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This paper using panel data of 2008-2019 Shanghai and Shenzhen A-share listed companies as the research sample and employing the multiple regression method to tests the relationship between executive compensation incentives and R&D investment of listed companies in China, further investigates the path of the relationship between the two and the influence of government subsidy to the relationship. In this paper, the selected samples are excluded according to the following criteria: ①Companies with incomplete data on financial indicators and corporate governance indicators are excluded. ②Eliminate companies with negative asset-liability ratio or greater than 1. ③Exclude companies in the financial and insurance industry. ④Exclude listed companies less than 1 year. ⑤Exclude companies containing S, ST and *ST. ⑥Exclude the companies with extreme sample data. The risk-taking data involved in this paper came from the WIND database. Other data come from the CSMAR database.
This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html
Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)
The Employer Database System is a database of all Oregon employers and their history of workers’ compensation (WC) insurance coverage. The system produces a snapshot of current employers with active workers’ compensation insurance policies.
The most current data are updated monthly during the first week of the month.
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.
Oregon workers' compensation data about insurers and self-insured employers. The data is presented in the Department of Consumer and Business Services report at https://www.oregon.gov/dcbs/reports/compensation/Pages/index.aspx. The attached pdf provides definitions of the data.
Explore and analyze comprehensive H-1B visa salary data meticulously organized by individual US states. Find insights into compensation trends across different regions.
This data set contains DOT employee workers compensation claim data for current and past DOT employees. Types of data include claim data consisting of PII data (SSN, Name, Date of Birth, Home Address, Financial Institution, medical, etc.) and claim data from the Department of Labor
View H-1B visa salary data aggregated by city. Compare salaries in major metropolitan areas and other locations across the US.
Lobbying-related compensation received by registered lobbyists as reported in their quarterly reports. See http://www.cityofchicago.org/city/en/depts/ethics/provdrs/lobby.html for more information on the Board of Ethics' role in regulating and reporting on lobbying in Chicago.
Filter H-1B visa salary information by job titles. Understand the salary landscape for specific roles across various industries in the United States.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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A. SUMMARY The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013.
B. HOW THE DATASET IS CREATED This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format.
C. UPDATE PROCESS New data is added on a bi-annual basis when available for each fiscal and calendar year.
D. HOW TO USE THIS DATASET Before using please first review the following two resources:
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Unlock valuable salary insights with our comprehensive Salary Dataset, designed for businesses, recruiters, and job seekers to analyze compensation trends, workforce planning, and market competitiveness.
Dataset Features
Job Listings & Salaries: Access structured salary data from top job platforms, including job titles, company names, locations, salary ranges, and compensation types. Employer & Industry Insights: Extract company-specific salary trends, industry benchmarks, and hiring patterns. Geographic Pay Disparities: Compare salaries across different regions, cities, and countries to identify location-based compensation trends. Job Market Trends: Monitor salary fluctuations, demand for specific roles, and hiring trends over time.
Customizable Subsets for Specific Needs Our Salary Dataset is fully customizable, allowing you to filter data based on job titles, industries, locations, experience levels, and salary ranges. Whether you need broad market insights or focused data for recruitment strategy, we tailor the dataset to your needs.
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Workforce Planning & Talent Acquisition: Optimize hiring strategies by analyzing salary benchmarks and compensation trends. Market Research & Competitive Intelligence: Compare salaries across industries and competitors to stay ahead in talent acquisition. Career Decision-Making: Help job seekers evaluate salary expectations and identify high-paying opportunities. AI & Predictive Analytics: Use structured salary data to train AI models for job market forecasting and compensation analysis. Geographic Expansion & Business Strategy: Assess salary variations across regions to plan business expansions and remote workforce strategies.
Whether you're optimizing recruitment, analyzing salary trends, or making data-driven career decisions, our Salary Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.
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Comprehensive physician salary data from verified doctor submissions across 75+ medical specialties
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.
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.
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Entity
Employee Salaries
Point of Contact
Human Resources
Sherri Arnold, Human Resources Business Partner III 757-385-8804 | Elda Soriano, HRIS Analyst 757-385-8597 |
Attributes
Column: Department
Description: 3-letter department code
Column: Department Division
Description: This is the City Division that the position is assigned to.
Column: PCN
Description: Tracking number used to reference each unique position within the City.
Column: Position Title
Description: 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 Date
Description: This is the date that the full-time employee first began employment with the City.
Column: Date in Title
Description: This is the date that the full-time employee first began employment in their current position.
Column: Salary
Description: This is the annual salary of the full-time employee or the hourly rate of the part-time employee.
Frequency of dataset update
Monthly
Data on individual compensation by nonprofit organizations as submitted on e-filed Form 990 and released publicly by the IRS
Comprehensive database of physician salaries across all medical specialties and US states, including averages, medians, and compensation ranges.
Glassdoor Data with U.S. salary insights, executive compensation, and company-level benchmarks. This structured Glassdoor Data powers HR analytics, payroll benchmarking, and financial modeling across startups, growth-stage firms, and enterprise organizations.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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Certified Report of Public Employment and Compensation for as submitted by the EIN Name of “City of Bloomington”
This data is reported exactly as entered by local officials.
Use of this data must be pursuant to Indiana Code 5-14-3-3(f), thus any information, including the names and addresses of government employees, obtained by viewing, printing and/or downloading will not be used for commercial or political purposes.
The following dataset is updated nightly and pulls from the City of Bloomington Payroll records dataset.
Please keep the following in mind when viewing or visualizing the data:
Compensation is the preferred term over salaries due to the fact that almost all employees are paid hourly. The only Salaried employees are those in elected positions (Mayor, Clerk, City Council people). For historical completed years, an employee’s compensation may include items such as, but not limited to: overtime, certifications, “on call” pay, etc.
For past years, the compensation would be as reported to the IRS with an effective date of the last day of the year. All data within the current year is a predicted compensation and may not reflect what the compensation will be by the end of the year. Previous years reflect what compensation was actually earned.
The “City of Bloomington '' has a wide variety of employee types: Regular Full Time, Regular Part Time, Temporary, Seasonal, Union and Non Union employees. Temporary and Seasonal employees can have multiple jobs at different pay rates. This data set reflects a combination of all these variables and just sums the compensation into one yearly amount.
Comprehensive database of verified healthcare professional salaries across different specialties and locations
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This paper using panel data of 2008-2019 Shanghai and Shenzhen A-share listed companies as the research sample and employing the multiple regression method to tests the relationship between executive compensation incentives and R&D investment of listed companies in China, further investigates the path of the relationship between the two and the influence of government subsidy to the relationship. In this paper, the selected samples are excluded according to the following criteria: ①Companies with incomplete data on financial indicators and corporate governance indicators are excluded. ②Eliminate companies with negative asset-liability ratio or greater than 1. ③Exclude companies in the financial and insurance industry. ④Exclude listed companies less than 1 year. ⑤Exclude companies containing S, ST and *ST. ⑥Exclude the companies with extreme sample data. The risk-taking data involved in this paper came from the WIND database. Other data come from the CSMAR database.