in the Caribbean, Uruguay and Chile were the Latin American countries with the highest national income per capita. Demographic elements and income There are many factors that may influence the income level, such as gender, academic attainment, location, ethnicity, etc. The gender pay gap, for example, is significant in Brazil. As of 2024, the monthly income per capita of men was 3,549 Brazilian reals, while the figure was 2,793 reals in the case of women. Additionally, monthly per capita household income varies greatly from state to state; the figures registered in Distrito Federal and São Paulo more than double the income of federative units like Acre, Alagoas or Maranhão. A high degree of inequality The Gini coefficient measures the degree of income inequality on a scale from 0 (total equality of incomes) to 100 (total inequality). Between 2010 and 2023, Brazil's degree of inequality in wealth distribution based on the Gini coefficient reached 52. That year, Brazil was deemed one of the most unequal countries in Latin America. Although the latest result represented one of the worst values in recent years, the Gini index is projected to improve slightly in the near future.

These Public Use Microdata Sample (PUMS) files contain records representing 1-percent samples of the occupied and vacant housing units in the United States and the people in the occupied units in 2000. Group quarters people also are included. The files contain individual weights for each person and housing unit, which when applied to the individual records, expand the sample to the relevant total. Some of the items included on the housing record are: acreage, agricultural sales, bedrooms, condominium fee, contract rent, cost of utilities, family income in 1999, farm residence, fire, hazard, and flood insurance, fuels used, gross rent, heating fuel, household income in 1999, household type, kitchen facilities, linguistic isolation, meals included in rent, mobile home costs, mortgage payment, mortgage status, plumbing facilities, presence and age of own children, presence of subfamilies in household, real estate taxes, rooms, selected monthly owner costs, size of building (units in structure), telephone service, tenure, vacancy status, value (of housing unit), vehicles available, year householder moved into unit, and year structure was built. Some of the items included on the person record are: ability to speak English, age, ancestry, citizenship, class of worker, disability status, earnings in 1999, educational attainment, grandparents as caregivers, Hispanic origin, hours worked, income in 1999 by type, industry, language spoken at home, marital status, means of transportation to work, migration Public Use Microdata Area (PUMA), migration state, mobility status, veteran period of service, years of military service, occupation, personal care limitation, place of birth, place of work PUMA, place of work state, poverty status in 1999, race, relationship, school enrollment and type of school, time of departure for work, travel time to work, vehicle occupancy, weeks worked in 1999, work limitation status, work status in 1999, and year of entry. The Public Use Microdata Sample (PUMS) files contain geographic units known as super-Public Use Microdata Areas (super-PUMAs) and Public Use Microdata Areas (PUMAs). To maintain the confidentiality of the PUMS data, minimum population thresholds are set for PUMAs and super-PUMAs. For the 1-percent state-level files, the super-PUMAs contain a minimum population of 400,000 and are composed of a PUMA or a group of contiguous PUMAs delineated on the 5-percent state-level PUMS files. Super-PUMAs are a new geographic entity for Census 2000. Super-PUMAs and PUMAs also are defined for place of residence on April 1, 1995, and place of work.

Abstract

The 2005/6 Household Income and Expenditure Survey is the second nationwide survey of households undertaken by Solomon Islands Statistics Office (SISO) since 1992.

The primary objectives of the HIES includes: • Re-basing of the weights of the current basket of goods and services in the Consumer Price Index (CPI). The survey also aimed to provide data on the behavior of household consumption expenditure patterns that will help form the weights that would reflect the relative importance that consumers attach to commodities and services; • Obtaining relevant data for purposes of updating the series of national accounts aggregates particularly the Gross Domestic Product.

The secondary objectives of the HIES were to: • Obtain data on housing and general demographic characteristics of households; • Obtain data on poverty measures, income and income inequality measures; • Obtain relevant data for the Millennium Development Goals (MDG), particularly health and education; and • Obtain other relevant data where necessary

The field data collecting exercise was undertaken from October 2005 to March 2006 and that seasonality effects on expenditure was not fully considered.

Geographic coverage

National. The HIES operation covered both the Urban and Rural areas focusing on Honiara, Other Urban Areas and the Rural Areas of the ten (9) provinces, and aimed to produce estimates at the country national and provincial levels only.

Analysis unit

• Households
• Individuals

Universe

The survey targeted private households whilst collective households in hospital, hotels, prison and educational institutions were excluded. A household is considered in the scope for the survey if the household have resided in the Solomon Islands for the last 12 months or more, or if not, they intend to live in Solomon Islands for the next 12 months.

Kind of data

Sample survey data [ssd]

Sampling procedure

Survey Design The survey was based on a two-stage sampling strategy using probability proportional to size (PPS) selection and random selection. The strategy for selection of each area type is slightly different depending also on enumerator workload schedule and the need to accommodate estimates at the National and Provincial level as well as Urban and Rural splits.

The Survey was designed to collect data for national and provincial level estimates and covered both urban and rural areas. The survey covered Honiara, provincial centers and rural areas within these provinces.

The sampling scheme used was a stratified two stage design with the Enumeration Areas (EA) as the Primary Sampling Unit (PSU) and the households within the sample areas as the secondary sampling unit (SSU). In the first stage the EAs were selected with probability proportional to their population size based on the 1999 population census. In the second stage households were selected using systematic sampling with a random start. The next stage was allocating the sample to each provinces proportional to the square-root of the population. This should mean that estimates of each province would roughly have the same level of accuracy. The sample was then split for each province between the provincial centers (considered to be urban) and the remaining rural population. Given the need for urban and rural estimates the sample was split between the two areas proportional to the square-root of the population based on the 1999 census. The last stage in the process involved modifying the final counts to accommodate the workloads for interviewers during the fieldwork. The interviewers were expected in the field for six months and could accommodate 10 households per month (60 household in total). It was desirable to have the total workloads for each province divisible by 60 to give each interviewer an even sized workload and have the sample spread out evenly across each month.

Since Honiara (capital of Solomon Islands) consists of a mix of areas which covers high income, middle income and low income areas, it was advisable that the EAs be grouped based on the class best suited to their situation. Thus for Honiara the EA list was sorted by the income group category for selection. The number of EAs to select from Honiara is simply the desirable sample size (480 households) divided by the number of households to be selected for each EA. It was decided that 10 households should be selected from each selected EA. Therefore the number of EAs that were selected was equivalent to (480 / 10) = 48 EAs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HIES is a relatively complex survey and the instruments to collect data was implemented through the following questionnaires and associated sections: • Household Control Form – household composition and particulars; • Household Expenditure Form – housing amenities, facilities and major household, expenditure on tenure, fixed capital, land, property etc; • Personal Income Form – Income pattern of household members and other income earning activities; • Household Dairy – Daily expenditure by type of goods and services • An additional health module was included – health facility utilization, immunization, motherhood, mortality, breast feeding & family planning, Malaria and miscellaneous

Cleaning operations

The Statistics Programme at the Secretariat of the Pacific Community (SPC) provided the assistance in data processing. A HIES data entry program was setup in CSPro version 2.6 and data entry started soon after the first workload was registered in the Statistics Office in November 2005 until May 2006. Logic procedures for data editing are prepared in Microsoft Access and data editing for all questionnaires were done in CSPro, except for the Diary where the editing is done in Microsoft Excel. Data management queries are done in Microsoft Access and the production of tables was done in Microsoft Excel. This report was prepared in Microsoft Word. Data verification of 5 per cent is done to check the accuracy of data input, though data edit checks are carried out for completeness, consistency and accuracy including the outliers. Anomalies of data were amended appropriately.

Response rate

Response Rates A sample of 4,320 households was planned for the country and about 3,822 households (88.5%) responded favorably satisfying the survey requirements.

Non-Response Despite efforts made by the enumerators and follow up attempts by the supervisors in most of the cases, there was non-response encountered during the survey.

The reasons for non response by the household were due mainly to the following: • The household was out of scope of the survey • Dwelling was vacant or not being lived in • The household could not be contacted after a number of attempts • Household excluded for other reasons like death in the family, refusals, customary reasons etc

Sampling error estimates

Error Measurements No formal measures of sample errors have been calculated for the survey results.

Non sampling errors cannot be readily measured. These included: o A response difficulty caused by misunderstanding of what was required from the survey and survey instruments by both households and interviewers. o The questionnaires were in English, which is at least a second language for interviewers and respondents. o The fact that some expenditure are seasonal and would not have been picked up in the survey period. o The exclusion of remote areas and institutions from the sampling frame.

These Public Use Microdata Sample (PUMS) files contain records representing a 5-percent sample of the occupied and vacant housing units in the United States and the people in the occupied units. People living in group quarters also are included. The files provide individual weights for persons and housing units, which when applied to the individual records, expand the sample to the relevant totals. Some of the items on the housing record are acreage, agricultural sales, allocation flags for housing items, bedrooms, condominium fee, contract rent, cost of utilities, family income in 1999, family, subfamily, and relationship recodes, farm residence, fire, hazard, and flood insurance, fuels used, gross rent, heating fuel, household income in 1999, household type, housing unit weight, kitchen facilities, linguistic isolation, meals included in rent, mobile home costs, mortgage payment, mortgage status, plumbing facilities, presence and age of own children, presence of subfamilies in household, real estate taxes, number of rooms, selected monthly owner costs, size of building (units in structure), state code, telephone service, tenure, vacancy status, value (of housing unit), vehicles available, year householder moved into unit, and year structure built. Some of the items on the person record are ability to speak English, age, allocation flags for population items, ancestry, citizenship, class of worker, disability status, earnings in 1999, educational attainment, grandparents as caregivers, Hispanic origin, hours worked, income in 1999 by type, industry, language spoken at home, marital status, means of transportation to work, migration Public Use Microdata Area (PUMA), migration state, mobility status, veteran period of service, years of military service, occupation, persons weight, personal care limitation, place of birth, place of work PUMA, place of work state, poverty status in 1999, race, relationship, school enrollment and type of school, time of departure for work, travel time to work, vehicle occupancy, weeks worked in 1999, work limitation status, work status in 1999, and year of entry. The Public Use Microdata Sample (PUMS) files contain geographic units known as Public Use Microdata Areas (PUMAs) and super-Public Use Microdata Areas (super-PUMAs). To maintain the confidentiality of the PUMS data, minimum population thresholds are set for PUMAs and super-PUMAs. For the 1-percent state-level files, the super-PUMAs contain a minimum population of 400,000 and are composed of a PUMA or a group of contiguous PUMAs delineated on the 5-percent state-level PUMS files. Super-PUMAs are a new geographic entity for Census 2000. The 5-percent state-level files contain PUMAs, each having a minimum population of 100,000, and corresponding super-PUMA codes. Each state is separately identified and may be comprised of one or more super-PUMAs or PUMAs. Large metropolitan areas may be subdivided into super-PUMAs and PUMAs. PUMAs and super-PUMAs do not cross state lines. Super-PUMAs and PUMAs also are defined for place of residence on April 1, 1995, and place of work.

In 2024, the average annual per capita disposable income of households in China amounted to approximately 41,300 yuan. Annual per capita income in Chinese saw a significant rise over the last decades and is still rising at a high pace. During the last ten years, per capita disposable income roughly doubled in China. Income distribution in China As an emerging economy, China faces a large number of development challenges, one of the most pressing issues being income inequality. The income gap between rural and urban areas has been stirring social unrest in China and poses a serious threat to the dogma of a “harmonious society” proclaimed by the communist party. In contrast to the disposable income of urban households, which reached around 54,200 yuan in 2024, that of rural households only amounted to around 23,100 yuan. Coinciding with the urban-rural income gap, income disparities between coastal and western regions in China have become apparent. As of 2023, households in Shanghai and Beijing displayed the highest average annual income of around 84,800 and 81,900 yuan respectively, followed by Zhejiang province with 63,800 yuan. Gansu, a province located in the West of China, had the lowest average annual per capita household income in China with merely 25,000 yuan. Income inequality in China The Gini coefficient is the most commonly used measure of income inequality. For China, the official Gini coefficient also indicates the astonishing inequality of income distribution in the country. Although the Gini coefficient has dropped from its high in 2008 at 49.1 points, it still ranged at a score of 46.5 points in 2023. The United Nations have set an index value of 40 as a warning level for serious inequality in a society.