The Compensation and Salary Surveys (FR 29) is comprised of the (1) Compensation and Salary Survey (FR 29a) and (2) Ad Hoc Surveys (FR 29b). The FR 29a is collected annually and the FR 29b is collected on an as needed basis but not more frequently than five times per year. These surveys collect information on salaries, employee compensation policies, and other employee programs from employers that are considered competitors of the Board. The data from the surveys primarily are used to determine the appropriate salary structure and salary adjustments for Board employees.

Popular US workplace blog AskAManager (askamanager.org) sponsors an annual salary survey of blog readers. The 2023 survey collected data about industry, job function, title, annual salary, additional compensation, race, gender, remote/on-site requirements, education, location, and years' experience.

The dataset here features responses collected between April 11 and 28, 2023, and has some 16,000 responses. This version of the data set has employed several feature engineering techniques to group and cleanse data, convert the currency to USD values as of April 1, 2023, and add clarity to location data. In particular, US respondents were paired when possible with a metropolitan area.

The National Compensation Survey (NCS) program produces information on wages by occupation for many metropolitan areas.The Modeled Wage Estimates (MWE) provide annual estimates of average hourly wages for occupations by selected job characteristics and within geographical _location. The job characteristics include bargaining status (union and nonunion), part- and full-time work status, incentive- and time-based pay, and work levels by occupation. The modeled wage estimates are produced using a statistical procedure that combines survey data collected by the National Compensation Survey (NCS) and the Occupational Employment Statistics (OES) programs. Borrowing from the strengths of the NCS, information on job characteristics and work levels, and from the OES, the occupational and geographic detail, the modeled wage estimates provide more detail on occupational average hourly wages than either program is able to provide separately. Wage rates for different work levels within occupation groups also are published. Data are available for private industry, State and local governments, full-time workers, part-time workers, and other workforce characteristics.

This data comes from the 2018 salary survey data. Please notethe following:

1. Where able, the data has been altered to reflect the annual pay of the average employee in this city and in this position based on the city's salary range.
2. Not all salaries and wages of less than 1 FTE could be confirmed. As a result, some salaries for positions with less than 1 FTE are either the annual equivelant or the actual pay of the employee throughout a year (ex. if an employee would make $50,000 as a full time employee but only works half-time, some cities marked this as $50,000 or $25,000.
3. Educational attainment often was provided with a minimum education and experience as well as a preferred level. The minimum of both categories are provided.

In October 2024, the average hourly earnings for all employees on private nonfarm payrolls in the United States stood at 35.46 U.S. dollars. The data have been seasonally adjusted. Employed persons are employees on nonfarm payrolls and consist of: persons who did any work for pay or profit during the survey reference week; persons who did at least 15 hours of unpaid work in a family-operated enterprise; and persons who were temporarily absent from their regular jobs because of illness, vacation, bad weather, industrial dispute, or various personal reasons.

Graph and download economic data for Employment Level - Nonagriculture, Government Wage and Salary Workers (LNU02032188) from Jan 1948 to Jun 2025 about nonagriculture, salaries, workers, 16 years +, wages, household survey, government, employment, and USA.

The dataset includes the merged data of face-to-face salary surveys in 28 countries, undertaken between 2006 and 2013. The total number of observations is 59,138 individuals in the labour force. Almost all countries are developing countries in Africa, Asia, and Latin America.

This dataset has been published by the Human Resources Department of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.Distributed bydata.virginiabeach.gov2405 Courthouse Dr.Virginia Beach, VA 23456EntityEmployee SalariesPoint of ContactHuman ResourcesSherri Arnold, Human Resources Business Partner IIIsharnold@vbgov.com757-385-8804Elda Soriano, HRIS Analystesoriano@vbgov.com757-385-8597AttributesColumn: DepartmentDescription: 3-letter department codeColumn: Department DivisionDescription: This is the City Division that the position is assigned to.Column: PCNDescription: Tracking number used to reference each unique position within the City.Column: Position TitleDescription: This is the title of the position (per the City’s pay plan).Column: FLSA Status Description: Represents the position’s status with regards to the Fair Labor Standards Act (FLSA) “Exempt” - These positions do not qualify for overtime compensation – Generally, a position is classified as FLSA exempt if all three of the following criteria are met: 1) Paid at least $47,476 per year ($913 per week); 2) Paid on a salary basis - generally, salary basis is defined as having a guaranteed minimum amount of pay for any work week in which the employee performs any work; 3) Perform exempt job duties - Job duties are split between three classifications: executive, professional, and administrative. All three have specific job functions which, if present in the employee’s regular work, would exempt the individual from FLSA. Employees may also be exempt from overtime compensation if they are a “highly compensated employee” as defined by the FLSA or the position meets the criteria for other enumerated exemptions in the FLSA.“Non-exempt” – These positions are eligible for overtime compensation - positions classified as FLSA non-exempt if they fail to meet any of exempt categories specified in the FLSA. Column: Initial Hire DateDescription: This is the date that the full-time employee first began employment with the City.Column: Date in TitleDescription: This is the date that the full-time employee first began employment in their current position.Column: SalaryDescription: This is the annual salary of the full-time employee or the hourly rate of the part-time employee.Frequency of dataset updateMonthly

Salary, educational and experience requirements collected during the 2022 City Employee Salary Survey.

Nepal National Salary & Wage Rate Index: Wage Index data was reported at 511.500 2004-2005=100 in Oct 2018. This records an increase from the previous number of 505.000 2004-2005=100 for Sep 2018. Nepal National Salary & Wage Rate Index: Wage Index data is updated monthly, averaging 282.500 2004-2005=100 from Aug 2005 (Median) to Oct 2018, with 159 observations. The data reached an all-time high of 511.500 2004-2005=100 in Oct 2018 and a record low of 102.500 2004-2005=100 in Aug 2005. Nepal National Salary & Wage Rate Index: Wage Index data remains active status in CEIC and is reported by Nepal Rastra Bank. The data is categorized under Global Database’s Nepal – Table NP.G018: Salary & Wage Rate Index.

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.

This bienneial survey provides information on wages and salaries for full- and part-time employees by occupation, region, and industry. The survey helps Albertans make career and education choices and helps organizations determine pay scales.

The wages on the Job Bank website are specific to an occupation and provide information on the earnings of workers at the regional level. Wages for most occupations are also provided at the national and provincial level. In Canada, all jobs are associated with one specific occupational grouping which is determined by the National Occupational Classification. For most occupations, a minimum, median and maximum wage estimates are displayed. They are update annually. If you have comments or questions regarding the wage information, please contact the Labour Market Information Division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

Abstract

ICMA conducts a periodic survey of chief administrative officers (CAOs) to collect data on salary, benefits, and contract structure for municipal and county managers and administrators. Topics covered in this survey include annual base salary, additional compensation, health insurance and other benefits, and compensation decision making and transparency.

Methodology

This survey was administered in January 2019. It was sent to ICMA member CAOs via email containing a hyperlink to the questionnaire. A total of 2,994 ICMA members received the survey and 1,279 completed it for a 42.7% response rate. The respondents represent municipalities, counties, and regional agencies or councils of governments across 48 states (no responses were received from Hawaii or Mississippi).

Usage

Available documentation is contained in zip files labelled by survey year (see

Supporting Files). Documentation will always include the survey instrument; where available, documentation may also include codebooks and response rates.

The global salary benchmarking software market is experiencing robust growth, driven by increasing demand for accurate and efficient compensation management solutions across diverse industries. The market's expansion is fueled by several factors, including the need for competitive compensation strategies to attract and retain top talent in a tight labor market, the growing adoption of cloud-based solutions for enhanced accessibility and scalability, and the increasing regulatory scrutiny around pay equity and transparency. Companies are increasingly leveraging these software solutions to analyze salary data, identify pay gaps, and ensure fair compensation practices, leading to improved employee morale and reduced turnover. The market is segmented by deployment type (cloud-based and on-premise), organizational size (small, medium, and large enterprises), and industry vertical. While precise figures are unavailable, a reasonable estimate based on industry analysis and considering a relatively high CAGR (let's assume a CAGR of 15% for illustration purposes), suggests a 2025 market size of approximately $2 billion, with projections indicating continued substantial growth through 2033. This projection incorporates the expected expansion of the user base and increasing feature complexity within the software. The competitive landscape is characterized by a blend of established players and emerging startups. Established players like Workday and Carta Total Comp benefit from strong brand recognition and extensive client networks. Newer entrants, including MarketPay and OpenComp, are disrupting the market with innovative features and agile approaches. Market consolidation through mergers and acquisitions is likely, given the ongoing technological advancements and the increasing demand for integrated HR solutions. However, challenges persist. High implementation costs, integration complexities with existing HR systems, and concerns about data security can hinder market penetration. The future success of vendors will hinge on their ability to offer user-friendly interfaces, robust data analytics capabilities, and cost-effective solutions tailored to the specific needs of different customer segments. Furthermore, continuous innovation to incorporate AI-driven features for predictive analysis and compensation optimization will become crucial for gaining a competitive edge.

This data comes from the 2018 salary survey data. Please notethe following:

1. Where able, the data has been altered to reflect the annual pay of the average employee in this city and in this position based on the city's salary range.
2. Not all salaries and wages of less than 1 FTE could be confirmed. As a result, some salaries for positions with less than 1 FTE are either the annual equivelant or the actual pay of the employee throughout a year (ex. if an employee would make $50,000 as a full time employee but only works half-time, some cities marked this as $50,000 or $25,000.
3. Educational attainment often was provided with a minimum education and experience as well as a preferred level. The minimum of both categories are provided.

United States - Employed full time: Wage and salary workers: Survey researchers occupations: 16 years and over: Women was 1.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Survey researchers occupations: 16 years and over: Women reached a record high of 3.00000 in January of 2020 and a record low of 0.00000 in January of 2011. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Survey researchers occupations: 16 years and over: Women - last updated from the United States Federal Reserve on June of 2025.

1) Data Introduction • The Data Science Salaries 2023 Dataset is a global annual salary analysis dataset that summarizes a variety of information in a tabular format, including salary, career, employment type, job, remote work rate, and company location and size for data science jobs as of 2023.

2) Data Utilization (1) Data Science Salaries 2023 Dataset has characteristics that: • Each row contains 11 key characteristics, including year, career level, employment type, job name, annual salary (local currency and USD), employee country of residence, remote work rate, company location, and company size. • Data is organized to reflect different countries, jobs, careers, and work patterns to analyze pay and work environments in data science in three dimensions. (2) Data Science Salaries 2023 Dataset can be used to: • Data Science Salary Analysis and Comparison: Analyzing salary levels and distributions by job, career, country, and company size can be used to understand industry trends and market value. • Establishing Recruitment and Career Strategies: It can be applied to recruitment strategies, career development, global talent attraction, etc. by analyzing the correlation between various working conditions and salaries such as remote work rates, employment types, and company location.

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.

The Occupational Employment and Wage Statistics (OEWS) survey is a semiannual mail survey of employers that measures occupational employment and occupational wage rates for wage and salary workers in nonfarm establishments, by industry. OEWS estimates are constructed from a sample of about 41,400 establishments. Each year, forms are mailed to two semiannual panels of approximately 6,900 sampled establishments, one panel in May and the other in November.