This Dataset indicates average salary by position title and grade for full-time regular employees. Data excludes elected, appointed, non-merit and temporary employees. Underfilled positions are also excluded from the dataset. Update Frequency : Annually

In 2023, the average wage in private industry in Alabama was at 58,993 U.S. dollars. This was nearly half of the annual average wages per employee in the District of Columbia, at 112,048 U.S. dollars. That year, the District of Columbia, Massachusetts, and New York were the top ranked states in terms of average wages per employee.

Average Monthly Nominal Wages: UF: Tumen Region: Khanty Mansiysky Area data was reported at 124,372.400 RUB in 2024. This records an increase from the previous number of 108,148.000 RUB for 2023. Average Monthly Nominal Wages: UF: Tumen Region: Khanty Mansiysky Area data is updated yearly, averaging 38,386.600 RUB from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 124,372.400 RUB in 2024 and a record low of 646.000 RUB in 1994. Average Monthly Nominal Wages: UF: Tumen Region: Khanty Mansiysky Area data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GC008: Average Monthly Wages: by Region.

Context

This dataset provides information on the average wage in various countries. Understanding the average wage in different countries is essential for economic analysis, benchmarking, and comparisons. Researchers, analysts, and policymakers can use this dataset to gain insights into global income disparities, labor market conditions, and economic trends.

Country_Gross Average Monthly Wages in 2020

The dataset comprises two primary columns: "Country" and "Gross Average Monthly Wages in 2020 (US$, at current Exchange Rates)." Each entry in the "Country" column represents a distinct country or region, while the corresponding entry in the "Gross Average Monthly Wages" column denotes the average earnings in US dollars for the specified location in the year 2020.

Development of Average Annual Wages

The "Development of Average Annual Wages" dataset, available on Kaggle, offers a comprehensive collection of average annual wage data spanning from the year 2000 to 2022. This dataset is a valuable resource for researchers, analysts, economists, and data enthusiasts interested in understanding the economic trends and wage dynamics across various countries over the past two decades.

Explore the progression of average salaries for graduates in City & Region Planning from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of City & Region Planning relative to other fields. This data is essential for students assessing the return on investment of their education in City & Region Planning, providing a clear picture of financial prospects post-graduation.

The median annual earnings in the United Kingdom was 37,430 British pounds per year in 2024. Annual earnings varied significantly by region, ranging from 47,455 pounds in London to 32,960 pounds in the North East. Along with London, two other areas of the UK had median annual earnings above the UK average; South East England, and Scotland, at 39,038 pounds and 38,315 pounds respectively. Regional Inequality in the UK Various other indicators highlight the degree of regional inequality in the UK, especially between London and the rest of the country. Productivity in London, as measured by output per hour, was 26.2 percent higher than the UK average. By comparison, every other UK region, except the South East, fell below the UK average for productivity. In gross domestic product per head, London was also an outlier. The average GDP per head in the UK was just over 37,000 pounds in 2023, but for London it was almost 64,000 pounds. Again, the South East's GDP per head was slightly above the UK average, with every other region below it. Within London itself, there is also a great degree of inequality. In 2023, for example, the average earnings in Kensington and Chelsea were 964 pounds per week, compared with 675 pounds in Barking and Dagenham. Wages continue to grow in 2025 In March 2025, weekly wages in the UK were growing by around 5.6 percent, or 1.8 percent when adjusted for inflation. For almost two years, wages have grown faster than inflation after a long period where prices were rising faster than wages between 2021 and 2023. This was due to a sustained period of high inflation in the UK, which peaked in October 2022 at 11.1 percent. Although inflation started to slow the following month, it wasn't until June 2023 that wages started to outpace inflation. By this point, the damage caused by high energy and food inflation had led to the the worst Cost of Living Crisis in the UK for a generation.

Comparison of the average salary of State of Oklahoma employees and the market average salary beginning in fiscal year 2005.

Average Monthly Nominal Wages: CF: Ryazan Region data was reported at 64,008.800 RUB in 2024. This records an increase from the previous number of 53,269.700 RUB for 2023. Average Monthly Nominal Wages: CF: Ryazan Region data is updated yearly, averaging 12,686.300 RUB from Dec 1992 (Median) to 2024, with 33 observations. The data reached an all-time high of 64,008.800 RUB in 2024 and a record low of 4.300 RUB in 1992. Average Monthly Nominal Wages: CF: Ryazan Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Demographic and Labour Market – Table RU.GC008: Average Monthly Wages: by Region.

Graph and download economic data for Median Personal Income in Northeast Census Region (MEPAINUSNEA646N) from 1974 to 2023 about Northeast Census Region, personal income, personal, median, income, and USA.

Explore the progression of average salaries for graduates in Geomatics Engineeringspecialize Positioning, Navigation And Wireless Location from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Geomatics Engineeringspecialize Positioning, Navigation And Wireless Location relative to other fields. This data is essential for students assessing the return on investment of their education in Geomatics Engineeringspecialize Positioning, Navigation And Wireless Location, providing a clear picture of financial prospects post-graduation.

Graph and download economic data for Median Family Income in West Census Region (MEFAINUSWEA646N) from 1953 to 2023 about West Census Region, family, median, income, and USA.

Explore the progression of average salaries for graduates in International Area Studies from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of International Area Studies relative to other fields. This data is essential for students assessing the return on investment of their education in International Area Studies, providing a clear picture of financial prospects post-graduation.

Wages in the United States increased to 31.34 USD/Hour in July from 31.26 USD/Hour in June of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages In the Euro Area increased to 2607 EUR/Month in the first quarter of 2025 from 2589 EUR/Month in the fourth quarter of 2024. This dataset provides the latest reported value for - Euro Area Average Monthly wage per person - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Explore the progression of average salaries for graduates in Translation & Localization Mgmt English/Japanese from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Translation & Localization Mgmt English/Japanese relative to other fields. This data is essential for students assessing the return on investment of their education in Translation & Localization Mgmt English/Japanese, providing a clear picture of financial prospects post-graduation.

This dataset presents the average daily wage earnings during the preceding calendar month from regular wage/salaried employment among the regular wage/salaried employees in CWS for each State/ UT. For 2023-24, Chandigarh's entire area has been considered urban for this survey. Before 2019-20, Ladakh was part of Jammu and Kashmir, and since 2020-21, Daman and Diu have been merg ed with Dadra and Nagar Haveli to form the union territory of Dadra and Nagar Haveli and Daman and Diu.

The statistic shows the average annual salary of employees working for urban non-private companies and organizations in China between 2013 and 2023, by geographic region. In 2023, the average income of an employee working at an urban unit in West China ranged at approximately ******* yuan per year.

Average full-time hourly wage paid and payroll employment by type of work, economic region and National Occupational Classification (NOC), 2016 and 2017.

VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

LAST UPDATED January 2019

DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

American Community Survey (2001-2017) http://api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

Salary information for State of Oklahoma employees by pay band, including average, maximum and minimum, and the size of the range by pay band.