Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2024 about family, median, income, real, and USA.

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2024 about personal income, personal, median, income, real, and USA.

In 2024 the median annual income of Asian households in the United States was 121,700 U.S. dollars. They were followed by White households, who's median earnings were 92,530 U.S. dollars. Furthermore, Black Americans and American Indian and Alaska Native families had the lowest household incomes. That year, median income among all U.S. household rose to 83,730 U.S. dollars.

The dissolution of the Soviet Union saw a drastic fall in income rates across the region. In 1950, after the economic recovery period that followed the Second World War, income per capita in the Soviet Union was around half of Western Europe's rate. These figures did increase in the subsequent decades, before falling throughout the 1970s and 1980s, yet, in the final years of the communist system in Europe, income per capita was still around half of Western Europe's rate (albeit slightly lower than in1950).

By 2000, however, these figures had dropped below a quarter of Western Europe's income per capita. Most of this downturn occurred before 1996, and the economic situation in Russia, Ukraine, and the Baltic states began to improve in the final years of the century. It would take another few years before the economic situation of the other former-Soviet states would also begin to stabilize.

In 1900, GDP per capita in Southern Europe was just over half of the rate in Western Europe, while it was just 39 percent across Central and Eastern Europe. By 1950, Central and Eastern Europe's GDP per capita had risen to 51 percent of Western Europe's, while Southern Europe's GDP per capita had fallen to 44 percent. Post-war recovery across the south was comparatively slower than the West due to the lack of American investment in the fascist states of Spain and Portugal, the civil war in Greece, and the lack of industrialization in Italy. As these factors reversed or concluded in the 1950s, Southern Europe's economic development fell more in line with that of the rest of Western Europe in this decade, with Italy, in particular, emerging as one of the world's leading economies.

In 2023, the usual median hourly rate of a worker's wage in the United States was 19.24 U.S. dollars, a decrease from the previous year. Dollar value is based on 2023 U.S. dollars. In 1979, the median hourly earnings in the U.S. was 17.48 dollars.

Aim of the study is to render the income distribution and income stratification in the Federal Republic of Germany (FRG) form 1950 to 1970.

Topics: Tabulations in Online-Database HISTAT (Historical Statistics):

A. Synopses A.01 Sources of liquid income in percent (1950-1970) A.02 Personal income distribution in percent (1950-1970) A.03 Distribution of household-income in percent (1950-1970) A.04 Average income per household on social position of head of the household, Index (1950-1970) A.05 Distribution of private households on incomg-groups (1950-1970) A.06 Distribution of private households on size of household and incomg-group (1950-1970) A.07 Average yearly income per household in DM (1950-1970) A.08 Distribution of private households on number of persons receiving income and on income groups (1950-1970)

B. Development of functional and personal income B.01a Private households on household size and social position of head of the household in FRG in thousand (1950-1970) B.01b Private households on social position of head of the household and on income-receive in FRG in thousand (1950-1970) B.02 Development of household income in FRG in billions DM (1950-1970) B.03a Net-total income of the entire private households in the FRG im billions DM (1950-1970) B.03b Net-average income of the entire privat households in the FRG in DM (1950-1970)

C. Number of Net-income of private households C.01a Number of net-income of the entire private households in the FRG on income groups (1950-1970) C.01b Number of net-income of Self-Employed households in the FRG on income groups (1950-1970) C.01c Number of net-income of white-collar worker households in the FRG on income groups (1950-1970) C.01d Number of net-income of blue-collar worker households in the FRG on income groups (1950-1970) C.01e Number of net-income of retiree households in the FRG on income groups (1950-1970) C.02 Number of Households in the FRG on constant income groups in thousand (1950-1970) C.03 Net-annuity of housholds in the FRG on constant income groups in billions DM (1950-1970)

Z. Compendious statistical value schedules (1950-1985) Z.01 Statistical values of stratification of private household´s net-annuity and of families´ net-annuity on social groups (1950-1985) Z.02 Average monthly household income on social groups (1950-1974)

About this dataset

Context

The dataset illustrates the median household income in Goodland, 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 Goodland increased by $1,950 (3.75%), 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 5 years and declined for 8 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 Goodland median household income. You can refer the same here

About this dataset

Context

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

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 151(3.17%) households where the householder is under 25 years old, 1,021(21.46%) households with a householder aged between 25 and 44 years, 1,950(40.99%) households with a householder aged between 45 and 64 years, and 1,635(34.37%) households where the householder is over 65 years old.
• In Lewis County, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

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

Income brackets:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

About this dataset

Context

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

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 49(0.69%) households where the householder is under 25 years old, 1,950(27.51%) households with a householder aged between 25 and 44 years, 2,629(37.09%) households with a householder aged between 45 and 64 years, and 2,460(34.71%) households where the householder is over 65 years old.
• In Laconia, the age group of 45 to 64 years stands out with both the highest median income and the maximum share of households. This alignment suggests a financially stable demographic, indicating an established community with stable careers and higher incomes.

Content

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

Income brackets:

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

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

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

For Western Europe's economies in the late twentieth century, there were regional differences in the development of GDP per capita in many of the northern, industrialized nations and those in the south and on the northern periphery. In 1950, GDP per capita was lower than the regional average in these countries due to the lower levels of industrialization. The south then managed to make up a lot of ground by 1973. During Western Europe's "Golden Age of Capitalism," however, Ireland actually lost ground on the rest of the region due to its isolationist policies and inability to industrialize at the same pace. The last quarter-century of the decade saw this trend reverse, with Ireland's GDP per capita eventually growing above the regional average due to the influx of U.S. investment and its increased integration with European markets. Finland, which had a fairly unique position as being a West Bloc country within the Soviet sphere of influence, did experience some economic success during the Cold War through its exports into the East Bloc. The dissolution of the Soviet Union saw Finland rapidly restructure its economy to compete with the west, which caused GDP to fall by 14 percent between 1989 and 1993. By the end of the decade, however, this transition saw Finland emerge as a global leader in the export of high-tech goods, and income surpassed Swedish figures. By 2004, Ireland and Finland were respectively ranked as the top two leading nations in high-tech manufacturing by the OECD.

Graph and download economic data for Real Median Household Income in Michigan (MEHOINUSMIA672N) from 1984 to 2024 about MI, households, median, income, real, and USA.

Context

This dataset provides comprehensive global demographic and socioeconomic indicators for each country, compiled for the year 2024. It includes data on population sizes, growth rates, fertility rates, migration, urbanization, and other critical factors that influence global social and economic trends.

Key Features:

Country Name: The name of each country or region included in the dataset.

Population (2024): Estimated total population of each country for the year 2024, measured in millions or billions.

Population Growth Rate: The annual percentage change in population from one year to the next. It highlights whether the population is growing or declining.

Urbanization Percentage: The proportion of the population living in urban areas, indicating trends in urban migration and the shift from rural to urban living.

Fertility Rate: The average number of children born per woman of childbearing age, a key indicator of population reproduction levels.

Median Age: The median age of the population, reflecting the age distribution and helping to assess population aging or youthfulness.

Life Expectancy at Birth: The average number of years a newborn is expected to live, assuming current mortality rates persist.

Infant Mortality Rate: The number of deaths of infants under one year of age per 1,000 live births, a key indicator of healthcare quality and access.

GDP (Gross Domestic Product): The total monetary or market value of all the goods and services produced within a country’s borders in a given time period (usually measured annually in USD).

GDP per Capita: GDP divided by the total population, reflecting the average economic output per person and serving as a measure of the average income or economic standard of living.

Human Development Index (HDI): A composite index that considers life expectancy, education, and income per capita to provide an overall measure of human development.

Applications of the Dataset: Policy and Development Analysis: Governments, international organizations, and think tanks can use this data to craft development policies, allocate resources, and address issues such as urbanization, aging populations, and fertility rates.

Economic Forecasting and Analysis: Economists and financial institutions can leverage this data for macroeconomic analysis, forecasting, and investment decisions, especially using indicators like GDP, GDP per capita, and HDI.

Social and Health Research: Public health organizations can track health indicators like life expectancy, infant mortality rates, and fertility rates to guide public health interventions and strategies.

Education and Demography: Educators and researchers in the fields of demography, sociology, and global studies can use this dataset to analyze population trends, migration patterns, and social changes across the globe.

Sources of Data:

The data is sourced from reputable international organizations including the United Nations, the World Bank, the World Health Organization (WHO), the International Monetary Fund (IMF), and other national statistical agencies.

Data Use & Limitations:

Use: This dataset is intended for general research, educational, and analytical purposes. It provides a snapshot of global demographic trends and socioeconomic conditions as of 2024. Limitations: While the data is collected from reliable sources, estimates for certain countries may vary slightly due to differing methods of data collection or reporting across regions. Additionally, as some countries may not have updated data for 2024, projections or estimates have been used where necessary.

This data selection represents a thematic extract from the comprehensive study “The Growth of the German Economy since the mid-19th Century“ (“Das Wachstum der deutschen Wirtschaft seit der Mitte des 19. Jahrhunderts”) from 1965 by Walter G. Hoffmann. The main objective of Hoffmann’s study is to work out statistical figures concerning the long-term development of the German national economy, as well as the individual fields of this subject area. In doing so, the time series shall enable the verification of various hypotheses concerning economic growth. This aim, however, can only be reached if such time series are based on comparable statistical, methodical, and content-related concepts, and if they are collected for a period with maximum length. Consequently, this data selection comprises more than 800 pages with 250 tables, featuring almost every time series between 1850 and 1960 that can be considered relevant for the economic development. Whenever necessary, these materials were completed by estimates. Moreover, the above-named analyses of long-term tendencies aim at creating a reference system for the numerous short-term changes occuring within most national economies in the course of a century.Here the special focus of Hoffman’s work lies on the visualisation of the gained materials as regards the raise, distribution, and use of the national income. The respective calculation is based on the two production factors of labour and capital and culminates in an overview of production. The calculation of the distribution, on the other hand, deals with the functional and individual, i.e. personal distribution of (earned and capital) income. In its turn, the calculation of use is divided into the sectors of private and public consumption, investment, and the national trade balance. Topics Timeseries data available via the downloadsystem HISTAT Data excerpt: earned income and capital income(income compilation, the following factors have been taken into consideration): - average yearly earned income in mining and salt-mines (1850-1959).- average yearly earned income in industry and handicraft (1850-1959).- average yearly earned income in traffic system without German Federal Railways, German Federal Mail, and shipping (1950-1959).- average yearly earned income in traffic system (1850-1959).- average yearly earned income in trade, banks, insurances, and hotel and catering industry (1925-1939).- average yearly earned income in trade, banks, insurances, and hotel and catering industry (1950-1960).- average yearly earned income of employed in the public service (1851-1913).- average yearly earned income in the public service (1925-1950).- average yearly earned income in other services (1850-1959).- average yearly earned income by economic sectores (1850-1959).- earned income by economic sectores (1850-1959).- rate of return of the industrial sector´s stock corporations (1926-1959).- distribution of net social product in factor costs in current prices (1850 – 1959).

Graph and download economic data for Personal income per capita (A792RC0A052NBEA) from 1929 to 2024 about personal income, per capita, personal, income, GDP, and USA.

The Data-compilation is a selection of time-series on wage- and salary development as well as on the development of the national income in Germany from 1850 to 1985. The following studies has been included: - Walther G. Hoffmann (1965): Das Wachstum der deutschen Wirtschaft seit der Mitte des 19. Jahrhunderts.- Rüdiger Hohls (1991): Arbeit und Verdienst. Entwicklung und Struktur der Arbeitseinkommen im Deutschen Reich und in der Bundesrepublik.- Pierenkemper, Toni (1987): Arbeitsmarkt und Angestellte im deutschen Kaiserreich 1880-1913. Interessen und Strategien als Elemente der Integration eines segmentierten Arbeitsmarktes.- Wiegand, Erich/Zapf, Wolfgang (1982): Wandel der Lebensbedingungen in Deutschland. Wohlfahrtsentwicklung seit der Industrialisierung. Tables in ZA-Online-Database HISTAT: A. Hoffmann, Walther G.: The Growth of the German Economy since the mid of the 19th centuryA.1 The average earned income per annum by industrial sector (1850-1959)A.2 The average earned income per annum in mining and saline (1850-1959)A.3 The average earned income per annum in industry and craft (1850-1959)A.4 The average earned income per annum in transport (1850-1959)A.5 The average earned income per annum in other services (1850-1959)A.6 Net national product (NNP) in factor costs in current prices and national income per capita according to Hoffmann (1850-1959)A.7 Gross value added and real national income per capita in prices of 1913 according to Hoffmann (1850-1959)A.8 The development of average earned income of employees in industry and craft, Index 1913 = 100 (1850-1959) B. Hohls, Rüdiger: The Sectoral Structure of Earnings in GermanyB.1 Nominal annual earnings of employees by industrial sector in Germany in Mark, 1885-1985B.2 Nominal earnings of white collar workers and blue collar workers in Germany, 1890-1940 C. Living costs, prices and earnings, consumer price indexC.1 Development of living costs (index) of medium employees’ households (1924-1978)C.2 Preices and earnings, index 1962 = 100 (1820-2001)C.3 Living costs, consumer price index (1820-2001) D. Pierenkemper, Toni: Employment market and employees in the German ‘Reich’ 1880-1913.D.1 Income of selected white collar categories in Mark (1880-1913)D.2 Real income of selected white collar categories (1880-1913) E. Wiegand, E.: Historical Development of Wages and Living Costs in Germany.E.1 Development of real gross income of blue collar workers in industry, index 1970 = 100 (1925-1978)E.2 Development of real gross income of blue collar workers in industry (1925-1978)E.3 Development of nominal and real national income per capita (1950-1978) E.4 Development of nominal and real national income per capita (1925-1939)E.5 National income: monthly income from dependent personal services per employee (1925-1971)E.6 Overlook: Development of wages, employed workers and gross income from dependent personal services in Germany (1810-1989)

This table contains 22 series, with data for years 1926 - 1960 (not all combinations necessarily have data for all years), and was last released on 2000-02-18. This table contains data described by the following dimensions (Not all combinations are available): Geography (11 items: Canada; Newfoundland and Labrador; Nova Scotia; Prince Edward Island ...), Wages and salaries (2 items: Based on Standard Industrial Classification; 1948 (SIC); Based on Standard Industrial Classification; 1980 (SIC) ...).

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Avenal. The dataset can be utilized to gain insights into gender-based income distribution within the Avenal population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Avenal, among individuals aged 15 years and older with income, there were 3,462 men and 2,080 women in the workforce. Among them, 1,950 men were engaged in full-time, year-round employment, while 743 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 17.33% fell within the income range of under $24,999, while 16.96% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 2.97% of men in full-time roles earned incomes exceeding $100,000, while 7.67% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 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 $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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

Abstract copyright UK Data Service and data collection copyright owner.

The OECD Employment and Labour Market Statistics provide detailed annual information the employment and labour market for the period 1950/60 onwards for all OECD countries (where data is available).
The OECD Employment and Labour Market Statistics includes a range of annual labour market statistics and indicators broken down by sex and age as well as information about part-time and short-time workers, job tenure, hours worked, unemployment duration, trade union, employment protection legislation, minimum wages, labour market programmes for OECD countries and non-member economies.
These data were first provided by the UK Data Service in February 2015.

Main Topics:

• administrative data
• age dependency ratio
• age groups
• age structure
• agriculture
• armed force
• average salary
• average tenure s
• average wages
• births
• broad economic activities
• civil employment
• civilian labour
• collective dismissals
• constant prices
• current prices
• death rates
• dependent employment
• discouraged workers
• dismissals
• duration of unemployment
• earning-dispersion measures
• earnings
• employee density
• employee turnover
• employee union
• employees
• employment
• employment protection legislation
• employment ratio
• employment status
• exchange rate
• finance
• full-time
• full-year equivalent employee
• gender
• gross earnings
• health
• incidents
• independent workers
• industry
• Involuntary part time workers
• job tenure
• jobs
• labour
• labour force
• labour force forecasts
• labour market
• labour market fluidity
• labour market programmes
• labour regulation
• low pay incidence
• median wages
• membership
• migration rates
• minimum wages
• national legislation
• natural increase rates
• pension age
• population
• population baseline
• population estimates females
• population projections
• PPP
• professional status
• real estate
• rigidness
• salary earner ratio
• salary earners
• self-employed
• services
• short-time workers
• standardised age groups
• statistics
• strict regulation
• strictness of legislation
• survey data
• synthetic indicators
• total employment
• total increase rates
• trade union
• trade union members
• transport
• turnover rate
• unemployment
• union members
• unpaid family workers
• unpaid workers
• vital statistics
• weekly hours
• working age ratio

Per Capita Personal Income in Hawaii was 69520.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, Per Capita Personal Income in Hawaii reached a record high of 69520.00000 in January of 2024 and a record low of 1580.00000 in January of 1950. Trading Economics provides the current actual value, an historical data chart and related indicators for Per Capita Personal Income in Hawaii - last updated from the United States Federal Reserve on December of 2025.