Analysis of ‘US Minimum Wage by State from 1968 to 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/lislejoem/us-minimum-wage-by-state-from-1968-to-2017 on 12 November 2021.

--- Dataset description provided by original source is as follows ---

US Minimum Wage by State from 1968 to 2020

The Basics

• What is this? In the United States, states and the federal government set minimum hourly pay ("minimum wage") that workers can receive to ensure that citizens experience a minimum quality of life. This dataset provides the minimum wage data set by each state and the federal government from 1968 to 2020.

• Why did you put this together? While looking online for a clean dataset for minimum wage data by state, I was having trouble finding one. I decided to create one myself and provide it to the community.

• Who do we thank for this data? The United States Department of Labor compiles a table of this data on their website. I took the time to clean it up and provide it here for you. :) The GitHub repository (with R Code for the cleaning process) can be found here!

Content

This is a cleaned dataset of US state and federal minimum wages from 1968 to 2020 (including 2020 equivalency values). The data was scraped from the United States Department of Labor's table of minimum wage by state.

Description of Data

The values in the dataset are as follows: - Year: The year of the data. All minimum wage values are as of January 1 except 1968 and 1969, which are as of February 1. - State: The state or territory of the data. - State.Minimum.Wage: The actual State's minimum wage on January 1 of Year. - State.Minimum.Wage.2020.Dollars: The State.Minimum.Wage in 2020 dollars. - Federal.Minimum.Wage: The federal minimum wage on January 1 of Year. - Federal.Minimum.Wage.2020.Dollars: The Federal.Minimum.Wage in 2020 dollars. - Effective.Minimum.Wage: The minimum wage that is enforced in State on January 1 of Year. Because the federal minimum wage takes effect if the State's minimum wage is lower than the federal minimum wage, this is the higher of the two. - Effective.Minimum.Wage.2020.Dollars: The Effective.Minimum.Wage in 2020 dollars. - CPI.Average: The average value of the Consumer Price Index in Year. When I pulled the data from the Bureau of Labor Statistics, I selected the dataset with "all items in U.S. city average, all urban consumers, not seasonally adjusted". - Department.Of.Labor.Uncleaned.Data: The unclean, scraped value from the Department of Labor's website. - Department.Of.Labor.Cleaned.Low.Value: The State's lowest enforced minimum wage on January 1 of Year. If there is only one minimum wage, this and the value for Department.Of.Labor.Cleaned.High.Value are identical. (Some states enforce different minimum wage laws depending on the size of the business. In states where this is the case, generally, smaller businesses have slightly lower minimum wage requirements.) - Department.Of.Labor.Cleaned.Low.Value.2020.Dollars: The Department.Of.Labor.Cleaned.Low.Value in 2020 dollars. - Department.Of.Labor.Cleaned.High.Value: The State's higher enforced minimum wage on January 1 of Year. If there is only one minimum wage, this and the value for Department.Of.Labor.Cleaned.Low.Value are identical. - Department.Of.Labor.Cleaned.High.Value.2020.Dollars: The Department.Of.Labor.Cleaned.High.Value in 2020 dollars. - Footnote: The footnote provided on the Department of Labor's website. See more below.

Data Footnotes

As laws differ significantly from territory to territory, especially relating to whom is protected by minimum wage laws, the following footnotes are located throughout the data in Footnote to add more context to the minimum wage. The original footnotes can be found here.

--- Original source retains full ownership of the source dataset ---

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.

The federally mandated minimum wage in the United States is 7.25 U.S. dollars per hour, although the minimum wage varies from state to state. As of January 1, 2025, the District of Columbia had the highest minimum wage in the U.S., at 17.5 U.S. dollars per hour. This was followed by Washington, which had 16.66 U.S. dollars per hour as the state minimum wage. Minimum wage workers Minimum wage jobs are traditionally seen as “starter jobs” in the U.S., or first jobs for teenagers and young adults, and the number of people working minimum wage jobs has decreased from almost four million in 1979 to about 247,000 in 2020. However, the number of workers earning less than minimum wage in 2020 was significantly higher, at about 865,000. Minimum wage jobs Minimum wage jobs are primarily found in food preparation and serving occupations, as well as sales jobs (primarily in retail). Because the minimum wage has not kept up with inflation, nor has it been increased since 2009, it is becoming harder and harder live off of a minimum wage wage job, and for those workers to afford essential things like rent.

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 Manufacturing in the United States increased to 28.92 USD/Hour in May from 28.80 USD/Hour in April of 2025. This dataset provides - United States Average Hourly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Federal Minimum Hourly Wage for Nonfarm Workers for the United States (FEDMINNFRWG) from Oct 1938 to Jun 2025 about per hour, minimum wage, nonfarm, workers, hours, federal, wages, and USA.

Federal Hourly Minimum Wage data was reported at 7.250 USD/Hour in Apr 2025. This stayed constant from the previous number of 7.250 USD/Hour for Mar 2025. Federal Hourly Minimum Wage data is updated monthly, averaging 3.350 USD/Hour from Oct 1938 (Median) to Apr 2025, with 1039 observations. The data reached an all-time high of 7.250 USD/Hour in Apr 2025 and a record low of 0.250 USD/Hour in Sep 1939. Federal Hourly Minimum Wage data remains active status in CEIC and is reported by Federal Reserve Bank of St. Louis. The data is categorized under Global Database’s United States – Table US.G: Federal Hourly Minimum Wage.

Analysis of ‘Living Wage - Top 100 Cities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/brandonconrady/living-wage-top-100-cities on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Content

Data was pulled from a table in the following Wikipedia article: https://en.wikipedia.org/wiki/List_of_United_States_cities_by_population I used Microsoft Excel's PowerQuery function to pull the table from Wikipedia. Lists each city, its rank (based on 2020 population), some data on its area, and population in both 2020 and 2010.

Living wages are based in US Dollars per hour, assuming 2080 hours worked per year.

In addition, living wage data from http://livingwage.mit.edu I left out the minimum wage from this dataset because it appears the data is somewhat inconsistent, and often falls back on the state minimum where localities can have a higher min wage. I also omitted the poverty wage data because for the most part it seemed to be the same for most areas. One last thing to keep in mind is some cities are grouped up into metropolitan statistical areas, and as a result you will see cities that are near each other have identical data.

Banner image source: https://unsplash.com/photos/wh-7GeXxItI

--- Original source retains full ownership of the source dataset ---

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.

In this article we examine the correlation between characteristics of individuals, companies, and industries involved in low-wage labour in Germany and the risks workers face of earning hourly wages that are below the minimum-wage or low-wage thresholds. To identify these characteristics, we use the Structure of Earnings Survey (SES) 2014. The SES is a mandatory survey of companies which provides information on wages and working hours from about 1 million jobs and nearly 70,000 companies from all industries. This data allows us to present the first systematic analysis of the interaction of individual-, company-, and industry-level factors on minimum- and low-wage working in Germany. Using a descriptive analysis, we first give an overview of typical low-paying jobs, companies, and industries. Second, we use random intercept-only models to estimate the explanatory power of the individual, company, and industry levels. One main finding is that the influence of individual characteristics on wage levels is often overstated: Less than 25 percent of the differences in the employment situation regarding being employed in minimum-wage or low-wage jobs can be attributed to the individual level. Third, we performed logistic and linear regression estimations to assess the risks of having a minimum- or low-wage job and the distance between a worker’s actual earnings and the minimum- or low-wage thresholds. Our findings allow us to conclude that several determinants related to individuals appear to suggest a high low-wage incidence, but in fact lose their explanatory power once controls are added for factors relating to the companies or industries that employ these individuals.

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.

This dataset provides values for WAGES IN MANUFACTURING reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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.

This dataset provides a comprehensive overview of key economic and educational statistics in the United States, compiled from the most recent data available from 2022 to 2024. It includes information on poverty line thresholds, minimum and living wages, average and median incomes, starting and average salaries for teachers, and school enrollment rates.

This dataset is essential for exploring salary trends among the general population and educators, as well as school enrollment rates, offering a deep dive into current socioeconomic trends in the United States.

Minimum Wages in Philippines remained unchanged at 645 PHP/day in 2025 from 645 PHP/day in 2024. This dataset provides - Philippines Minimum Wages- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Sum of the full-time active positions in a title description published in alphabetical order. The Position Schedule is updated and included in the Departmental Estimates and the Supporting Schedule (updated twice a year). The minimum salary, maximum salary, mean salary and annual rate are to the dollar. This dataset is updated two times per year after publication of the Preliminary and Executive Budget, usually in January and April respectively.

Analysis of ‘Veteran Employment Outcomes’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mpwolke/cusersmarildownloadsvetcsv on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Veteran Employment Outcomes (VEO) are new experimental U.S. Census Bureau statistics on labor market outcomes for recently discharged Army veterans. These statistics are tabulated by military specialization, service characteristics, employer industry (if employed), and veteran demographics. They are generated by matching service member information with a national database of jobs, using state-of-the-art confidentiality protection mechanisms to protect the underlying data.

https://lehd.ces.census.gov/data/veo_experimental.html

Content

"The VEO are made possible through data sharing partnerships between the U.S. Army, State Labor Market Information offices, and the U.S. Census Bureau. VEO data are currently available at the state and national level."

"Veteran Employment Outcomes (VEO) are experimental tabulations developed by the Longitudinal Employer-Household Dynamics (LEHD) program in collaboration with the U.S. Army and state agencies. VEO data provides earnings and employment outcomes for Army veterans by rank and military occupation, as well as veteran and employer characteristics. VEO are currently released as a research data product in "experimental" form."

"The source of veteran information in the VEO is administrative record data from the Department of the Army, Office of Economic and Manpower Analysis. This personnel data contains fields on service member characteristics, such as service start and end dates, occupation, pay grade, characteristics at entry (e.g. education and test scores), and demographic characteristics (e.g. sex, race, and ethnicity). Once service member records are transferred to the Census Bureau, personally-identifying information is stripped and veterans are assigned a Protected Identification Key (PIK) that allows for them to be matched with their employment outcomes in Census Bureau jobs data."

Earnings, and Employment Concepts

Earnings "Earnings are total annual earnings for attached workers from all jobs, converted to 2018 dollars using the CPI-U. For the annual earnings tabulations, we impose two labor force attachment restrictions. First, we drop veterans who earn less than the annual equivalent of full-time work at the prevailing federal minimum wage. Additionally, we drop veterans with two or more quarters with no earnings in the reference year. These workers are likely to be either marginally attached to the labor force or employed in non-covered employment."

Employment

"While most VEO tabulations include earnings from all jobs, tabulations by employer characteristics only consider the veteran's main job for that year. Main jobs are defined as the job for which veterans had the highest earnings in the reference year. To attach employer characteristics to that job, we assign industry and geography from the highest earnings quarter with that employer in the year. For multi-establishment firms, we use LEHD unit-to-worker imputations to assign workers to establishments, and then assign industry and geography."

https://lehd.ces.census.gov/data/veo_experimental.html

Acknowledgements

United States Census Bureau

https://lehd.ces.census.gov/data/veo_experimental.html

Photo by Robert Linder on Unsplash

Inspiration

U.S. Veterans.

--- Original source retains full ownership of the source dataset ---

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.

In April 2025, the UK minimum wage for adults over the age of 21 in will be 12.21 pounds per hour. For the 2025/26 financial year, there will be four minimum wage categories, three of which are based on age and one for apprentice workers. Apprentices, and workers under the age of 18 will have a minimum wage of 7.55 pounds an hour, increasing to ten pounds for those aged 18 to 20. When the minimum wage was first introduced in 1999, there were just two age categories; 18 to 21, and 22 and over. This increased to three categories in 2004, four in 2010, and five between 2016 and 2023, before being reduced down to four in the most recent year. The living wage The living wage is an alternative minimum wage amount that employers in the UK can voluntarily pay their employees. It is calculated independently of the legal minimum wage and results in a higher value figure. In 2023/24, for example, the living wage was twelve pounds an hour for the UK as a whole and 13.15 for workers in London, where the cost of living is typically higher. This living wage is different from what the UK government has named the national living wage, which was 10.42 in the same financial year. Between 2011/12 and 2023/24, the living wage has increased by 4.80 pounds, while the London living wage has grown by 4.85 pounds. Wage growth cancelled-out by high inflation 2021-2023 For a long period between the middle of 2021 and late 2023, average wage growth in the UK was unable to keep up with record inflation levels, resulting in the biggest fall in disposable income since 1956. Although the UK government attempted to mitigate the impact of falling living standards through a series of cost of living payments, the situation has still been very difficult for households. After peaking at 11.1 percent in October 2022, the UK's inflation rate remained in double figures until March 2023, and did not fall to the preferred rate of two percent until May 2024. As of November 2024, regular weekly pay in the UK was growing by 5.6 percent in nominal terms, and 2.5 percent when adjusted for inflation.

Detailed Data Dictionary: https://docs.google.com/spreadsheets/d/1JKUYZYPNZfcg5Ol9LTk8fwe5hwiu7c5DSn-3Wia7mo8/edit?gid=1071313126gid=1071313126

Developed by a seasoned team of ML experts from Google, Meta, and Amazon and alumni of Stanford, Caltech, and Columbia, our AI-powered pipeline provides invaluable insights for HR tech, lead generation, market intelligence, and corporate development. With cutting-edge AI and LLMs, we transform raw job postings into actionable data, analyzing job titles, skills, predicted salaries, locations, and more.

Each posting undergoes multi-layered processing, with GPU-driven models delivering daily, weekly, and monthly data for a balanced real-time and historical view. Our processing pipeline integrates advanced AI models:

• Deduplication Model: Filters out exact and near-duplicates, ensuring unique, high-quality job data.
• Title Taxonomy Model: Categorizes over 20 million titles into 50,000 standardized groups, simplifying analysis.
• Skill & Qualification Models: Extracts hard skills, soft skills, certifications, and degrees, mapped to standard education levels and tailored by job context.
• Job Category Model: Predicts work types (remote, onsite, hybrid), seniority, and employment types (full-time, contract).
• Location Prediction Model: Parses or estimates job locations—ZIP code, city, state—using averaged lat/long values from search-based estimates for accuracy.
• Salary Estimation Model: Predicts minimum, average, and maximum salaries, using parsed and AI-predicted values for a robust salary range.
• Government Classification Models: Assigns SOC codes and titles to postings for structured role insights and regulatory compliance.
• Human Feedback Model: An in-house team of annotators reviews job descriptions and AI outputs, refining model accuracy.

Delivered through S3, FTP, and Google Drive, Canaria’s dataset provides flexibility in integration, with APIs available on request. Combining real-time AI with human validation, Canaria’s data delivers business-ready insights to meet evolving HR and market demands.

Core Industry Applications - HR & Workforce Analytics: Access insights into salary trends, workforce demographics, and skill demands to drive strategic HR decisions. - Lead Generation: Identify target leads and hiring needs through granular job postings data. - Investment & Market Intelligence: Gain insights into competitor hiring strategies and industry shifts. - Education & Skill Development: Support curriculum development and training programs based on skill trends and emerging job requirements. - Corporate Development: Align growth strategies with real-time job market data. - Talent Sourcing: Streamline talent sourcing by identifying active job markets and regions with the highest demand for specific skills. - Job Market Forecasting: Analyze hiring trends and job postings data to forecast demand for specific roles and skills. - Economic Research: Provide labor market insights for economic studies, helping to assess job growth and employment shifts by industry.