Wages in the United States increased 4.72 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Wages in China increased to 120698 CNY/Year in 2023 from 114029 CNY/Year in 2022. This dataset provides - China Average Yearly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages in the United States increased to 31.24 USD/Hour in June from 31.15 USD/Hour in May of 2025. This dataset provides - United States Average Hourly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by North American Industry Classification System (NAICS), type of work, gender, and age group.

Average hourly and weekly wage rate, and median hourly and weekly wage rate by National Occupational Classification (NOC), type of work, sex, and age group, 1997 to 2022.

Wages in Italy increased to 32450 EUR/Year in 2023 from 31720 EUR/Year in 2022. This dataset provides the latest reported value for - Italy Average Nominal Monthly Wages - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The WageIndicator Survey is a continuous, multilingual, multi-country web-survey, counducted across 65 countries since 2000. The web-survey generates cross sectional and longitudinal data which might provide data especially about wages, benefits, working hours, working conditions and industrial relations. The survey has detailed questions about earnings, benefits, working conditions, employment contracts and training, as well as questions about education, occupation, industry and household characteristics. The WageIndicator Survey is a multilingual questionnaire and aims to collect information on wages and working conditions. As labour markets and wage setting processes vary across countries, country specific translations have been favoured over literal translations. The WageIndicator Survey includes regularly extra survey questions for project targeting specific countries, for specific groups or about specific events. These projects usually address a specific audience (employees of a company, employees in an industry, readers of a magazine, members of a trade union or an occupational association, and alike). The data of the project questions are included in the dataset. Bias: Non-Probability web based surveys are problematic because not every individual has the same probability of being selected into the survey. The probability of being selected depends on national or regional internet access rates and on numbers of visitors accessing the webiste. Data of such surveys form a convenience rather than a probability sample. Due to the non-probability based nature of the survey and its selectivity the obtained results cannot be generalized for the population of interest; i.e. the labor force. Comparisons with representative studies found an underrepresentation of male labour force, part-timers, older age groups, and low educated persons. Besides other strategies to reduce the bias the WageIndicators provides different weighting schemes in order to correct for selection bias. Data Characteristics: The data is organised in annual releases. The data of the period 2000-2005 is released as one dataset. Each data release consists of a dataset with continuous variables and one with project variables. The continuous variables can be merged across years. All variable and value labels are in English. The data does not include the text variables and verbatims form open-ended survey questions, these are available in Excel-Format upon request. Spatial Coverage: The survey started in 2000 in the Netherlands. Since 2004, websites have been launched in many European countries, in North and South America and in countries in Asia. From 2008 on web sites have been launched in more African countries, as well as in Indonesia and in a number of post-Soviet countries. For each country, the questions have been translated. Multilingual countries employ multilingual questionnaires. Country-specific translations and locally accepted terminology have been favored over literal translations.

Wages in Mexico decreased to 278.93 MXN/Day in May from 621.89 MXN/Day in April of 2025. This dataset provides - Mexico Average Daily Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The minimum wage is a basic labour standard that sets the lowest wage rate that an employer can pay to employees who are covered by the legislation. Today, one of its main purposes is to protect non-unionized workers in unskilled jobs, although it can also influence, directly or indirectly, the level of compensation of other employees as well. A minimum wage constitutes a floor above which employees or their unions may negotiate with management for higher remuneration. However, it is rarely static: adjustments are required from time to time to maintain its relevance in changing economic and social conditions.

Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

Pakistan Average Monthly Wages data was reported at 24,028.000 PKR in 2021. This records an increase from the previous number of 21,326.000 PKR for 2019. Pakistan Average Monthly Wages data is updated yearly, averaging 12,636.500 PKR from Jun 2008 (Median) to 2021, with 10 observations. The data reached an all-time high of 24,028.000 PKR in 2021 and a record low of 6,612.000 PKR in 2008. Pakistan Average Monthly Wages data remains active status in CEIC and is reported by Pakistan Bureau of Statistics. The data is categorized under Global Database’s Pakistan – Table PK.G004: Average Monthly Wages: by Industry. No data for 2016-2017 as per source. Labour Force Survey has not been conducted for these two years due to Population Census.

The WageIndicator Survey is a continuous, multilingual, multi-country web-survey, counducted across 65 countries since 2000. The web-survey generates cross sectional and longitudinal data which might provide data especially about wages, benefits, working hours, working conditions and industrial relations.
The survey has detailed questions about earnings, benefits, working conditions, employment contracts and training, as well as questions about education, occupation, industry and household characteristics.

Research Focus:
The WageIndicator Survey is a multilingual questionnaire and aims to collect information on wages and working conditions. As labour markets and wage setting processes vary across countries, country specific translations have been favoured over literal translations. The WageIndicator Survey includes regularly extra survey questions for project targeting specific countries, for specific groups or about specific events.
These projects usually address a specific audience (employees of a company, employees in an industry, readers of a magazine, members of a trade union or an occupational association, and alike). The data of the project questions are included in the dataset.

Sample:
The target population of the WageIndicator is the labour force, that is, individuals in paid employment as well as job seekers. In addition to workers in formal dependent employment the survey aims to include apprentices, employers, own-account workers, freelancers, workers in family businesses, workers in the informal sector, unemployed workers, job seekers individuals who never had a job, as well as retired workers and housewifes school pupils or students with a job on the side and persons performing voluntary work.
The WageIndicator data is derived from a volunteer survey, inviting webvisitors to the national WageIndicator websites to complete the web-survey. Annually, the websites receive millions of web-visitors.

Bias:
Non-Probability web based surveys are problematic because not every individual has the same probability of being selected into the survey. The probability of being selected depends on national or regional internet access rates and on numbers of visitors accessing the webiste. Data of such surveys form a convenience rather than a probability sample. Due to the non-probability based nature of the survey and its selectivity the obtained results cannot be generalized for the population of interest; i.e. the labor force.
Comparisons with representative studies found an underrepresentation of male labour force, part-timers, older age groups, and low educated persons.
Besides other strategies to reduce the bias the WageIndicators provides different weighting schemes in order to correct for selection bias.

Data Characteristics:
The data is organised in annual releases. The data of the period 2000-2005 is released as one dataset. Each data release consists of a dataset with continuous variables and one with project variables. The continuous variables can be merged across years. All variable and value labels are in English. The data does not include the text variables and verbatims form open-ended survey questions, these are available in Excel-Format upon request.

Spatial Coverage:
The survey started in 2000 in the Netherlands. Since 2004, websites have been launched in many European countries, in North and South America and in countries in Asia. From 2008 on web sites have been launched in more African countries, as well as in Indonesia and in a number of post-Soviet countries.
For each country each, the questions have been translated. Multilingual countries employ multilingual questionnaires. Country-specific translations and locally accepted terminology have been favored over literal translations.

Rights: Due to the confidential character of the WageIndicator microdata, direct access to the data is only provided by means of research contracts. Access is in principle restricted to universities and research institutes.

Date: 2000 -

Wages in Slovakia increased to 1801 EUR/Month in May from 1755 EUR/Month in April of 2025. This dataset provides - Slovakia Average Monthly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Java town. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Java town, the median income for all workers aged 15 years and older, regardless of work hours, was $51,298 for males and $42,109 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 18% between the median incomes of males and females in Java town. With women, regardless of work hours, earning 82 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Java town.

- Full-time workers, aged 15 years and older: In Java town, among full-time, year-round workers aged 15 years and older, males earned a median income of $60,817, while females earned $52,500, resulting in a 14% gender pay gap among full-time workers. This illustrates that women earn 86 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the town of Java town.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Java town.

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 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

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.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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

Average weekly earnings at sector level headline estimates, Great Britain, monthly, seasonally adjusted. Monthly Wages and Salaries Survey.

Please provide me with the following: Guidelines / procedures which cover / include the calculation of Reckonable Salaries Pension Increases, year by year, since 1 August 2011 Please do not hesitate to contact me if you need any further information You subsequently clarified your request with: Reckonable salary would be the same as reckonable pay Your clarified request was received on 18th January 2023 and I am dealing with it under the terms of the Freedom of Information Act 2000. Summary of Response Under Section 21 of the Act, we are not required to provide information in response to a request if it is already reasonably accessible to you. Pensions uses reckonable “pay” for the calculation of pensions in the 2008 section of the Scheme and information is available on our website by searching for reckonable pay. The below link is a factsheet regarding the calculation of reckonable pay which may be of help: https://www.nhsbsa.nhs.uk/sites/default/files/2017-04/Total%20Reckonable%20Pay%20factsheet%20%E2%80%93%202008%20Section%20%2804.2017%29%20V4.pdf Information on Pensions Increases can be found on the Gov.uk website as follows: https://www.gov.uk/government/collections/public-service-pensions-increases The above link provides information on increases from 2014 to 2022. The below link provides information from earlier years. http://webarchive.nationalarchives.gov.uk/20130402150008/http:/www.hm-treasury.gov.uk/tax_pensions_increases.htm Click the link titled ‘Pensions Increase archive’ for data prior to 2013.

Average weekly earnings, average hourly wage rate and average usual weekly hours by union status and type of work, last 5 years.

Wages in Manufacturing in the United States remained unchanged at 28.87 USD/Hour in June. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by home-based region to local and unitary authority level.

Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by four-digit Standard Occupational Classification.