In Washington State, as throughout the rest of the United States, the COVID-19 public health and economic crisis has brought about historic levels of unemployment that have persisted for more than a year.¹ Most impacted are people of color, particularly Pacific Islanders and Black workers, women, and individuals with lower levels of education—communities that were not fully reaping the benefits of Washington’s pre-pandemic economic boom. The state estimates that hundreds of thousands of Washingtonians will need new skills in order to enter the post-pandemic economy. Under the leadership of Governor Jay Inslee, several state agencies have developed an economic recovery plan aimed at promoting economic stability for historically underserved and vulnerable populations. With a focus on credentials with economic value and building navigable education and training pathways, Washington’s inclusive recovery plan seeks to address the persistent and pervasive structural barriers to high-quality, well-paying jobs.²

As the entire nation grapples with growing labor market and income inequality made even more visible by COVID-19, policymakers at all levels of government are weighing a variety of public investments in education and training to help individuals secure good, family sustaining jobs. Short-term training—lasting less than three months—is often considered by policymakers and workforce leaders as a pathway to middle-skill jobs. It presents a solution for helping dislocated workers quickly reenter the labor market, supporting career advancement or transition opportunities for incumbent workers, and providing new high school graduates with occupation-specific skills needed to land a well-paying job. Short-term training programs are also appealing to youth and adults. They teach discrete, occupation-specific skills; are often more affordable than postsecondary degree pathways; and can often be stacked with other credentials to position workers along an educational and career path.

Given the enthusiasm among some policymakers for expanding access to short-term training, it is surprising how little we know about these types of programs in terms of who provides them, the occupations for which they tend to prepare workers, who enrolls in these programs, and what labor market outcomes are associated with program completion. A limited amount of research on short-term training programs suggests mixed results. While some programs provide demonstrable value to students in terms of employment and earnings outcomes, there is a great deal of variability based on program, provider, and student demographics. Men, whites, and students who already have some college or college credentials tend to have more favorable outcomes than women, students of color, and students who have a high school diploma or less.³

Whether short-term training programs yield positive and equitable outcomes is an important question that deserves attention as federal policymakers consider expanding the use of Pell Grants—need-based grants to low-income undergraduates—and as state policymakers weigh investments in short-term training as part of a higher education completion and economic recovery strategy.

Based on comprehensive data from the Washington Workforce Training and Education Coordinating Board, this analysis explores short-term training programs, including which providers offer them and in which occupation-specific programs of study; the demographics of those who enroll in programs; and outcomes for program completers or graduates. Given limitations on the maintenance and matching of student-level data at the federal level, state-specific analyses of training program participation and outcomes provide the best glimpse into who accesses and benefits most from short-term training.

This study reveals several trends related to the delivery of short-term training programs in Washington, who is enrolling, and how they fare in the labor market.

• Men and women enroll in short-term training at comparable rates, but they generally enroll in different programs. Men represent more than 80 percent of truck and bus driver, skilled trades, and information technology program participants, whereas women are overrepresented in education and health care training. Thus, short-term program participation mirrors, and perhaps reinforces, the occupational gender segregation seen in the labor market.
• Black people are overrepresented in short-term training programs. Whereas Black people account for 4.4 percent of the Washington state population, they represent 8.6 percent of students who enroll in short-term training. White students, on the other hand, are underrepresented in short-term training compared to their share of the state population. The share of Hispanic/Latinx, Asian, Native American, and multiracial short-term training participants was within 1.5 percentage points of each group’s share of Washington residents.
• Short-term training programs have higher completion rates compared to longer ones. Across all short-term training programs, the average completion rate is 74.5 percent, which is notably higher than longer programs less than a year in length (68.4 percent), programs between one and two years (66.3 percent), and programs longer than two years (65.2 percent).
• Short-term training programs associated with higher earnings enroll participants with higher levels of education. For instance, nearly a quarter of participants in computer and information systems security programs, which have the highest-paid graduates, possess a bachelor’s degree or higher. Given past studies that demonstrate a wage premium for college graduates, the higher earnings of some short-term training program graduates could be explained, in part, by the educational attainment levels of participants.
• The typical short-term training program graduate earns more than the state minimum wage but not enough to support a family. The average median hourly earnings for a short-term training program graduate is $17.84 one year after program completion. While this exceeds Washington’s minimum wage, recently raised to $13.50/hour, individuals with dependents earn less than the state’s living wage. In fact, the typical short-term training program graduate earns less annually than a high school graduate. The median annual wage for a high school graduate in Washington is $37,000, while the average median annual earnings for all short-term training program graduates is $33,696.

The purpose of this analysis is to better understand the landscape of short-term training programs, who pursues short-term training, and the labor market outcomes of those who complete these programs. Three main questions guided this descriptive analysis:

1. Which entities deliver short-term training programs, and for what fields do short-term training programs aim to prepare students?
2. What are the demographic characteristics, in terms of gender, race, and prior education, of individuals who enroll in short-term training?
3. What are the completion, employment, and earnings outcomes of short-term training program graduates?

In summer 2020, New America requested and received data on Washington’s training programs from the Washington Workforce Training and Education Coordinating Board (WTECB), the state’s governor-appointed workforce board. The WTECB is responsible for implementing standardized accountability measures for the state’s workforce development system. As part of its accountability function, the workforce board maintains training program participation and performance data. Additionally, it links individual participant records reported by each training provider with unemployment insurance (UI) wage records and other administrative databases, such as the State Wage Interchange System (SWIS),⁴ to compute statistics on the employment and earnings of training program completers. Through the Washington Career Bridge website, the workforce board publishes detailed enrollment and outcome information for education and training programs that charge tuition in the state.⁵ The information analyzed for this report was compiled from two sets of extracted data from the Career Bridge site.

The information contained in this report is based on an analysis of 10,976 training programs offered in the State of Washington since 2013. To understand the scope, demographic composition, and outcomes associated with training programs for which current federal legislative proposals could make Pell Grants available, this analysis is primarily focused on short-term training programs that are fewer than 600 clock hours and 15 weeks in length.⁶ These short-term training programs account for 2,560, or 23.3 percent, of Washington’s training programs included in the data set. Where relevant, we highlight how the participant characteristics and outcomes of short-term training programs compare to longer training programs—those greater than 600 clock hours and between 15 and 52 weeks, one to two years, and two or more years in length.

The compiled data set included comprehensive information about each of the state’s training programs, including a unique program identification number (ID), the type of training provider, the program length, associated clock hours, and six-digit Classification of Instructional Programs (CIP) code. The data set also included aggregate-level data on the demographics (gender, race, and prior education level) of program participants and the outcomes of graduates for each training program, namely the completion rate, the employment rate one year after program completion, and the median hourly and annual earnings one year after program completion. Appendix A provides more detailed information about the key variables used in this analysis.

The analysis contained in this report is descriptive in nature, with much of the analysis consisting of sample mean comparisons. Using CIP codes, which classify instructional programs offered by postsecondary institutions by the occupational field for which program participants prepare, we were able to examine the 20 most common short-term training programs of study, which account for nearly 55 percent of short-term training programs in the data set (see Appendix B for list of common short-term programs of study and corresponding occupations). We also explore which providers tend to offer certain programs of study as well as the demographic profile of participants and the outcomes of graduates based on program of study.

Using aggregate data on the demographics of participants in each training program, we calculated the overall percentage of male and female participants; the percentage of participants who identify as white, Black, Hispanic/Latinx, Asian, Native American, and multiracial; and the percentage of participants whose highest level of education before enrolling in training was some college or less (includes high school diploma and GED holders and those without a high school diploma or GED), a certificate or associate degree, and a bachelor's degree. Using aggregate-level data on the outcomes of graduates for each training program, we were able to calculate the average completion rate across all short-term training programs as well as the average employment rate and median annual earnings one year after completion for each training program.⁷

Limitations

Because participant demographic data was only available in the aggregate, it was not possible to do cross-tabulations between any two demographic groups (e.g., race/ethnicity and gender). Furthermore, because the data set lacked demographic information about program graduates specifically, it was not possible to assess how the demographic profile of graduates differs from that of those who initially enrolled in the program.

For some programs, the data set lacked complete participant demographic and completer outcome information. The WTECB, which requires that training providers collect and submit participant data on an annual basis, suppresses participant demographic data in Career Bridge if a training program does not enroll at least 10 participants. The WTECB also suppresses the employment and earnings information for training programs that have fewer than 25 completers. Some of the missing outcome data can be attributed to lags in the collection of employment and earnings information for recently completed programs, as the employment and earnings of completers is measured one year after completion. Furthermore, in Washington, much like in other states, UI records exclude self-employed individuals, federal workers, military personnel, and foreign-employed workers, and therefore these groups are underrepresented in the employment and earnings data. The exclusion of these workers from employment and earnings records is more likely to skew the outcome data for entrepreneurship/entrepreneurial studies programs, which have a sizable number of self-employed graduates; or marine science/merchant marine officer programs, many graduates of which go on to contract, federal, or foreign employment.

Given WTECB publication cutoffs and reporting lags, the data set did not include participant and/or completer outcome data for all programs within a common short-term training program of study category. We excluded a common short-term program of study from the in-depth analysis if the data set lacked participant or completer outcome data for at least 10 programs. In all, the data set included sufficient program data for 14 of the 20 common short-term programs of study (the availability of program data on marine science/merchant marine officer; carpentry/carpenter; data entry/microcomputer applications; computer programming/programmer; plumbing technology/plumber; and electrical, electronic, and communications engineering technology/technician programs of study varied across participant or completer outcome indicators and thus are sometimes excluded from certain in-depth analyses). Appendix C includes a list of common short-term programs of study for which sufficient program demographic and outcome data exist. The overall analysis of short-term training programs includes all programs of study, regardless of the number of programs for which participant or outcome data were available.

In the absence of student-level Standard Occupational Classification (SOC) data indicating the specific occupations in which individuals are employed, it was not possible to determine the likelihood of graduates finding employment related to their program of study. Graduates employed in occupations misaligned with their program of study could skew—up or down—the average median earnings associated with a program of study.

Of the 2,560 short-term training programs analyzed in Washington State, there are 265 different types of programs of study offered by training providers. Truck and bus driver programs account for the greatest share of short-term training (11.6 percent), followed by early childhood education (5.8 percent), electrician (4.1 percent), nursing assistant/aide (4.1 percent), and automobile and marine science (3.7 percent) programs.

As Figure 1 indicates, public community and technical colleges and private career/vocational schools provide the vast majority of short-term training. More than half of short-term training programs analyzed, 54 percent, were offered by community and technical colleges, while private vocational schools account for 39 percent of programs.⁸ Yet the data also show that these two providers tend to offer different types of training. As Figure 2 indicates, private career/vocational schools are the primary provider of truck and bus driver, electrician, marine science, carpentry, and plumbing technology programs, while public community and technical colleges tend to offer the majority of early childhood education, nursing assistant/aide, automotive mechanics, data entry, welding technology, computer and information systems security, business administration, airline pilot and flight crew, accounting technology, and web page design programs.

Short-term training programs at private career vocational schools cost more in tuition and fees than those at public community and technical colleges, $3,512.64 compared to $1,375.62, on average. Yet this finding does not hold for all programs of study. We examined five programs of study commonly offered by both public community and technical colleges and private career vocational schools. As Figure 3 below shows, a nursing assistant/aide or home health aide program costs slightly more at a public community and technical college than a private career vocational school, $292.20 and $185.77, respectively. Yet these short-term training programs are among the least expensive. Truck and bus driver, computer programming, and welding technology training programs cost substantially more at a private vocational school—$2,871.35, $5,508.05, and $936.16, respectively, than at a community or technical college.

Yet these program costs do not necessarily reflect the out-of-pocket cost a training program participant incurs. Individuals can benefit from several sources of public workforce funding. Washington's Job Skills Program pays for half the training offered by a community college, while partner businesses cover the other half;⁹ the Worker Retraining Program gives financial assistance to individuals who need basic skills and technical training via colleges;¹⁰ the Washington College Grant covers tuition at eligible in-state public colleges or universities, including community or technical colleges, or approved private colleges or career training programs for low- and middle-income families;¹¹ and the Workforce Innovation and Opportunity Act covers college training programs that confer credit. The state also fully funds or heavily subsidizes occupation-specific training for early childhood education professionals, who are required to take certain community college courses to obtain licensure. Individuals who leave their employment to care for disabled or elderly family members can also obtain their home care professional certification at little or no cost due to state training subsidies. More data are needed to determine how much adults are paying to pursue training and how the cost to individuals impacts decisions about whether to pursue certain types of training.

Gender

Men make up 54.8 percent of all short-term training participants included in this analysis, while women make up 45.2 percent. However, the gender composition of short-term training varies greatly based on program of study. Consistent with prior research, Figure 4 shows that short-term training program enrollment mirrors the gender-based occupational segregation present in the labor market.¹² Men make up more than 80 percent of participants in truck and bus driver (94.7 percent), airline pilot and flight crew (92.4 percent), marine science (91.5 percent),¹³ automotive mechanics (89.3 percent), welding technology (90.3 percent), electrician (89 percent), carpentry (86 percent), and computer information systems security (79.5 percent) programs. Women, on the other hand, make up the vast majority of participants in early childhood education (96.2 percent), nursing assistant/aide (87.2 percent), phlebotomy technician (84.4 percent), accounting technology (80.8 percent), and home health aide (81.1 percent) training.

Race and Ethnicity

As Figure 5 below shows, white students represent 67.2 percent of those enrolled in training. However, compared to the overall racial and ethnic composition of Washington State, they are underrepresented by about 11 percentage points. Hispanic/Latinx individuals are the largest minority group in Washington State (13 percent) and its short-term training programs (13.5 percent), followed by Asian students, who make up 9.3 percent of short-term training participants and 9.6 percent of the state population. Black students’ participation in short-term training (8.6 percent) is nearly twice this group’s share of the state population (4.4 percent).¹⁴

The racial and ethnic composition of short-term training programs varied by program of study, as shown in Figure 6. Health care-related and female-dominated programs are among the most racially and ethnically diverse, with the greatest proportion of students of color. Home health aide programs are 38.6 percent Hispanic/Latinx, 22.3 percent Black, and 19.1 percent Asian, while nursing assistant/aide programs are 16.9 percent Hispanic/Latinx, 11.6 percent Asian, and 10.3 percent Black. In phlebotomy technician programs, Hispanic/Latinx make up 25 percent of participants, while Asian students represent 12.5 percent and Black students are 8.3 percent.

In addition to medical-related programs, Hispanic/Latinx individuals are the most represented minority group in electrician (39 percent), data entry (23.3 percent), automotive mechanics (15.1 percent), and early childhood education (13.2 percent) programs. Compared to their overall share of short-term program participants, Black students also make up a disproportionate share of those enrolled in computer and information systems security (11.1 percent) and carpentry (12 percent). And Asian students are the most represented minority in accounting technology programs (16 percent).

Prior Education

Across all programs of interest, individuals with a high school diploma or GED or less make up the largest share of participants (55 percent), followed by adults with some college (18.4 percent). Individuals who already hold a postsecondary certificate or degree account for more than a quarter (26.6 percent) of all short-term training program participants.

Except for entrepreneurship programs, for which 87.5 percent of participants have a postsecondary certificate or degree, the highest level of education for the majority of participants in the short-term training programs of study examined is some college or less (see Figure 7). In male-dominated truck and bus driver and traditional skilled trades programs, including automotive mechanics, electrician, and welding technology, more than 82 percent of participants have some college or less. Most of these programs also have the highest proportion of participants with a high school diploma or less. Electrician (84 percent) and automotive mechanics (80.4) programs lead with the highest share of those with education at or below the high school level, followed by welding technology (71.6 percent) programs. On the other hand, computer and information systems security, another male-dominated program, has the second-highest share of bachelor’s degree holders, at 23.9 percent.

Female-dominated training programs have a significant but comparatively smaller share of students with a high school diploma or less and also have more college-educated students than most male-dominated programs of study examined. While roughly 55–60 percent of participants in medical-related training programs (phlebotomy technician and nursing assistant/aide) have a high school diploma or less, these programs have some of the highest shares of certificate or associate degree holders. For instance, 16.3 percent of phlebotomy technician and 17.7 percent of nursing assistant/aide program participants have a postsecondary certificate or associate degree. Web page design (19.2 percent) and computer and information systems security (21.1 percent) enroll the highest shares of certificate or associate degree holders.

Across all short-term training programs, the average completion rate is 74.5 percent. This captures everyone who graduated with a credential, including a non-degree certificate, as well as community and technical college and private vocational school students who transferred to a four-year institution. Completion rates are notably higher for short-term training than longer programs less than a year in length (68.4 percent), programs between one and two years (66.3 percent), and programs longer than two years (65.2 percent).

Some short-term training programs of study such as marine science (98.7 percent), entrepreneurship (97.4 percent), phlebotomy technician (93.4 percent), truck and bus driver (93.8 percent), nursing assistant/aide (85.7 percent), home health aide (88.9 percent), and electrical technician (80.8 percent) have higher than average completion rates, whereas web page design (59.7 percent), early childhood education (55.6 percent), and electrician (52 percent) programs have lower than average completion rates (see Figure 8).

Across all short-term training programs, 74.8 percent of those that complete a program are employed four quarters after exit. Computer and information systems security (83.6 percent), phlebotomy technician (81.1 percent), electrician (79 percent), airline pilot and flight crew (78.7 percent), nursing assistant/aide (77.6 percent), truck and bus driver (76.7 percent), and accounting technology (75.4 percent) program graduates have higher than average completion rates for short-term training programs. Entrepreneurship, a program with one of the highest completion rates, has the lowest employment rates, at 50.4 percent, likely because many program graduates go on to self-employment and are thus not captured in state employment data systems.

What is unclear is what percentage of those not employed one year after completion are enrolled in further education and the likelihood that short-term training graduates will eventually pursue additional training related to their field of study. Additional data on post-program educational enrollment could shed light on the extent to which short-term training programs offer stackable credentials that position adults to increase their qualifications within a particular career path.

The average median hourly earnings for a short-term training program graduate is $17.84 four quarters after program exit. Whereas the average short-term training program graduate earns more than Washington State’s minimum wage, recently raised to $13.50/hour, not all graduates are bringing home a living wage.¹⁵ What defines a living wage is different for each worker and is often determined by family composition and financial obligations.

According to the Massachusetts Institute of Technology, which calculates state-specific living wage models to serve as alternative, more accurate measures of basic needs compared to the federal poverty threshold, the living wage for a single working adult in Washington State is $13.47/hour. A sole earner in a two-adult household must make $20.40/hour, whereas each working adult in a two-adult household must earn $10.20/hour to get by. With dependent children, the required hourly living wage increases. A single parent must earn $27.08/hour to care for a single child and $32.23/hour for two children. A two-parent household, in which both adults are working and sharing the financial load, requires a $14.89 hourly wage per person to support a family of three and $17.45/hour for a family of four (Figure 9).¹⁶

Figure 9: Hourly Living Wage in Washington State

Note: Aggregate living wage figures assume that individuals work 2,080 hours a year, or 40 hours a week
Source: Massachusetts Institute of Technology Living Wage Calculator.

As Figure 10 illustrates, on average, graduates of nearly all of the short-term training programs examined are earning enough to support a single adult household. The one exception is nursing assistant/aide program graduates, who earn $13.19/hour on average and fall short of reaching any of the living wage categories. This group of individuals would appear to benefit most from the recent and steady increases in the state minimum wage. Nonetheless, a nursing assistant/aide with a family is not likely to earn enough to survive unless he or she is part of a two-adult working household. Sole-earner nursing assistants/aides with two children are earning poverty-level wages.

Only marine science graduates who are single with no children earn enough to support themselves and/or a family. All other short-term training program graduates do not. Web page design and automotive mechanics program graduates, who earn $14.83/hour or less, would also struggle to support even one child, even with a partner with comparable earnings.

These aggregate living wage figures assume that individuals work 2,080 hours a year, or 40 hours a week, which might not be the case for all short-term training graduates.

In Washington State, the median earnings of high school graduates is $37,000.¹⁷ Yet the average median annual earnings for short-term training program graduates is $33,415. Furthermore, 10 programs studied were associated with lower than average median annual earnings. Of these, five are female-dominated programs and related occupations (accounting technology, home health aide, phlebotomy technician, early childhood education, and nursing assistant/aide), which also tend to enroll more participants of color, whereas three are male-dominated programs (airline pilot and flight crew, welding technology, and automotive mechanics). Graduates of nursing assistant/aide and early childhood education programs, two of the most common short-term training programs in the state, earned $22,720.85 and $25,158.23, respectively, one year after completing the program (see Figure 11).

There have been countless studies reaffirming the presence of gender and racial wage gaps, factors that are likely at play in Washington. Yet, the higher earnings of some short-term training program graduates could be explained, in part, by the educational attainment levels of participants (see Figure 12).

The short-term training program for which graduates average the highest annual median earnings, $53,599.71, is computer and information systems security. This program also enrolls one of the highest shares of bachelor’s degree holders (23.9 percent). This finding reflects the positive relationship between postsecondary education and better labor market outcomes that researchers have documented for a long time.¹⁸ But there are some programs like truck and bus driver, business administration, electrician, and airline pilot and flight crew for which graduates earn a solid wage without prior postsecondary education. Truck and bus driver and electrician programs have the highest shares of participants with a high school diploma or less, at 66.5 and 84 percent, respectively. Except for business administration, the programs with the highest-earning graduates enroll mostly male participants. On the other hand, graduates of web page design and female-dominated and racially diverse short-term programs like early childhood education and nursing assistant/aide earn the lowest wages even though roughly a quarter of these program participants are college-educated (i.e., possess a postsecondary certificate, associate degree, or bachelor’s degree).

Research has shown that workers with an occupational license, a required credential awarded by a government agency, tend to earn more than workers without a license.¹⁹ The data set does not include information about the licensing of short-term training program participants, thus raising questions about the extent to which graduate earnings might be explained by the possession of non-degree credentials of value.

More research is needed to determine the extent to which prior education and credential attainment influence the short- and long-term earning potential of short-term training graduates, but this analysis suggests educational background—and perhaps other demographic characteristics of those who pursue short-term training—plays a role in graduate earnings. To assume that all short-term training programs position all graduates to land family-sustaining jobs ignores persistent realities about the labor market conditions that have historically disadvantaged less educated, female, and minority workers.

With the COVID-19 public health and economic crisis causing massive and sustained levels of unemployment, short-term training is likely to play a key role in our nation’s recovery strategy.²⁰ Short-term training programs certainly provide some value to graduates who acquire new and relevant job-related skills and credentials, and to employers who benefit from a more qualified workforce. The accessibility of short-term training compared to lengthier programs makes it an attractive option for jobseekers, dislocated workers, career changers, and incumbent workers looking to progress in their careers. However, program value cannot fully be assessed without taking into account the cost incurred by students and the short- and long-term benefits to program completion, in the form of employment, earnings, and career advancement opportunities.

In Washington, much like in other states, the public workforce system, state financial aid, and occupation-specific training subsidies fund many short-term training programs. Yet even if public dollars were to fully fund short-term training programs, removing financial burdens for those who enroll, many graduates would still land jobs that fail to pay a living wage. And the short-term training graduates who earn the least, many of whom are college-educated, tend to enroll in female-dominated programs and go on to become essential workers in female-dominated and racially diverse care occupations. Unfortunately, these earnings trends based on occupation are not unique to Washington State. Nationally, across all occupations, the annual mean wage is $56,310, but child care workers ($26,790), home health aide, personal care aides, and nursing assistant/aide ($29,320) earn substantially less. Workers in male-dominated automotive mechanics ($47,060), truck and bus driver ($52,090), and electrician ($61,550) occupations earn close to or more than the average American worker.²¹

The Workforce Innovation and Opportunity Act requires that governors or state agencies disseminate information about eligible training providers and the performance and costs associated with the training programs they offer via a searchable database—something Washington State did long before the federal requirement. Now every state has a website similar to Career Bridge to inform individuals about training opportunities in their communities and the job and earnings prospects they can expect following program completion.²²

Greater transparency about short-term training program costs and outcomes—albeit an important decision-making tool for jobseekers and a useful resource for evaluating the effectiveness of public investments in training—will not eliminate bad jobs. Neither will dissuading people from pursuing training that leads to low-paying work, or worse, blaming individuals for choosing low-wage work that might be well aligned with their personal interests and/or offer a more conducive environment or schedule for balancing family and other obligations. The reality is care jobs in the early childhood and health sectors are in demand and expected to grow. They require skilled professionals to provide the quality of care that children, the elderly, and individuals with disabilities deserve. Market forces would suggest that the critical importance and challenging nature of care work, coupled with high rates of worker turnover, would translate into better compensation. But deep-rooted obstacles such as societal biases and exclusionary labor laws have long prevented equal access to quality jobs for women and people of color.

The findings outlined in this report speak to the importance of labor policies that ensure living wages, not to mention family-sustaining benefits for all workers. Washington State boasts the second-highest minimum wage in the U.S., behind Washington DC, and the state has committed to incremental cost-of-living adjustments to this wage based on the federal Consumer Price Index for Urban Wage Earners and Clerical Workers.²³ This will certainly help, but the state-wide minimum wage falls short of the living wage many families need to get by.

Washington has been a leader in using state education, employment, and wage data systems to assess the value of taxpayer-funded training.²⁴ By using these data to examine whether short-term training graduates were employed one year after program completion and their hourly and annual earnings, this analysis provides a glimpse into the value of this training, which accounts for nearly a quarter of all training in the state.

However, to determine whether short-term training graduates are employed in a field aligned with their training, the extent to which short-term training programs lead to sustained wage increases, and whether short-term training serves as a stepping-stone to advanced career training and career progression, more research is needed. Washington recently passed legislation requiring employers to provide quarterly reports of the standard occupational classifications or job titles of workers, in addition to employee wages and hours worked, beginning in October 2021.²⁵ This occupational data will facilitate a more comprehensive evaluation of all training programs.

Other states and the federal government should follow Washington’s lead. Before even more public investments go toward short-term training programs, it is important to determine whether they are delivering on their promise to jobseekers and helping to dismantle systemic labor market inequities that predominantly hinder women, people of color, and those with fewer educational opportunities.

“X” signifies that data are available for at least 10 programs within the common short-term program of study.