This data collection provides selected economic, social, demographic, and political information for 48 states of the United States during the 1950s and 1960s. Variables describe population characteristics, such as the number of adults aged 65 and over, the number of dentists and physicians, the number of patients in mental hospitals, the death rates of white and non-white infants under one year of age per 1,000 live births, respectively, the number of recipients of public assistance such as Aid to Families with Dependent Children (AFDC), elementary and secondary school enrollment, enrollment in vocational programs, the total number of students in higher education, the number of those conferred with M.A. and Ph.D. degrees, and the number of workers in research experiment stations. Other variables provide economic information, such as personal income per capita, average monthly payment per recipient of some public assistance programs, average salary per month for full-time state and local employees, state and local government revenues and expenditures, and various intergovernmental revenues from the federal government for certain services. Additional variables record crime statistics, such as the number of robbery, burglary, larceny, auto theft, assault, rape, and murder offenses per 100,000 of the population. There are also variables that give information on each state's topography, such as the acreage of state parks, total farm acreage, municipal road mileage, and total unsurfaced road mileage.

Graph and download economic data for Real Median Family Income in the United States (MEFAINUSA672N) from 1953 to 2023 about family, median, income, real, and USA.

This statistic represents the hourly earnings in the U.S. manufacturing sector between May 2006 and May 2021. On average, employees in the manufacturing sector in the United States had hourly earnings of ***** U.S. dollars in May 2021.

In 2022, it was estimated that the CEO-to-worker compensation ratio was 344.3 in the United States. This indicates that, on average, CEOs received more than 344 times the annual average salary of production and nonsupervisory workers in the key industry of their firm.

Mexico Minimum Wage: Daily: Weighted Average of the 3 Geographic Area data was reported at 102.680 MXN in Mar 2019. This stayed constant from the previous number of 102.680 MXN for Feb 2019. Mexico Minimum Wage: Daily: Weighted Average of the 3 Geographic Area data is updated monthly, averaging 10.787 MXN from Jan 1964 (Median) to Mar 2019, with 663 observations. The data reached an all-time high of 102.680 MXN in Mar 2019 and a record low of 0.018 MXN in Dec 1965. Mexico Minimum Wage: Daily: Weighted Average of the 3 Geographic Area data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.G040: Minimum Wage and Wage Index.

The study constructs new series of nominal wages in industry and crafts as well as a new consumer goods price index for the period 1850-1889; the coefficient of the two series gives the real wage. While such information was collected and published by government agencies from the late 1880s onwards, the decades before are part of the pre-statistical age. After all, information is available from municipal authorities, from branches of territorial state authorities and from individual companies. For the construction of a new nominal wage series, the current study refer to Kuczynski´s material (1961/62), supplements it with information from individual studies of the past 50 years, and constructs wage indices for the heavy ironware, machine construction, mining, printing, and municipal construction industries on this basis by means of unbalanced panel regression with fixed effects. Of the 38 individual wage series on which these sector indices are based, 27 come from Kuczynski, the remainder from more recent studies. Wages in the textile sector are represented by those in the cotton industry. The study uses the wage series published by Kirchhain (1977). Weighted according to employment figures, all these sector-specific series (excluding miners´ wages) are aggregated into a Fisher index of nominal wages in industry and crafts. Both this index and the indices at sector level are linked in 1888/89 with the series by Hoffmann (1965); the resulting values denote annual earnings in Marks. The sector indices differ little from those of Kuczynski and Hoffmann despite the expansion of the database and the different methodology of index construction, but the aggregated index shows a stronger growth rate than that of Kuczynski; the latter index is obviously erroneous (Pfister 2018, 576). The consumer goods price index is based on five sub-indices for (1) food, (2) beverages and luxury foods, (3) rent, (4) furniture, household goods and heating, and (5) clothing. The sub-indices for food and rent are new, the other three are from Hoffmann (1965). Weights are determined for 1848/49 and 1889 on the basis of research literature, values in between are interpolated linearly. Both the sub-index of food prices and the overall index are constructed as Fisher indices. Both the rental index and the food prices rise more strongly in the long term than the two corresponding Hoffmann indices (Pfister 2018, 578 and 582). Hoffmann constructs the rental price index only indirectly by multiplying the estimated building capital by an assumed interest rate. The rent index of the current study is based on data from three major cities. Only if it is assumed that large cities are completely unrepresentative for the entire real estate market should Hoffmann´s series still be considered. In the case of food prices, the comparatively stronger long-term increase - compared to previous research - results from the higher weight of prices from the southern parts of the country far from the sea in the new sub-index. Here, the price dampening effect of growing imports of American grain had a weaker effect than in the coastal regions in the north. Thus, one of the main findings of the study is that the assessment of the development of the living standards of urban workers from the 1850s to 1880s strongly depends on how one determines the effect of the first wave of modern globalization on the German price structure. The greater consideration given in this study to food prices in areas distant from the sea results in a more pessimistic view of the development of real wages during this period than has been the case with some previous research. To the data: 1. individual wage series (table set A.01) This set of tables contains wage series from six branches at the level of regions, cities, individual enterprises and in one case (cotton industry) an entire branch. Only series containing data for at least 15 years were taken into account. In detail, the series are the following:Heavy IronwareBochum 1869-1889: Average annual income of the workers of the Bochumer Verein (steelworks) in Mark; Däbritz (1934, Annex Table 4).Essen 1848-1889: Average annual income of the workers of the Krupp works in Mark; Kuczynksi (1961-62, vol. I, 377, vol. II, 227, vol. III, 426).Ruhr 1855-1889: Average annual income of the workers at the blast furnaces in the Ruhr district in Mark; banks (2000, Table A59).Saar 1869-1889: Day wage of workers at the blast furnaces of the Burbach Ironworks in Mark; Kuczynksi (1961-62, vol. III, 426).Silesia 1869-1889: Average annual income of workers at the blast furnaces in Silesia in Mark; banks (2000, Table A59). Machine constructionAugsburg 1851-1889: Average annual income of the workers of the Machine Factory Augsburg in Mark; Vol. II, 227; Kuczynski (1961-62, Vol. III, 426).Chemnitz 1860-1887: Weekly wage of machinists in Mark; Kuczynski (1961-62, vol. II, 227; vol. III, 426).Esslingen 1848-1889: Average annual income of workers at the Ess...

Canada Minimum Wage data was reported at 16.380 CAD in 2024. This records an increase from the previous number of 15.450 CAD for 2023. Canada Minimum Wage data is updated yearly, averaging 5.701 CAD from Dec 1965 (Median) to 2024, with 60 observations. The data reached an all-time high of 16.380 CAD in 2024 and a record low of 0.917 CAD in 1965. Canada Minimum Wage data remains active status in CEIC and is reported by Employment and Social Development Canada. The data is categorized under Global Database’s Canada – Table CA.G043: Minimum Wage. In Canada, every province and territory provides for a minimum wage in its employment standards legislation, and therefore may vary from one province to another. A value for the hourly minimum wage for Canada is the average of provincial hourly minimum wages.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Sistersville, WV, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 1,965, while the mean income for the highest quintile (20% of households with the highest income) is 134,113. This indicates that the top earners earn 68 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 203,574, which is 151.79% higher compared to the highest quintile, and 10360% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 Sistersville median household income. You can refer the same here

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)

Indonesia National Income: SNA 1960: 1960 Series data was reported at 5,592.300 IDR bn in 1973. This records an increase from the previous number of 3,856.500 IDR bn for 1972. Indonesia National Income: SNA 1960: 1960 Series data is updated yearly, averaging 2,619.550 IDR bn from Dec 1960 (Median) to 1973, with 14 observations. The data reached an all-time high of 21,562.000 IDR bn in 1965 and a record low of 286.200 IDR bn in 1966. Indonesia National Income: SNA 1960: 1960 Series data remains active status in CEIC and is reported by Statistics Indonesia. The data is categorized under Global Database’s Indonesia – Table ID.AC001: Gross National Product: Current Price.

United States Avg Hourly Earnings: sa: PW: 1982-84p: Information data was reported at 12.980 USD in Jun 2018. This records an increase from the previous number of 12.900 USD for May 2018. United States Avg Hourly Earnings: sa: PW: 1982-84p: Information data is updated monthly, averaging 11.755 USD from Jan 1964 (Median) to Jun 2018, with 654 observations. The data reached an all-time high of 14.130 USD in Aug 1965 and a record low of 10.240 USD in Dec 1991. United States Avg Hourly Earnings: sa: PW: 1982-84p: Information data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G034: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Production Workers.

Canada Minimum Wage: New Brunswick data was reported at 15.300 CAD in 2024. This records an increase from the previous number of 14.750 CAD for 2023. Canada Minimum Wage: New Brunswick data is updated yearly, averaging 5.000 CAD from Dec 1965 (Median) to 2024, with 60 observations. The data reached an all-time high of 15.300 CAD in 2024 and a record low of 0.800 CAD in 1965. Canada Minimum Wage: New Brunswick data remains active status in CEIC and is reported by Employment and Social Development Canada. The data is categorized under Global Database’s Canada – Table CA.G043: Minimum Wage.

The Gross Domestic Product per capita in El Salvador was last recorded at 4585.23 US dollars in 2024. The GDP per Capita in El Salvador is equivalent to 36 percent of the world's average. This dataset provides - El Salvador GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides information about earnings of employees who are working in an area, who are on adult rates and whose pay for the survey pay-period was not affected by absence. Tables provided here include total gross weekly earnings, and full time weekly earnings with breakdowns by gender, and annual median, mean and lower quartile earnings by borough and UK region. These are provided both in nominal and real terms. Real earnings figures are on sheets labelled "real", are in 2016 prices, and calculated by applying ONS’s annual CPI index series for April to ASHE data. Annual Survey of Hours and Earnings (ASHE) is based on a sample of employee jobs taken from HM Revenue & Customs PAYE records. Information on earnings and hours is obtained in confidence from employers. ASHE does not cover the self-employed nor does it cover employees not paid during the reference period. The earnings information presented relates to gross pay before tax, National Insurance or other deductions, and excludes payments in kind. The confidence figure is the coefficient of variation (CV) of that estimate. The CV is the ratio of the standard error of an estimate to the estimate itself and is expressed as a percentage. The smaller the coefficient of variation the greater the accuracy of the estimate. The true value is likely to lie within +/- twice the CV. Results for 2003 and earlier exclude supplementary surveys. In 2006 there were a number of methodological changes made. For further details goto : http://www.nomisweb.co.uk/articles/341.aspx. The headline statistics for ASHE are based on the median rather than the mean. The median is the value below which 50 per cent of employees fall. It is ONS's preferred measure of average earnings as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings. It therefore gives a better indication of typical pay than the mean. Survey data from a sample frame, use caution if using for performance measurement and trend analysis '#' These figures are suppressed as statistically unreliable. ! Estimate and confidence interval not available since the group sample size is zero or disclosive (0-2). Furthermore, data from Abstract of Regional Statistics, New Earnings Survey and ASHE have been combined to create long run historical series of full-time weekly earnings data for London and Great Britain, stretching back to 1965, and is broken down by sex.

This dataset provides information about earnings of employees who are working in an area, who are on adult rates and whose pay for the survey pay-period was not affected by absence.

Tables provided here include total gross weekly earnings, and full time weekly earnings with breakdowns by gender, and annual median, mean and lower quartile earnings by borough and UK region. These are provided both in nominal and real terms.

Real earnings figures are on sheets labelled "real", are in 2016 prices, and calculated by applying ONS’s annual CPI index series for April to ASHE data.

Annual Survey of Hours and Earnings (ASHE) is based on a sample of employee jobs taken from HM Revenue & Customs PAYE records. Information on earnings and hours is obtained in confidence from employers. ASHE does not cover the self-employed nor does it cover employees not paid during the reference period.

The earnings information presented relates to gross pay before tax, National Insurance or other deductions, and excludes payments in kind.

The confidence figure is the coefficient of variation (CV) of that estimate. The CV is the ratio of the standard error of an estimate to the estimate itself and is expressed as a percentage. The smaller the coefficient of variation the greater the accuracy of the estimate. The true value is likely to lie within +/- twice the CV.

Results for 2003 and earlier exclude supplementary surveys. In 2006 there were a number of methodological changes made. For further details goto : http://www.nomisweb.co.uk/articles/341.aspx.
The headline statistics for ASHE are based on the median rather than the mean. The median is the value below which 50 per cent of employees fall. It is ONS's preferred measure of average earnings as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings. It therefore gives a better indication of typical pay than the mean.

Survey data from a sample frame, use caution if using for performance measurement and trend analysis
'#' These figures are suppressed as statistically unreliable.
! Estimate and confidence interval not available since the group sample size is zero or disclosive (0-2).

Furthermore, data from Abstract of Regional Statistics, New Earnings Survey and ASHE have been combined to create long run historical series of full-time weekly earnings data for London and Great Britain, stretching back to 1965, and is broken down by sex.

Kuwait KW: GDP: USD: Gross National Income data was reported at 139.107 USD bn in 2017. This records an increase from the previous number of 124.179 USD bn for 2016. Kuwait KW: GDP: USD: Gross National Income data is updated yearly, averaging 28.017 USD bn from Dec 1965 (Median) to 2017, with 53 observations. The data reached an all-time high of 187.416 USD bn in 2013 and a record low of 1.655 USD bn in 1965. Kuwait KW: GDP: USD: Gross National Income data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kuwait – Table KW.World Bank: Gross Domestic Product: Nominal. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total;

United States Avg Weekly Earnings: sa: PW: 1982-84p: Information data was reported at 461.910 USD in Jun 2018. This records an increase from the previous number of 459.360 USD for May 2018. United States Avg Weekly Earnings: sa: PW: 1982-84p: Information data is updated monthly, averaging 428.500 USD from Jan 1964 (Median) to Jun 2018, with 654 observations. The data reached an all-time high of 542.480 USD in Mar 1965 and a record low of 365.150 USD in Jan 1992. United States Avg Weekly Earnings: sa: PW: 1982-84p: Information data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.G034: Current Employment Statistics Survey: Average Weekly and Hourly Earnings: Production Workers.

In this studiy a compilation of the average earnings growth rates since 1850 on the basis of different sources is given:the yearly growth-rates of average work-income from 1850 to 1951 (according to Walther G. Hoffmann), the growth rate of average gross compensation, growth rate of gross hourly earnings of industrial workers,growth rate of gross earnings ( according to D. Schewe/K. Nordhorn, H.J. Müller und R. Skiba). Topics Timeseries available via the downloadsystem HISTAT: A.1 Die Wachstumsrate der Lohneinkommen im Deutschen Reich und in der Bundesrepublik Deutschland (1850-1959)B.1 Die Entwicklung der Wachstumsrate des durchschnittlichen Lohneinkommens im Deutschen Reich und in der Bundesrepublik Deutschland (1917-1967)B.2 Wachstumsrate der Lohneinkommen in der Bundesrepublik Deutschland (1951-1968)

ABD'de saatlik ücretler Haziran ayında 2025 yılında Mayıs ayına kıyasla 31.15 ABD Doları'ndan 31.24 ABD Doları'na yükseldi. Bu sayfa, ABD Ortalama Saatlik Ücretleri - gerçek degerler, tarihsel veriler, tahmin, grafik, istatistikler, ekonomik takvim ve haberleri saglar.