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HomePublicationsTool/ResourceLow-Wage Work in California Data Explorer

Low-Wage Work in California Data Explorer

May 12, 2022 - 

Press Coverage

Use this site to explore a wide range of data on California’s low-wage workers: numbers of workers, demographics, job quality, occupations, industries, economic security indicators, geography, and more.

Click on the title bars to expand each section.

For a more detailed tutorial on how to navigate this Data Explorer, please view the user guide.

The Low-Wage Work in California Data Explorer offers an in-depth look at the people who make up California’s low-wage workforce and provides users with graphics, tables, research summaries, interactive visualizations, and downloadable data. The explorer provides a wide range of information on the state’s low-wage workforce, including demographics, job characteristics, industries, occupations, use of public assistance programs, and geography.

Data analysis was done by Kuochih Huang, Enrique Lopezlira, and Ken Jacobs. Graphics were done by Sandy Olgierson.

This project was made possible by grants from The James Irvine Foundation and The California Wellness Foundation.

Number of low-wage workers in California
Defining low-wage work
Growing inequality

  • Almost one out of every three California workers earns low wages

  • 30% of California workers earned less than $18.02 in 2021

  • That translates into 4,300,000 low-wage workers

Definition

We define low-wage workers as those earning less than two-thirds of the median full-time wage in California.

In 2021, this means workers making less than $18.02 per hour are considered low-wage workers. This low-wage threshold is higher than in previous years, due to the high number of low-wage jobs lost during the pandemic, coupled with wage growth over this period, which resulted in a higher median full-time wage. See the Data and Methods section for more details.

Sample

We limit this analysis to California workers, ages 18-64, who were not self-employed. See the Data and Methods section for more details.

  • Since the mid 1990’s, workers at the bottom and in the middle of the wage distribution have seen their earnings rise in real terms (after adjusting for inflation) much more slowly than high-wage workers.

Age
Education
Race and ethnicity
Gender
Rates of low-wage work
  • The large majority of California’s low-wage workers are adults, not teens.
  • The average age for low-wage workers is 36, compared to 40 for all workers.
  • California’s low-wage workers are now older than they were in previous decades.

  • California’s low-wage workers are less educated than the overall workforce.
  • But, 45% have at least some college experience, and about one in seven has a bachelor’s or advanced degree.
  • California’s low-wage workers are more educated now than in past decades.
  • Between 1994 and 2021 the percentage without a high school degree declined by over one-third, while the percentage with some college or a college degree increased by almost one-fourth.

  • Workers of color constitute the majority of California’s workforce.
  • This is especially true for the state’s low-wage workers: for example, 58% are Latinx, compared with 41% of all workers.
  • A higher proportion of California’s low-wage workforce is foreign born (36%) as compared to the proportion of all workers (31%).

  • Overall, more than half of California’s low-wage workers are women, and this is true across all demographic groups.

  • It is also useful to examine the proportion of low-wage workers within major demographic groups (i.e., the rate of low-wage work).
  • Rates of low-wage work are above average among younger workers, women, Latinx, black, and foreign-born workers.
  • Workers without a college degree also have high rates of low-wage work.

Family earnings
Workers' share of family earnings
Family poverty level
Family structure
Economic insecurity for families
Other effects of low wages
  • Even when combining the wages of all workers in the family, the median family earnings of California’s low-wage workers is $40,000, just a little over half of the state’s overall median.
  • Low-wage workers’ earnings make up a majority (60%) of their family’s overall earnings.
  • About four out of 10 low-wage workers are the sole earner in their family (roughly the same as the workforce as a whole).

  • Low-wage workers’ earnings make up a majority (60%) of their family’s overall earnings.
  • About four out of 10 low-wage workers are the sole earner in their family (roughly the same as the workforce as a whole).

  • Low-wage workers are much more likely to live in families with earnings below the Federal Poverty Level (FPL) as compared to the overall California workforce.
  • About half of low-wage workers live in families with earnings under 200% of the FPL.

  • 42% of low-wage workers have children, and 44% are married.

  • Low-wage workers’ families are more likely to have children receiving free or reduced-price school lunch, to have a family member enrolled in Medi-Cal, and to be rent burdened.

Many low-wage working families rely on public assistance to make ends meet

When jobs don’t pay enough, workers turn to public assistance in order to meet their basic needs. The taxpayers bear a significant portion of the hidden costs of low-wage work in the United States.

Low wages negatively affect the physical and mental health of workers

All else equal, low wages (and in turn poverty) results in increased rates of illness, as well as greater likelihood of premature death. Earning low wages also leads to poor mental health, including heightened stress and anxiety, and reduced cognitive functioning.

Parents’ earnings affect the physical and mental health of their children

Several studies have found that an increase in family income reduces the likelihood of low birth weight and poor mental health among children. Higher wages are also associated with reduced rates of parental neglect and mistreatment.

  • Randall Akee et al., “How Does Household Income Affect Child Personality Traits and Behaviors?,” American Economic Review 108, no. 3 (March 2018): 775–827, https://doi.org/10.1257/aer.20160133.
  • Kerri M. Raissian and Lindsey Rose Bullinger, “Money Matters: Does the Minimum Wage Affect Child Maltreatment Rates?,” Children and Youth Services Review, Economic Causes and Consequences of Child Maltreatment, 72 (January 1, 2017): 60–70, https://doi.org/10.1016/j.childyouth.2016.09.033.
  • Hilary Hoynes, Doug Miller, and David Simon, “Income, the Earned Income Tax Credit, and Infant Health,” American Economic Journal: Economic Policy 7, no. 1 (February 2015): 172–211, https://doi.org/10.1257/pol.20120179.
  • E. Jane Costello et al., “Relationships between Poverty and Psychopathology: A Natural Experiment,” JAMA 290, no. 15 (October 15, 2003): 2023–29, https://doi.org/10.1001/jama.290.15.2023.

Parents’ earnings affect the future economic prospects of their children

Children from low-income families earn less and work fewer hours as adults. Children with access to greater economic resources before age five experience better educational attainment, greater adult economic self-sufficiency, and an increase in longevity.

  • Bailey, Martha J. et al., “Is the Social Safety Net a Long-Term Investment? Large-Scale Evidence from the Food Stamps Program,” Working Paper (National Bureau of Economic Research, April 2020), https://www.nber.org/papers/w26942.
  • Randall Akee et al., “How Does Household Income Affect Child Personality Traits and Behaviors?,” American Economic Review 108, no. 3 (March 2018): 775–827, https://doi.org/10.1257/aer.20160133.
  • Chloe N. East, “The Effect of Food Stamps on Children’s Health: Evidence from Immigrants’ Changing Eligibility,” Journal of Human Resources, September 5, 2018, 0916-8197R2, https://doi.org/10.3368/jhr.55.3.0916-8197R2.
  • Jacob Bastian and Katherine Michelmore, “The Long-Term Impact of the Earned Income Tax Credit on Children’s Education and Employment Outcomes,” Journal of Labor Economics 36, no. 4 (February 20, 2018): 1127–63, https://doi.org/10.1086/697477.
  • Hilary Hoynes, Diane Whitmore Schanzenbach, and Douglas Almond, “Long-Run Impacts of Childhood Access to the Safety Net,” American Economic Review 106, no. 4 (April 2016): 903–34, https://doi.org/10.1257/aer.20130375.

Public policies and other measures that increase wages can be expected to improve outcomes for families of all races while also reducing racial disparities.

Median hourly wages in California
Median annual earnings in California
Full-time/part-time status for California workers
Full-year/part-year status
Percentage of California workers in a union
Percentage of workers in California with employer sponsored health or retirement benefits
Other dimensions of low-wage jobs
  • The median wage for low-wage workers was $14.91 per hour in 2021, about 60% of the median hourly wage for all California workers.

  • Median annual earnings for low-wage workers in California were $25,000 in 2021, and only $12,000 for part-time workers.
  • Even when working full time, median earnings for low-wage workers only reached $27,000.

  • Low-wage workers are twice as likely to work part time (defined as less than 35 hours per week) compared to the overall California workforce.

  • Not only are low-wage workers more likely to work part time, they’re also more likely to work part year (less than 50 weeks) compared to the overall workforce.
  • The result is that just over half of low-wage workers have full-time, full-year jobs.

  • Low-wage workers are less likely to be members of a union, or covered by a union contract, compared to the overall California workforce.

  • Low-wage workers are less likely to receive health insurance or retirement benefits from their employer.

Wage theft

Each year millions of workers across the country are victims of wage theft—meaning they are paid less than the full wages to which they are legally entitled. Wage theft takes various forms, including minimum wage violations, overtime violations, and off-the-clock violations.

Ihna Mangundayao et al., “More than $3 Billion in Stolen Wages Recovered for Workers between 2017 and 2020” (Economic Policy Institute, December 22, 2021), 3, https://www.epi.org/publication/wage-theft-2021/.

David Cooper and Teresa Kroeger, “Employers Steal Billions from Workers’ Paychecks Each Year: Survey Data Show Millions of Workers Are Paid Less than the Minimum Wage, at Significant Cost to Taxpayers and State Economies” (Economic Policy Institute, May 10, 2017), https://www.epi.org/publication/employers-steal-billions-from-workers-paychecks-each-year/.

Ruth Milkman, Ana Luz González, and Victor Narro, “Wage Theft and Workplace Violations in Los Angeles: The Failure of Employment and Labor Law for Low-Wage Workers” (UCLA Institute for Research on Labor and Employment, 2010), http://ccaucla-laborcenter.electricembers.net/wp-content/uploads/downloads/2014/04/LAwagetheft.pdf.

The non-compete agreements

Non-compete contracts prohibit workers from taking similar positions at a new employer or starting a competing business, limiting the ability of workers to negotiate wage increases or improve their employment situation. A recent report based on a 2017-2018 national sample found more than one in ten lower-wage workers are subject to non-compete contracts. Another recent study finds that non-compete contracts reduce the wages for low-wage workers by 2 to 3%.

Michael Lipsitz and Evan Starr, “Low-Wage Workers and the Enforceability of Noncompete Agreements,” Management Science 68, no. 1 (January 2022): 143–70, https://doi.org/10.1287/mnsc.2020.3918.

Tyler Boesch, Katherine Lim, and Ryan Nunn, “Non-Compete Contracts Sideline Low-Wage Workers” (Federal Reserve Bank of Minneapolis, October 15, 2021), https://www.minneapolisfed.org:443/article/2021/non-compete-contracts-sideline-low-wage-workers.

Unpredictable and “on call” schedules

In a national sample of both hourly and salaried workers in 2016, the large majority of low-wage workers had fluctuations in their work hours (79.2% for hourly workers and 81.6% for salaried workers), and more than one-third (36%) received one week or less advanced notice of scheduling changes. Unpredictable schedules are associated with greater psychological distress and poor sleep quality, as well as increased school absences and greater behavioral challenges for workers’ children.

Susan J. Lambert, Julia R. Henly, and Jaeseung Kim, “Precarious Work Schedules as a Source of Economic Insecurity and Institutional Distrust,” RSF: The Russell Sage Foundation Journal of the Social Sciences 5, no. 4 (September 1, 2019): 218–57, https://doi.org/10.7758/RSF.2019.5.4.08.

Dani Carrillo et al., “Instability of Work and Care: How Work Schedules Shape Child-Care Arrangements for Parents Working in the Service Sector,” Social Service Review 91, no. 3 (September 2017): 422–55, https://doi.org/10.1086/693750.

Susan J. Lambert, Peter J. Fugiel, and Julia R. Henly, “Precarious Work Schedules among Early-Career Employees in the US: A National Snapshot” (University of Chicago EINet, 2014), https://crownschool.uchicago.edu/sites/default/files/uploads/lambert.fugiel.henly_.precarious_work_schedules.august2014_0.pdf.

Saru Jayaraman, “Shelved: How Wages and Working Conditions for California’s Food Retail Workers Have Declined as the Industry Has Thrived” (UC Berkeley Food Labor Research Center, June 1, 2014), https://laborcenter.berkeley.edu/shelved-how-wages-and-working-conditions-for-californias-food-retail-workers-have-declined-as-the-industry-has-thrived/.

Daniel Schneider and Kristen Harknett, “Consequences of Routine Work-Schedule Instability for Worker Health and Well-Being,” American Sociological Review 84, no. 1 (February 1, 2019): 82–114, https://doi.org/10.1177/0003122418823184.

Elaine Zundl et al., “Still Unstable: The Persistence of Schedule Uncertainty During the Pandemic” (The Shift Project, January 27, 2022), https://shift.hks.harvard.edu/still-unstable/.

Industries
Rates of low-wage work by industry
Occupation groups
Rates of low-wage work by occupation group
Common low-wage detailed occupations
Independent contracting and gig workers
Employment projections by industry
Employment projections by occupations
Employment projections by educational requirement
  • Low-wage workers are employed throughout California’s economy, but retailers and restaurants alone account for almost one-third (31%) of the state’s low-wage workers. (Industry is a category that describes what the business does.)

  • California industries that have high rates of low-wage work include some parts of the service sector (such as restaurants, retail, hotels, and home care and child care services), as well as some parts of the goods-producing sector (such as agriculture and non-durable manufacturing).

  • Low-wage workers are employed in all major occupations, but three groups—office and administrative support, sales, and food preparation and serving occupations—account for almost 40% of California’s low-wage workers. (Occupation is a category that describes what the worker does.)

  • California occupations that have high rates of low-wage work include service jobs (such as food preparation workers, home care workers, and janitors), as well as jobs in the goods-producing sector (such as farm workers and warehouse workers).

  • Almost one-third of low-wage workers are employed in these 10 occupations.
  • Retail sales workers, personal care aides, and cooks and food preparation workers are the most common low-wage occupations.

Independent contracting was the sole source of income for 8.6% of Californian workers in 2016, and an additional 9.7% combined independent contracting and W2 work.

The large majority of workers in California are W2 workers. In 2016, 81.7% held only a traditional W2 job. Independent contracting was the sole source of income for 8.6% of workers during that year, and another 9.7% combined independent contracting and traditional W2 work. The proportion of workers with any independent contracting income in California showed minimal change between 2014 and 2016.

Independent contractors work throughout California’s economy, but the industry profile of independent contracting varies by the level of earnings.

Independent contractors with low earnings are more likely to work in industries such as personal services, janitorial services, and landscaping. Independent contractors with higher earnings are more likely to work in industries such as professional services, transportation, construction, and real estate. Workers who are engaged in only independent contracting report substantially lower earnings than either W2-only workers or mixed-income workers.

Only a small proportion of the workforce are gig workers, and these workers often earn subminimum wages.

The proportion of the workforce actively using on-demand labor platforms to earn money is very small—only 1.4% of workers reported earnings from on-demand labor platforms (like Uber) in 2016. Other studies using accurate measures have arrived at very similar estimates.

Independent studies of on-demand platform (UBER and LYFT) drivers in California find that these workers earn below the state minimum wage after accounting for waiting time and expenses.

  • Official employment projections to 2028 do not show a substantial change in California’s industry mix, meaning that our state’s low-wage occupational and industry configuration will continue into the foreseeable future.

  • Between 2018 and 2028, many projected high-growth occupations in California are also the occupations with high shares of low-wage jobs, such as personal care aides and food preparation and serving occupations.

  • Official projections show no meaningful change by 2028 in the distribution of employment by occupations’ required education for an entry-level job.

Rates of low-wage work by workplace county
Where low-wage workers work
Rates of low-wage work by residence county
Where low-wage workers live
  • Jobs in the Central Valley and far Northern California are more likely to pay low wages than jobs in other parts of the state.
  • On the other hand, jobs in the Bay Area are less likely to pay low wages, but the low-wage measure is not adjusted for regional differences in the cost of living.

  • California’s low-wage jobs are concentrated in Los Angeles County, with 29% of low-wage jobs located in that county.

  • Workers who live in far Northern California and the Central Valley are more likely to earn low wages.
  • Workers living in the Bay Area are less likely to earn low wages, but the low-wage measure is not adjusted for regional differences in the cost of living.

  • Although jobs in the Central Valley and far Northern California are more likely to pay low wages, over one third of low-wage workers reside in Southern California.
  • Despite these trends, the low-wage measure is not adjusted for regional differences in the cost of living.

First 12 months unemployment
First 12 months unemployment by gender
Employment change by industry
  • Compared to all workers, low-wage workers were more likely to lose their jobs at some point during the first 12 months of the pandemic.

  • Female low-wage workers were more likely than both male low-wage workers and female workers overall to lose their jobs during the pandemic.

  • Industries that have higher rates of low-wage jobs suffered the most job loss during the pandemic.

Data sources

The data explorer uses four data sources:

  • Economic Policy Institute (EPI) extracts of the Current Population Survey (Basic Monthly which includesOutgoing Rotation Groups (CPS-ORG)), 1994-2021
  • IPUMS-CPS extract of the Annual Social and Economic Supplement of the Current Population Survey (CPS-ASEC), 2021
  • IPUMS-USA extract of the American Community Survey (ACS) 1-year sample, 2019
  • Current Employment Statistics (CES), from February 2020 to February 2022

Sample definition

Due to differences in data availability in the three sources used for analyses of workers (first three bullets, above), each dataset has a slightly different sample definition.

The ACS sample is restricted to 18-64 year olds, with non-zero earnings in the past year, who were not self-employed or unpaid family workers, and who were at work last week or had a job but were not at work last week. The ACS sample only includes individuals who live and work in the state of California.

Neither of the CPS datasets identifies the respondent’s place of work; therefore,for each of those datasets our sample is defined as California residents age 18-64 years, with non-zero earnings either last week (CPS-ORG) or last year (CPS-ASEC), who were employed last week, but not self-employed.

When calculating wages using both the ACS and CPS, we trimmed wage outliers by dropping hourly wages less than $0.50 or greater than $100 in 1989 dollars (see below “Defining low wage”).

Defining low wage

Low wage is defined as earning two-thirds of the median full-time wage. Differences in data availability affect the construction of the hourly wage variable in our three datasets.

In the CPS-ORG, we use an hourly wage variable constructed by EPI. Specifically, for workers paid on an hourly basis, the variable is equal to their actual reported hourly wage. For workers paid on a weekly basis, the variable is constructed by dividing their earnings last week by the numbers of hours worked last week. In both cases, the wage measure used to determine low wages includes tips, overtime, and commissions, before tax deductions.

The CPS-ASEC does not include an hourly or weekly earnings measure; we therefore construct the hourly wage measure by dividing the worker’s annual earnings by the product of usual hours worked per week and weeks worked last year. The CPS-ASEC earnings variable includes all income from the worker’s job, including pay from tips, overtime, and commissions, before tax deductions.

The ACS hourly wage variable was also calculated as annual earnings divided by the product of usual hours worked per week and weeks worked last year.[1] The ACS annual earnings variable includes wages, salary, commissions, cash bonuses or tips from all jobs, before tax deductions.

For each dataset, we trimmed hourly wage outliers by dropping wages less than $0.50 or greater than $100 in 1989 dollars.[2] We then smoothed the hourly wages with a function that randomly adds or subtracts between $0.00 and $0.25 to each hourly wage. Finally, we adjusted wages from previous years to 2021 dollars using the California Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W).

We used the CPS-ORG dataset to calculate the low-wage threshold, which then is applied to CPS-ASEC and ACS. We set the hourly wage threshold at two-thirds of the median full-time wage, a widely used metric.[3] We adjusted the 2021 threshold, based on a benchmark analysis by the US Census,[4] to account for the low-response rates in these surveys during the pandemic. The final value of the threshold was $18.02 in 2021. During the pandemic, more low-wage workers than high-wage workers lost jobs. This is known as a compositional effect, which pushed up the median full-time wage, and therefore also the low-wage threshold, higher than they would have been absent a pandemic.

Notes

[1] Since the ACS surveys respondents over the course of the year and asks about earnings in the previous 12 months, we apply the ACS-provided adjust variable to convert the reported earnings to real dollars.

[2] This step follows the methodology from: Economic Policy Institute, “Methodology for Measuring Wages and Benefits,” State of Working America Data Library, February 21, 2019, https://www.epi.org/data/methodology/.

[3] OECD, “Earnings and Wages – Wage Levels – OECD Data,” theOECD, accessed April 19, 2022, http://data.oecd.org/earnwage/wage-levels.htm. Heather Boushey et al., “Understanding Low-Wage Work in the United States,” The Mobility Agenda (Inclusion; Center for Economic Policy and Research, March 2007), https://core.ac.uk/download/pdf/6967463.pdf.

[4] Jonathan Rothbaum and Charles Hokayem, “How Did the Pandemic Affect Survey Response: Using Administrative Data to Evaluate Nonresponse in the 2021 Current Population Survey Annual Social and Economic Supplement” (United States Census Bureau, September 14, 2021), https://www.census.gov/newsroom/blogs/research-matters/2021/09/pandemic-affect-survey-response.html.