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Graph and download economic data for Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men (LEU0254609800A) from 2000 to 2024 about occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.
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United States - Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men was 49.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men reached a record high of 95.00000 in January of 2000 and a record low of 46.00000 in January of 2013. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men - last updated from the United States Federal Reserve on June of 2025.
In 2023, the best paying industry in the United States for data entry keyers was in the federal postal service. The second best paying industry was in natural gas distribution, where data entry keyers earned an annual wage of approximately ****** U.S. dollars in 2023.
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Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over (LEU0254556400A) from 2000 to 2024 about second quartile, occupation, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.
In 2022, the top paying state for date entry keyers in the United States was the District of Columbia, where this workforce earned an annual mean wage of approximately ****** U.S. dollars. The state with the second highest annual mean wage for data entry keyers was Massachusetts, where those employed within this industry earned ****** U.S. dollars.
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United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over: Women was 886.00000 $ in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over: Women reached a record high of 886.00000 in January of 2024 and a record low of 429.00000 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over: Women - last updated from the United States Federal Reserve on June of 2025.
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Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over: Women (LEU0254770000A) from 2000 to 2024 about second quartile, occupation, females, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.
Rigidity in real hiring wages plays a crucial role in some recent macroeconomic models. But are hiring wages really so noncyclical? We propose using employer/employee longitudinal data to track the cyclical variation in the wages paid to workers newly hired into specific entry jobs. Illustrating the methodology with 1982-2008 data from the Portuguese census of employers, we find real entry wages were about 1.8 percent higher when the unemployment rate was 1 percentage point lower. Like most recent evidence on other aspects of wage cyclicality, our results suggest that the cyclical elasticity of wages is similar to that of employment. (JEL E24, E32, J31, J64)
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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.
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.
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.
Using a longitudinal matched employer-employee dataset for Portugal over the 1986-2007 period, this study analyzes the wage responses to aggregate labor market conditions for newly hired workers and existing workers within the same firm. Accounting for worker, firm, and job title heterogeneity, the data support the hypothesis that entry wages are more procyclical than wages of stayers. A one point increase in the unemployment rate decreases wages of newly hired workers within a given firm-job title by around 2.7 percent and by 2.2 percent for stayers within the same firm-job title. Finally, the results reveal a one-for-one wage response to changes in labor productivity. (JEL: E24, E32, J64)
Data is collected because of public interest in how the City’s budget is being spent on salary and overtime pay for all municipal employees. Data is input into the City's Personnel Management System (“PMS”) by the respective user Agencies. Each record represents the following statistics for every city employee: Agency, Last Name, First Name, Middle Initial, Agency Start Date, Work Location Borough, Job Title Description, Leave Status as of the close of the FY (June 30th), Base Salary, Pay Basis, Regular Hours Paid, Regular Gross Paid, Overtime Hours worked, Total Overtime Paid, and Total Other Compensation (i.e. lump sum and/or retro payments). This data can be used to analyze how the City's financial resources are allocated and how much of the City's budget is being devoted to overtime. The reader of this data should be aware that increments of salary increases received over the course of any one fiscal year will not be reflected. All that is captured, is the employee's final base and gross salary at the end of the fiscal year. In very limited cases, a check replacement and subsequent refund may reflect both the original check as well as the re-issued check in employee pay totals. NOTE 1: To further improve the visibility into the number of employee OT hours worked, beginning with the FY 2023 report, an updated methodology will be used which will eliminate redundant reporting of OT hours in some specific instances. In the previous calculation, hours associated with both overtime pay as well as an accompanying overtime “companion code” pay were included in the employee total even though they represented pay for the same period of time. With the updated methodology, the dollars shown on the Open Data site will continue to be inclusive of both types of overtime, but the OT hours will now reflect a singular block of time, which will result in a more representative total of employee OT hours worked. The updated methodology will primarily impact the OT hours associated with City employees in uniformed civil service titles. The updated methodology will be applied to the Open Data posting for Fiscal Year 2023 and cannot be applied to prior postings and, as a result, the reader of this data should not compare OT hours prior to the 2023 report against OT hours published starting Fiscal Year 2023. The reader of this data may continue to compare OT dollars across all published Fiscal Years on Open Data. NOTE 2: As a part of FISA-OPA’s routine process for reviewing and releasing Citywide Payroll Data, data for some agencies (specifically NYC Police Department (NYPD) and the District Attorneys’ Offices (Manhattan, Kings, Queens, Richmond, Bronx, and Special Narcotics)) have been redacted since they are exempt from disclosure pursuant to the Freedom of Information Law, POL § 87(2)(f), on the ground that disclosure of the information could endanger the life and safety of the public servants listed thereon. They are further exempt from disclosure pursuant to POL § 87(2)(e)(iii), on the ground that any release of the information would identify confidential sources or disclose confidential information relating to a criminal investigation, and POL § 87(2)(e)(iv), on the ground that disclosure would reveal non-routine criminal investigative techniques or procedures. Some of these redactions will appear as XXX in the name columns.
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Israel Labour Input Index: 1990=100: Railway Service: Wages: Average per Employee per Month data was reported at 706.700 1990=100 in Jun 2011. This records an increase from the previous number of 420.300 1990=100 for May 2011. Israel Labour Input Index: 1990=100: Railway Service: Wages: Average per Employee per Month data is updated monthly, averaging 277.650 1990=100 from Jan 1989 (Median) to Jun 2011, with 270 observations. The data reached an all-time high of 814.600 1990=100 in Jan 2010 and a record low of 65.800 1990=100 in Jan 1989. Israel Labour Input Index: 1990=100: Railway Service: Wages: Average per Employee per Month data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G041: Labour Input Index: Bus and Railway Services.
A. Objective To generate statistics for wage and salary administration and for wage determination in collective bargaining negotiations.
B. Uses of Data Inputs to wage, income, productivity and price policies, wage fixing and collective bargaining; occupational wage rates can be used to measure wage differentials, wage inequality in typical low wage and high wage occupations and for international comparability; industry data on basic pay and allowance can be used to measure wage differentials across industries, for investment decisions and as reference in periodic adjustments of minimum wages.
C. Main Topics Covered Occupational wage rates Median basic pay and median allowances of time-rate workers on full-time basis
National Capital Region
Establishment
The survey covered non-agricultural establishments employing 50 or more workers except national postal activities, central banking, public administration and defense and compulsory social security, public education services, public medical, dental and other health services, activities of membership organizations, extra territorial organizations and bodies.
Sample survey data [ssd]
Statistical unit: The statistical unit is the establishment. Each unit is classified to an industry that reflects its main economic activity---the activity that contributes the biggest or major portion of the gross income or revenues of the establishment.
Survey universe/Sampling frame: The sampling frame used for the survey was taken from the List of Establishments of the National Statistics Office. On a partial basis, this is regularly updated based on the responses to other surveys of the BLES, establishment reports on retrenchments and closures submitted to the Regional Offices of the Department of Labor and Employment and other establishment lists.
Sampling design: The OWS is a complete enumeration survey of non-agricultural establishments employing 50 persons or more in the National Capital Region.
Sample size: For OWS 2002, number of establishments covered was 5,954 of which, 3,974 were eligible units.
Note: Refer to Field Operations Manual
Not all of the fielded questionnaires are accomplished. During data collection, there are reports of permanent closures, non-location, duplicate listing and shifts in industry and employment outside the survey coverage. Establishments that fall in these categories are not eligible elements (three consecutive survey rounds for "can not be located" establishments) of the frame and their count is not considered in the estimation. Non-respondents are made up of refusals, strikes or temporary closures, can not be located (less than three consecutive survey rounds) and those establishments whose questionnaires contain inconsistent item responses and have not replied to the verification queries by the time output table generation commences.
Respondents are post-stratified as to geographic, industry and employment size classifications. Non-respondents are retained in their classifications. Sample values of basic pay and allowances for the monitored occupations whose basis of payment is an hour or a day are converted into a standard monthly equivalent, assuming 313 working days and 8 hours per day. Daily rate x 26.08333; Hourly rate x 208.66667.
Other [oth] mixed method: self-accomplished, mailed, face-to-face
The 2002 OWS questionnaire is made up of the following sections:
Cover page (Page 1) This contains the address box for the establishment and other particulars.
Survey Information (Page 2) This section provides information on the purpose of the survey, coverage, reference period, collection authority, authorized field personnel, confidentiality clause, due date, availability of results and assistance available.
Part A: General Information (Page 3) This part inquires on the main economic activity, major product/s, goods or services, total employment, ownership (with foreign equity or wholly Filipino), spread of operations (whether establishment is a multinational), market orientation (for manufacturing only, engaged in export or domestic market only), presence of a union and existence of a collective bargaining agreement in the establishment.
Part B: Employment and Wage Rates of Time-Rate Workers on Full Time Basis (Pages 4 - 5) It inquires data on the distribution of time-rate workers on full-time basis by time unit (hourly, daily, monthly) and basic pay and allowance intervals;
Part C: Employment and Wage Rates of Time-Rate Workers on Full-Time Basis in Selected Occupations (Pages 6 - 11) For each occupation covered, the establishment is asked to report the time unit of work (hourly, daily, monthly), corresponding basic pay per worker and number of workers. Similar data are also asked for workers in the occupation that are given regular allowances. The total number of workers disaggregated by sex in each monitored occupation is likewise requested
Part D: Key and Representative Occupations in the Establishment (Page 12) This asks for the occupations and corresponding employment of those considered as unique to the industry/sector to which the establishment belongs, employs the most number of works, historically important in the wage structure or emerging/has a high growth potential.
Survey Results (Pages 13 - 14) Selected statistical tables from the previous two (2) survey rounds are provided for information of the respondents.
Part E: Certification of Respondent (Page 15) This box is provided for the respondent’s comments or suggestions (on the data it provided for the survey, results of previous survey rounds and improvements on the design/contents of the questionnaire) and for the name and signature, position, and telephone/fax numbers and e-mail address of the person responsible for filling out the form.
Part F: Survey Personnel (Page 15) This portion is allocated for the names of personnel involved in collection, editing and review of each questionnaire and dates when the activities were completed.
Part G: Industries with Selected Occupations (Page 16) This lists the selected 43 industries whose occupational wage rates and employment are being monitored.
Note: Refer to Questionnaire.
Data are manually and electronically processed. Upon collection of accomplished questionnaires, enumerators perform field editing before leaving the establishments to ensure completeness, consistency and reasonableness of entries in accordance with the field operations manual. The forms are again checked for data consistency and completeness by their field supervisors.
The BLES personnel undertake the final review, coding of information on classifications used, data entry and validation and scrutiny of aggregated results for coherence. Questionnaires with incomplete or inconsistent entries are returned to the establishments for verification, personally or through mail.
Note: Refer to Field Operations Manual Chapter 1 Section 1.10.
The response rate in terms of eligible units was 78.7%.
The survey results are checked for consistency with the results of previous OWS data and the minimum wage rates corresponding to the reference period of the survey.
In 2024, the expected median starting salary for MBA graduates worldwide was ******* U.S. dollars. On the other hand, master's graduates in data analytics, business analytics, finance, and management were expected to have a median salary of ****** U.S. dollars.
In 2021, the average annual starting salary for MBA graduates working in the consulting industry in the United States was ******* U.S. dollars. In comparison, the average annual MBA starting salary for graduates working in financial services was ******* U.S. dollars.
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Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over: Men (LEU0254663200A) from 2000 to 2023 about second quartile, occupation, full-time, males, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.
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Israel Labour Input Index: 1990=100: Railway Service: Wages data was reported at 1,171.200 1990=100 in Jun 2011. This records an increase from the previous number of 696.100 1990=100 for May 2011. Israel Labour Input Index: 1990=100: Railway Service: Wages data is updated monthly, averaging 279.200 1990=100 from Jan 1989 (Median) to Jun 2011, with 270 observations. The data reached an all-time high of 1,266.200 1990=100 in Jan 2010 and a record low of 73.100 1990=100 in Jan 1989. Israel Labour Input Index: 1990=100: Railway Service: Wages data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G041: Labour Input Index: Bus and Railway Services.
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Israel Labour Input Index: 2010=100: Bus Service: Wages: Monthly Avg per Employee Job incl Cooperative Members data was reported at 108.200 2010=100 in Dec 2017. This records a decrease from the previous number of 109.800 2010=100 for Nov 2017. Israel Labour Input Index: 2010=100: Bus Service: Wages: Monthly Avg per Employee Job incl Cooperative Members data is updated monthly, averaging 101.650 2010=100 from Jan 2008 (Median) to Dec 2017, with 120 observations. The data reached an all-time high of 134.400 2010=100 in Dec 2008 and a record low of 77.100 2010=100 in Jun 2009. Israel Labour Input Index: 2010=100: Bus Service: Wages: Monthly Avg per Employee Job incl Cooperative Members data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G041: Labour Input Index: Bus and Railway Services.
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Israel Labour Input Index: 2015=100: Bus Service: Wages data was reported at 127.400 2015=100 in Jun 2018. This records a decrease from the previous number of 132.100 2015=100 for May 2018. Israel Labour Input Index: 2015=100: Bus Service: Wages data is updated monthly, averaging 123.700 2015=100 from Jul 2016 (Median) to Jun 2018, with 24 observations. The data reached an all-time high of 132.100 2015=100 in May 2018 and a record low of 111.900 2015=100 in Oct 2016. Israel Labour Input Index: 2015=100: Bus Service: Wages data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G041: Labour Input Index: Bus and Railway Services: 2015=100.
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Israel Labour Input Index: 2015=100: Railway Service: Wages data was reported at 190.408 2015=100 in Jun 2018. This records an increase from the previous number of 107.820 2015=100 for May 2018. Israel Labour Input Index: 2015=100: Railway Service: Wages data is updated monthly, averaging 110.099 2015=100 from Jul 2016 (Median) to Jun 2018, with 24 observations. The data reached an all-time high of 190.408 2015=100 in Jun 2018 and a record low of 89.266 2015=100 in Oct 2016. Israel Labour Input Index: 2015=100: Railway Service: Wages data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.G041: Labour Input Index: Bus and Railway Services: 2015=100.
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Graph and download economic data for Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men (LEU0254609800A) from 2000 to 2024 about occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.