The Public Cost of Low-Wage Jobs in California’s Construction Industry

Ken Jacobsand Kuochih Huang


In California, the question of whether and under what conditions labor standards requirements should be included in housing bills typically hinges on the issue of how much it would add to the cost of the project.[1] However, one important aspect of cost has so far not been considered: the cost to the public safety net resulting from low-road employment practices common in residential construction. Our analysis calculates the cost of utilization of the five major means-tested safety net programs by California construction workers and their families. We find almost half of families of construction workers in California are enrolled in a safety net program at an annual cost of over $3 billion. By comparison, just over a third of all California workers have a family member enrolled in one or more safety net program.

Taking the Low Road in Residential Construction

Construction is a large, vital industry in California, accounting for $107 billion in personal income in 2020, or about $1 out of every $25 of total statewide earnings.[2] In both California and nationally, construction is a bifurcated industry, separated into two subsectors with strikingly different working conditions: a high wage, often unionized nonresidential construction sector, and a low-wage, often exploitative residential construction sector.

Ormiston et al. (2020)[3] explain the structural reasons for the development of such contrasting industry subsectors, including the complexity of nonresidential projects and the lack of barriers to entry in the residential sector.[4] The structural features of the residential sector incentivized a race to the bottom, and employers are now governed by the operating principle to “reduce labor costs through whatever means possible.”[5]

Ormiston et al. discuss the many ways, both legal and illegal, that employers in residential construction minimize their labor costs. Legally, workers are typically paid low wages with minimal or no benefits. Construction contractors have reported in government employer surveys that wages are more than 30% higher for nonresidential construction workers than for workers in the residential sector, and the value of fringe benefits is more than triple.[6]

The use of illegal employment practices—primarily misclassification and paying under the table—to minimize labor costs is “rampant” in many parts of the residential construction sector, according to Ormiston et al.[7] The Economic Roundtable reported that in 2011 an estimated 19% of California construction workers who were independent contractors were misclassified; these workers earned only 67 cents for every dollar earned by comparable workers with employee status.[8] Construction workers in frequently misclassified occupations in California earned a median wage of just $14.98 in 2017.[9] Workers paid under the table are even more disadvantaged, earning just 52 cents for every dollar earned by workers with employee status.[10] The Economic Roundtable found that overall 16% of construction jobs in California were held by “informal” workers; one-third of these were misclassified and two-thirds were being paid under the table. A disproportionate share of the workers in residential construction are undocumented immigrants—13% nationally in 2014[11]–who may fear reprisals for speaking up for their rights.

Other strategies for illegally reducing labor expenses include ignoring health and safety requirements, and devising ways to underpay workers’ compensation insurance premiums, practices especially troubling given the fact that, per employer surveys, less than half of residential construction workers are provided health insurance through their jobs.[12]

When workers do not earn enough money to meet their basic needs, they often turn to safety net programs to make up the difference. In this brief we will estimate the public cost to California and the federal government from the use of safety net programs by construction workers and their families in California.

Data and Methods

We examine California construction workers’ and their families’ utilization of the five largest means-tested safety net programs for which data are available: Medicaid; Children’s Health Insurance Program (CHIP); basic household income assistance under Temporary Aid for Needy Families (TANF); Earned Income Tax Credit (EITC); and Supplemental Nutrition Assistance Program (SNAP). Responsibility for funding the health programs is shared by California and the federal government. We include only the cash assistance portion of TANF, and this program too receives funding from both California and the federal government. While there is a state-level EITC program, in this analysis we include only the federal EITC. The federal government alone funds SNAP. We analyze only programs that function as income supplements, omitting job-training, housing cost assistance, educational, and other programs that indirectly assist low-income families.

To calculate the numbers of working families who participated in safety net programs, we restrict the sample to those who work 27 or more weeks per year and 10 or more hours per week in all industries in California. We exclude observations who live in institutional group quarters. To identify construction workers, we further use the 1990 Census Bureau industrial code All Construction (60), and the 2010 Census Bureau occupation codes from First-Line Supervisors of Construction Trades and Extraction Workers (6200) to Construction Workers, n.e.c. (6765), and we include W2 workers and the not-incorporated self-employed but exclude the incorporated self-employed.

We mainly rely on four sources of data: the US Census Bureau’s American Community Survey (ACS), the March Supplement of the US Bureau of Labor Statistics Current Population Survey (CPS), the US Bureau of Labor Statistics Occupational Employment Statistics (OES), and administrative data from the Medicaid, CHIP, TANF, EITC, and SNAP programs. Medicaid figures exclude aged, blind, and disabled enrollees. The ACS surveys a large number of respondents and asks them about their work history, income, and family structure. The March Supplement, also known as the Annual Demographic Supplement, asks respondents about receipts of cash and noncash transfer payments during the past year and includes questions about the programs we examine in this analysis.

However, survey databases like the ACS and CPS frequently have safety net program utilization counts that differ from program administrative data. We adjusted the CPS so that its program utilization estimates match the program administrative data. The CPS does not provide a large enough sample size to accurately estimate program utilization for construction workers at the state or county levels. The ACS does have sufficient sample size for this analysis but lacks specific questions about program utilization, and its occupational employment counts differ from more accurate data like the OES. On the other hand, while the OES has accurate employment counts for wage workers, it does not include independent contractors. To overcome these issues, we built a model using CPS data to predict program utilization based on income, demographics, and family structure. We then used that model to impute program utilization onto the ACS data. We calculated the ratio of wage workers to non-incorporated self-employed workers based on the ACS and used it to adjust the OES data for non-incorporated self-employed workers, and then adjusted the employment counts in the ACS to match the adjusted OES data. Finally, we used that imputed and adjusted ACS data to analyze safety net program utilization in families of construction workers.

For a detailed explanation of methodology, please see Appendix A: Methodology from Fast Food, Poverty Wages: The Public Cost of Low-Wage Jobs in the Fast-Food Industry.[13]

Note that the data do not allow us to separate residential from nonresidential construction workers for this analysis. Our results apply to California construction workers as a whole. Given what we know about differences in employment practices in the two subsectors, it is likely that program utilization rates among residential construction workers and their families are higher than we find here. Further research would be needed to confirm if this is correct.


Table 1 shows the annual enrollment of California construction workers and their families in safety net programs between 2015 and 2019. Almost half (48%) of construction working families are enrolled in one or more of the five means-tested programs we examine. Of particular note, almost one-third receive Adult Medicaid benefits (31%) and/or EITC (32%).

Compared to ALL working families in California, construction working families are significantly more likely to participate in safety net programs: 48% of construction working families compared to 36% of all working families. Construction working families participate at higher rates in each of the five programs individually as well.

Overall, construction working families are one-third more likely than all working families to participate in one or more means-tested safety net programs in California.

Table 1. Annual Enrollment in Safety Net Programs for Working Families, CA, 2015-2019

Number of Construction Working Families Enrolled
Share of Construction Working Families Enrolled
Share of ALL Working Families Enrolled
Adult Medicaid 200,000 31% 24%
Children's Medicaid/CHIP 140,000 21% 13%
EITC 220,000 32% 21%
TANF 20,000 3% 2%
SNAP 120,000 18% 12%
Any program 330,000 48% 36%

Source: Authors’ calculations based on the 2015-2019 American Community Survey, 2016–2020 March Current Population Survey, 2019 Occupational Employment Statistics, and administrative data from Medicaid, CHIP, EITC, SNAP, and TANF programs.
Note: The analysis is restricted to workers who work at least 27 weeks in a year and 10 or more hours per week


In Table 2 we see the annual combined California and federal spending on safety net programs for all working families and for construction working families between the years 2015-2019. In total, $38.3 billion is spent on the participation of all working families in the five programs, and $3.4 billion is spent on construction working families.

Construction workers account for almost 9% of the total safety net expenditures for all California working families.[14]

Table 2. Annual State and Federal Spending on Safety Net Programs for Working Families, CA, 2015-2019 (2019 dollars)

Amount Spent on Construction Working Families
Amount Spent on ALL Working Families
Adult Medicaid/CHIP 1,580,000,000 19,890,000,000
Children's Medicaid/CHIP 830,000,000 7,130,000,000
EITC 570,000,000 6,540,000,000
TANF 60,000,000 900,000,000
SNAP 310,000,000 3,810,000,000
All Programs 3,350,000,000 38,250,000,000

Source: Authors’ calculations based on the 2015-2019 American Community Survey, 2016–2020 March Current Population Survey, 2019 Occupational Employment Statistics, and administrative data from Medicaid, CHIP, EITC, SNAP, and TANF programs.
Note: The analysis is restricted to construction workers who work at least 27 weeks in a year and 10 or more hours per week.


Table 3 presents the health insurance coverage status of construction workers and all workers in California. One-quarter (26%) of California construction workers lack health insurance. The rate at which California construction workers lack health insurance is more than two and a half times the rate for all California workers (10%).

Table 3. Health insurance coverage of all workers and construction workers, CA, 2015-2019

Construction Workers
All Workers
No health insurance coverage 26% 10%
With health insurance coverage 74% 90%

Source: Authors’ analysis of 2015-2019 IPUMS American Community Survey (ACS) data.
Note: BTCW worker definition: ind1990==60 & occ2010>=6200 & occ2010<=6765

Determining the cost of uninsurance in California, let alone the cost for uninsured construction workers, is complicated and inexact, and beyond our scope. Suffice to say that along with the negative impact on construction workers’ wellbeing, uninsurance creates additional expenses for the state, counties, and federal government. The Kaiser Family Foundation reports that in the years 2015-2017, uncompensated health care costs for the uninsured nationwide averaged $42.4 billion per year, with the public picking up around 80% of these costs.[15]


The low wages and exploitative practices in the resident construction industry cause profound hardship for workers and their families. It also costs the public. When employers misclassify their workers or pay them under the table, they are defunding and defrauding government programs, including workers’ compensation, Social Security, and Medicare. Misclassification costs state and federal coffers at least $3,000 annually for every worker that is misclassified.[16] The lack of both employer-provided insurance and access to workers’ compensation leaves many residential construction workers uninsured. And, as found in this analysis, low-road employment practices cause above-average utilization of safety net programs by California construction working families.

A top priority for the Newsom Administration is contending with the affordable housing and homelessness crisis. When the state makes decisions related to prevailing wage standards on residential housing construction it is important to consider the array of costs of low-wages, few benefits, and other low-road practices in the residential construction market.


[1] Matt Hinkel and Dale Belman, “Should Prevailing Wages Prevail? Reexamining the Effect of Prevailing Wage Laws on Affordable Housing Construction Costs” (Institute for Construction Economic Research, 2021),

[2] U.S. Bureau of Economic Analysis, Regional Data, GDP and Personal Income, “Private nonfarm earnings: Construction,” 2020.

[3] Russell Ormiston, Dale Belman, Julie Brockman, and Matt Hinkel (2020). “Rebuilding Residential Construction.” in Paul Osterman ed., Creating Good Jobs: An Industry-Based Strategy, pp. 75-113. Cambridge: The MIT Press.

[4] Ormiston et al., “Rebuilding Residential Construction,” pp. 76-80.

[5] Ormiston et al., “Rebuilding Residential Construction,” p. 76.

[6] Scott Littlehale, “Rebuilding California: The Golden State’s Housing Workforce Reckoning” (Smart Cities Prevail, January 2019),

[7] Ormiston et al., “Rebuilding Residential Construction,” p. 76.

[8] Yvonne Yen Liu and Daniel Flaming, “Sinking Underground: The Growing Informal Economy in California Construction” (Economic Roundtable, September 2014),

[9] These occupations were carpet installer, laborer, painter, or construction helper. Ratna Sinroja, Sarah Thomason, and Ken Jacobs, “Misclassification in California: A Snapshot of the Janitorial Services, Construction, and Trucking Industries” (UC Berkeley Center Labor Center, March 2019),

[10] Liu and Flaming, “Sinking Underground: The Growing Informal Economy in California Construction.”

[11] Jeffrey S. Passel and D’Vera Cohn, “Size of U.S. Unauthoriized Immigrant Workforce Stable After the Great Recession” (Pew Research Center, November 3, 2016),

[12] Littlehale, “Rebuilding California: The Golden State’s Housing Workforce Reckoning.”

[13] Sylvia Allegretto et al., “Fast Food, Poverty Wages: The Public Cost of Low-Wage Jobs in the Fast-Food Industry” (UC Berkeley Labor Center), accessed December 8, 2020,

[14] Based on 2019 ACS data, the estimated number of construction workers is 755,000, the estimated number of all California workers is 17,675,000. Note: 2019 ACS (1 year sample) extracted via IPUMS-USA, Includes only individuals who worked at least 27 weeks for at least 10 hours per week over the twelve months prior to being surveyed. Construction workers do not include extraction occupations and incorporated self-employed workers.

[15] Teresa A. Coughlin, Haley Samuel-Jakubos, and 2021, “Sources of Payment for Uncompensated Care for the Uninsured” (Kaiser Family Foundation, April 6, 2021),

[16] Sara Hinkley, Annette Bernhardt, and Sarah Thomason, “Race to the Bottom: How Low‐Road Subcontracting Affects Working Conditions in California’s Property Services Industry” (UC Berkeley Center for Labor Research and Education, March 8, 2016),