Defining low-wage work
There is no one way to define low-wage work. We follow the Organization for Economic Co-operation and Development and “social-inclusion” approaches which define low-wage work by comparing wages relative to other jobs in the labor market.[1] We define “low-wage work” as jobs that pay less than two-thirds of the median full-time wage in California. In 2022, low-wage jobs paid less than $19.69. This approach does not evaluate how much earnings a worker or their family need to be self-sufficient or maintain a basic family budget considering costs of living.
To calculate the low-wage threshold, we rely on Economic Policy Institute (EPI) extracts of the Current Population Survey (Basic Monthly) which includes Outgoing Rotation Groups (CPS-ORG).[2] Our sample includes California residents aged 18 to 64 years with non-zero wage earnings who were employed last week, but not self-employed or without pay at their main job, and usually work full time (35+ hours) at their main job. This includes those who are currently part-time or are not at work but usually work full-time.
To develop the threshold, we use an hourly wage variable constructed by EPI. For workers paid on an hourly basis, the variable is equal to their reported hourly wage. For workers paid on a weekly basis, the variable is constructed by dividing their earnings last week by the number of hours worked last week. The wage measure includes tips, overtime, and commissions and is before tax deductions. The wage variable adjusts for outliers by dropping wages less than $0.50 or greater than $100 in 1989 dollars. Because people tend to round their responses to the wage question when surveyed (e.g., saying they are paid $15.00 rather than $15.05), we smooth hourly wages with a function that randomly adds or subtracts between $0.00 and $0.25 to each hourly wage. To ensure robustness, we drop responses with imputed wages and reweigh our worker sample to account for differences in the distribution of key characteristics across the samples that include or exclude imputed wages using inverse probability weighting.[3] We then define the low-wage work threshold as earning less than two-thirds of the median full-time wage and make one final adjustment: we adjust the threshold down by 2% to account for pandemic-induced low survey response rates.[4] Our final low-wage work threshold is $19.69.
Data sources
The data explorer relies on four data sources:
- Economic Policy Institute (EPI) extracts of the 2022 Current Population Survey Outgoing Rotation Groups (CPS-ORG)[5]
- IPUMS-CPS extract of the 2022 Annual Social and Economic Supplement of the Current Population Survey (CPS-ASEC)[6]
- IPUMS-USA extract of the 2021 & 2022 American Community Survey (ACS) 1-year samples.[7] To increase sample sizes some analyses combine the 2021 and 2022 samples. In these analyses we calculate the share of workers paid low wages by inflating 2021 wages to 2022 dollars and applying the 2022 low-wage threshold.
- California Employment Development Department 2020-2030 California Long-Term Employment Projections[8]
Analytical sample
Our analytical sample(s) are used to conduct our demographic analyses of low-wage workers in California and are defined slightly differently. To understand the low-wage work workforce in California, our CPS and ACS samples generally include those aged 16[9] or older[10] with non-zero wage 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 and who lived or worked in California. Note that we include part-time workers when analyzing characteristics of the low-wage workforce. To identify workers earning below $19.69 in the CPS ASEC and ACS samples, we construct the hourly wage variable as annual earnings divided by the product of usual hours worked per week and weeks worked last year. We trim wage outliers and smooth wages by randomly adding or subtracting between $0.00 and $0.25 to each wage observation.
Racial/ethnic categories
In the Census, workers self-identify their ethnicity as “Hispanic” or non-Hispanic and then select their race (and may select more than one). We provide data for the following mutually exclusive racial/ethnic categories: Hispanic ethnicity (regardless of race), Non-Hispanic white, Non-Hispanic Black, Non-Hispanic Asian American and Pacific Islander (AAPI), Non-Hispanic American Indian and Alaska Native (AIAN) alone, and Non-Hispanic two or more races or other race (we refer to this category as multiracial/other).
Additionally, where possible, we disaggregate the broader Non-Hispanic Asian American and Pacific Islander (AAPI) category by region to include South Asian, Southeast Asian, East Asian, Pacific Islander, and “Other Asian”.[11] Any workers who identify as AAPI in combination with another racial group (e.g., Chinese and white) are classified as “multiracial/other.” See Exhibit 1 for a list of AAPI groups included in each region.
Research identifies several methods for identifying the American Indian and Alaska Native (AIAN) community.[12] The method used can result in very different estimates in population size and underlying characteristics. In an effort to provide as complete a picture as possible, we provide three methods for identifying AIAN low-wage workers. Depending on the method, we find different rates of experiences of low-wage work and differences in underlying group composition. The AIAN groups include:
- Non-Hispanic AIAN alone. This includes only those identifying as AIAN with no other race/ethnicity. This is the smallest category and most restrictive definition.
- Hispanic AIAN alone. This includes only those selecting Hispanic ethnicity and AIAN race.
- AIAN in combination with any other race or ethnicity. This is the largest and most inclusive definition. It includes all workers identifying as AIAN in combination with any other race(s) and includes Hispanic ethnicity. This method includes those captured in method 1 and method 2.
Endnotes
[1] OECD. “Earnings and Wages - Wage Levels - OECD Data,” 2022. http://data.oecd.org/earnwage/wage-levels.htm. Boushey, Heather, Shawn Fremstad, Rachel Gragg, and Margy Waller. “Understanding Low-Wage Work in the United States.” The Mobility Agenda | Center for Economic Policy and Research, 2007. https://core.ac.uk/download/pdf/6967463.pdf.
[2] Economic Policy Institute. 2024. Current Population Survey Extracts, Version 1.0.51, https://microdata.epi.org.
[3] Autor, David, Arindrajit Dube, and Annie McGrew. “The Unexpected Compression: Competition at Work in the Low Wage Labor Market.” Cambridge, MA: National Bureau of Economic Research, March 2023. https://doi.org/10.3386/w31010.
[4] Rothbaum, Jonathan, and Adam Bee. “How Has the Pandemic Continued to Affect Survey Response? Using Administrative Data to Evaluate Nonresponse in the 2022 Current Population Survey Annual Social and Economic Supplement.” U.S. Census Bureau, 2022. https://www.census.gov/newsroom/blogs/research-matters/2022/09/how-did-the-pandemic-affect-survey-response.html.
[5] Economic Policy Institute. 2024. Current Population Survey Extracts, Version 1.0.51, https://microdata.epi.org
[6] IPUMS-USA. 2022. Annual Social and Economic Supplement of the Current Population Survey. https://cps.ipums.org/cps/
[7] IPUMS-USA. 2022. American Community Survey. https://usa.ipums.org/usa/
[8] EDD. “Long Term Occupational Projections (Ten-Years) 2020-2030,” 2022. https://labormarketinfo.edd.ca.gov/data/employment-projections.html.
[9]We include 16-17 year olds due to recent increased labor force participation among 16-19 year olds and substantial recent wage growth among young non-college workers. (see Autor, David, Arindrajit Dube, and Annie McGrew. “The Unexpected Compression: Competition at Work in the Low Wage Labor Market.” Cambridge, MA: National Bureau of Economic Research, March 2023. https://doi.org/10.3386/w31010. and Lafortune, Julien, and Sarah Bohn. “Young Californians May Be Choosing Work over School.” Public Policy Institute of California, 2023. https://www.ppic.org/blog/young-californians-may-be-choosing-work-over-school/. PPIC).
[10] Employment research often includes only “prime-age” workers aged 25 to 54; however, we elect to include older workers in our analysis to understand low-wage work throughout the life course.
[11] Our approach to disaggregating Asian American/Pacific Islanders is similar to the National Equity Atlas (See National Equity Atlas. “Data and Methods | Examining the Geography of Opportunity for Asian Americans and Pacific Islanders in Metro America,” 2023. https://nationalequityatlas.org/neighborhood-affordability-for-AAPI-renters/methodology.)
[12] Brundage Jr., Vernon. “A Profile of American Indians and Alaska Natives in the U.S. Labor Force : Monthly Labor Review: U.S. Bureau of Labor Statistics.” Bureau of Labor Statistics, 2023. https://www.bls.gov/opub/mlr/2023/article/a-profile-of-american-indians-and-alaska-natives-in-the-us-labor-force.htm. CA Consortium for Urban Indian Health, California Native Vote Project, and Advancement Project California. “We the Resilient: Stories and Data from American Indians and Alaska Natives in California.” Accessed May 28, 2024. https://canativevote.org/what-we-do/research/. Urban Indian Health Institute. “Best Practices for American Indian and Alaska Native Data Collection,” 2020. https://www.uihi.org/resources/best-practices-for-american-indian-and-alaska-native-data-collection/. Villegas, Malia, Amber Ebarb, Sarah Pytalski, and Yvette Roubideaux. “Disaggregating American Indian & Alaska Native Data: A Review of Literature,” 2016. https://www.policylink.org/sites/default/files/AIAN-report.pdf.
