VITAL SIGNS INDICATOR Jobs by Wage Level (EQ1)

FULL MEASURE NAME Distribution of jobs by low-, middle-, and high-wage occupations

LAST UPDATED January 2019

DESCRIPTION Jobs by wage level refers to the distribution of jobs by low-, middle- and high-wage occupations. In the San Francisco Bay Area, low-wage occupations have a median hourly wage of less than 80% of the regional median wage; median wages for middle-wage occupations range from 80% to 120% of the regional median wage, and high-wage occupations have a median hourly wage above 120% of the regional median wage.

DATA SOURCE California Employment Development Department OES (2001-2017) http://www.labormarketinfo.edd.ca.gov/data/oes-employment-and-wages.html

American Community Survey (2001-2017) http://api.census.gov

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Jobs are determined to be low-, middle-, or high-wage based on the median hourly wage of their occupational classification in the most recent year. Low-wage jobs are those that pay below 80% of the regional median wage. Middle-wage jobs are those that pay between 80% and 120% of the regional median wage. High-wage jobs are those that pay above 120% of the regional median wage. Regional median hourly wages are estimated from the American Community Survey and are published on the Vital Signs Income indicator page. For the national context analysis, occupation wage classifications are unique to each metro area. A low-wage job in New York, for instance, may be a middle-wage job in Miami. For the Bay Area in 2017, the median hourly wage for low-wage occupations was less than $20.86 per hour. For middle-wage jobs, the median ranged from $20.86 to $31.30 per hour; and for high-wage jobs, the median wage was above $31.30 per hour.

Occupational employment and wage information comes from the Occupational Employment Statistics (OES) program. Regional and subregional data is published by the California Employment Development Department. Metro data is published by the Bureau of Labor Statistics. The OES program collects data on wage and salary workers in nonfarm establishments to produce employment and wage estimates for some 800 occupations. Data from non-incorporated self-employed persons are not collected, and are not included in these estimates. Wage estimates represent a three-year rolling average.

Due to changes in reporting during the analysis period, subregion data from the EDD OES have been aggregated to produce geographies that can be compared over time. West Bay is San Mateo, San Francisco, and Marin counties. North Bay is Sonoma, Solano and Napa counties. East Bay is Alameda and Contra Costa counties. South Bay is Santa Clara County from 2001-2004 and Santa Clara and San Benito counties from 2005-2017.

Due to changes in occupation classifications during the analysis period, all occupations have been reassigned to 2010 SOC codes. For pre-2009 reporting years, all employment in occupations that were split into two or more 2010 SOC occupations are assigned to the first 2010 SOC occupation listed in the crosswalk table provided by the Census Bureau. This method assumes these occupations always fall in the same wage category, and sensitivity analysis of this reassignment method shows this is true in most cases.

In order to use OES data for time series analysis, several steps were taken to handle missing wage or employment data. For some occupations, such as airline pilots and flight attendants, no wage information was provided and these were removed from the analysis. Other occupations did not record a median hourly wage (mostly due to irregular work hours) but did record an annual average wage. Nearly all these occupations were in education (i.e. teachers). In this case, a 2080 hour-work year was assumed and [annual average wage/2080] was used as a proxy for median income. Most of these occupations were classified as high-wage, thus dispelling concern of underestimating a median wage for a teaching occupation that requires less than 2080 hours of work a year (equivalent to 12 months fulltime). Finally, the OES has missing employment data for occupations across the time series. To make the employment data comparable between years, gaps in employment data for occupations are ‘filled-in’ using linear interpolation if there are at least two years of employment data found in OES. Occupations with less than two years of employment data were dropped from the analysis. Over 80% of interpolated cells represent missing employment data for just one year in the time series. While this interpolating technique may impact year-over-year comparisons, the long-term trends represented in the analysis generally are accurate.

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

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.

In March 2025, inflation amounted to 2.4 percent, while wages grew by 4.3 percent. The inflation rate has not exceeded the rate of wage growth since January 2023. Inflation in 2022 The high rates of inflation in 2022 meant that the real terms value of American wages took a hit. Many Americans report feelings of concern over the economy and a worsening of their financial situation. The inflation situation in the United States is one that was experienced globally in 2022, mainly due to COVID-19 related supply chain constraints and disruption due to the Russian invasion of Ukraine. The monthly inflation rate for the U.S. reached a 40-year high in June 2022 at 9.1 percent, and annual inflation for 2022 reached eight percent. Without appropriate wage increases, Americans will continue to see a decline in their purchasing power. Wages in the U.S. Despite the level of wage growth reaching 6.7 percent in the summer of 2022, it has not been enough to curb the impact of even higher inflation rates. The federally mandated minimum wage in the United States has not increased since 2009, meaning that individuals working minimum wage jobs have taken a real terms pay cut for the last twelve years. There are discrepancies between states - the minimum wage in California can be as high as 15.50 U.S. dollars per hour, while a business in Oklahoma may be as low as two U.S. dollars per hour. However, even the higher wage rates in states like California and Washington may be lacking - one analysis found that if minimum wage had kept up with productivity, the minimum hourly wage in the U.S. should have been 22.88 dollars per hour in 2021. Additionally, the impact of decreased purchasing power due to inflation will impact different parts of society in different ways with stark contrast in average wages due to both gender and race.

In 2024, Santa Cruz-Watsonville, California, households needed an hourly wage of almost 78 U.S. dollars to afford the rent of a two-bedroom apartment. San Francisco had one of the least affordable two-bedroom apartments, as a household would have to earn at least 64.6 U.S. dollars hourly to afford rent . These figures are considerably higher than the average minimum wage, which is in place in many states. There was no state in which a minimum wage worker could afford rent for the average two-bedroom apartment, if they only worked 40 hours a week.

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.

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

The minimum wage per day guaranteed by law in Mexico was decreed to increase by approximately 12 percent between 2024 and 2025, reaching 278.8 Mexican pesos in 2025. The Northern Free Zone located near the northern border was the exception, where the minimum daily wage increased to 419.88 Mexican pesos. Education and income disparity The income distribution is entirely a new story than minimum wages, in fact, there are many factors that influence the level of salaries for Mexican workers. One of the main differences is by the number of schooling years, someone with more than 18 years of study earns on average double than employees with seven to nine years. Moreover, the area of study, while statistics and finance mean salaries, the highest wages by degree, are above 30,000 Mexican pesos per month, others such as performing arts and theology rank as the lowest paying degrees in Mexico.
Poverty still among the main problems
Despite one of the main reasons for minimum wage increases being moving people out from poverty conditions, poverty continues to be one of the main problems Mexican society faces. The number of people living under poverty conditions has decreased by 8.54 million inhabitants from 2014 to 2022, nonetheless, the figure is still higher than 46.5 million. The poverty rate varies among states, with Chiapas leading the ranking with 67.4 percent of the population under such conditions, while both Baja California and Baja California Sur recorded less than 14 percent.

Number of employees, average hourly and weekly earnings (including overtime), and average weekly hours for the industrial aggregate excluding unclassified businesses, last 5 months.

In 2024, households in California needed an hourly wage of over 47 U.S. dollars to afford the rent of a two-bedroom apartment. Massachusetts had the second-least affordable two-bedroom apartments, as a household would have to earn at least around 45 U.S. dollars per hour in order to afford rent payments. These figures are considerably higher than the average minimum wage in place in many states. There was no state in which a minimum wage worker could afford rent for the average two-bedroom apartment, if they only worked 40 hours a week. Where are the least affordable counties and metros? The least affordable rents were predominately in Californian counties and metropolitan areas in 2024. District of Columbia has one of the highest minimum wages in the country, which stood at 17 U.S. dollars per hour as of January 2024. Thus, the affordability of two-bedroom apartments highlights how disproportionately high housing costs are in the state.

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.

Average usual hours and wages of employees (full- and part-time) by age group, gender, union coverage, job permanency, and National Occupational Classification (NOC). Data are presented for 24 months earlier, 12 months earlier and current month, as well as 24-month and year-over-year level change and percentage change.

In 2023, according to the Bureau of Labor Statistics, the hourly mean wage of nurse practitioners in the United States stood at 61.78 U.S. dollars. With an hourly mean wage of 77.66 U.S. dollars, registered nurses in California had the highest wages, followed by Nevada and Washington. On the other hand, Tennessee had the lowest hourly mean wages for nurse practitioners in 2023.

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 California City. 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 California City, the median income for all workers aged 15 years and older, regardless of work hours, was $31,591 for males and $23,120 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 27% between the median incomes of males and females in California City. With women, regardless of work hours, earning 73 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of California City.

- Full-time workers, aged 15 years and older: In California City, among full-time, year-round workers aged 15 years and older, males earned a median income of $55,000, while females earned $41,450, leading to a 25% gender pay gap among full-time workers. This illustrates that women earn 75 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in California City, showcasing a consistent income pattern irrespective of employment status.

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 California City median household income by race. You can refer the same here

This dataset represents the statewide average hourly wage of Department of Rehabilitation’s total successful closures in State Fiscal Years 2014 through 2023 by county.

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 Davis. 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 Davis, the median income for all workers aged 15 years and older, regardless of work hours, was $45,837 for males and $32,301 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Davis. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thecity of Davis.

- Full-time workers, aged 15 years and older: In Davis, among full-time, year-round workers aged 15 years and older, males earned a median income of $94,742, while females earned $73,926, leading to a 22% gender pay gap among full-time workers. This illustrates that women earn 78 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Davis, showcasing a consistent income pattern irrespective of employment status.

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

This table contains 1339 series, with data for years 1961 - 1983 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (62 items: Canada; Newfoundland and Labrador; Atlantic provinces ...), Wage earners (2 items: Average weekly hours; Average hourly earnings ...), Standard Industrial Classification, 1960 (SIC) (124 items: Mining; including milling; Metals; Gold; Copper-gold-silver ...).

This statistic is based on a survey and displays U.S. pharmacists' earnings based on hourly wage as of 2016. Some 14.5 percent of pharmacist respondents claimed to earn 51 to 55 U.S. dollars per hour. Compensation for pharmacists appears to be rising and sometimes pharmacists could also raise their take-home pay through commissions, profit-sharing, and bonuses.

Earnings of U.S. pharmacists

About 42 percent of pharmacists in the United States earn 61 to 70 U.S. dollars per hour, while 3.2 percent earn 40 U.S. dollars per hour or less. Pharmacists earn some of the highest mean hourly wages among health care practitioners and technical occupations at an average of 57.34 U.S. dollars per hour. Dental hygienists earn about 35 U.S. dollars per hour. Pharmacists have one of the highest salaries in the health care industry. Those living in Santa Cruz, California and Gadsden, Alabama, are among the highest-paid professionals in the country. Job location is an important determinant on a pharmacist’s earnings while employer and tenure have a small influence as well.

In comparison, some of the lowest paid jobs in the United States are found in the food industry, especially among employees in fast food restaurants. Within the education and health services industry, about 213,000 people are paid hourly wages that are at or below minimum wage during this year. However, overall those with more education, tend to earn a higher hourly wage.

Average full-time hourly wage paid and payroll employment by type of work, North American Industry Classification System (NAICS) and National Occupational Classification (NOC), 2016 and 2017.

Number of employees by hourly wage distributions, type of work, North American Industry Classification System (NAICS) and sex, last 5 years.