Investing $1 in English Upskilling Generates a $6 Return in Economic Impact
Concerned with endemic workforce shortages and growing skills gaps, state and local government leaders are prioritizing efforts to bolster labor force participation rates and upskill incumbent workers. English learners — who now represent 1 in 10 working-age adults across the U.S. — are an often untapped talent pool. Most employers struggle to attract and retain this fast-growing, high-potential workforce.
In response, a growing number of states, from Colorado to Michigan and beyond, are investing in “English upskilling” as a component of workforce development efforts that connect workers with digital skills, work-based learning opportunities, job placement services, and more.
How English Upskilling Works
English upskilling is not a traditional language learning program. Enabled by the ubiquity of smartphones, states are now able to deliver highly targeted, workforce-aligned English instruction that connects learners with the specific language skills that they need for in-demand jobs.
States and local governments purchase English upskilling licenses in bulk, and distribute them for use by local employers, community colleges, and workforce development partners.
States are able to target the upskilling programs to the specific English skills needed for hard-to-fill, in-demand roles in sectors like healthcare, manufacturing, hospitality, and more. State and local governments have found that mobile-first English upskilling can provide a cost effective way to equip adult English learners with both the language skills and workforce skills that help power local economies.
Quantifying the Economic Impact
To measure the economic impact of English upskilling, EnGen analyzed results from partnerships with publicly funded agencies across 14 states, including the Colorado Office of New Americans, the Office of Global Michigan, the Michigan Global Talent Initiative, and nearly 20 public community colleges.
These institutions invested an aggregate $1.6M in public funds to provide English upskilling to a total of 5,500 learners. English upskilling in turn advanced learners’ English proficiency, which in turn bolstered their employment opportunities and wages, resulting in nearly $10.4M in broader economic gains for these local economies.
Findings suggest that every $1 invested in English upskilling generates a $6 return for local economies.
Invest: Local governments and other publicly funded institutions invest in licenses at scale, building capacity to connect thousands of adult English learners with career-aligned language and job skills.
Empower: Workers access targeted, job-specific instruction via their mobile device to boost language and job skills. On average, more than 60% of EnGen learners advance at least one level on the American Community Survey’s (ACS) English proficiency scale, a nationally recognized metric used to fund adult literacy programs.
Employ: Learners leverage their new English skills to connect with hard-to-fill, high-demand jobs with local employers. Researchers at the University of California and University of Houston have linked gains in ACS proficiency level improvements with wage increases of 10% to 30% for low-wage workers.
Amplify: Workers’ additional income translates to shared economic benefit in the form of increases in local tax revenues, consumer spending, job creation, and business investment. Research from the Economic Policy Institute suggests that a $1 increase in compensation to minimum-wage workers leads to a $1.20 increase in economic activity.
Gain: Local governments gain $6 for every $1 invested in English upskilling, all while building a more fully-staffed, future-ready workforce.
See the full methodology below for additional details on the cost-benefit analysis.
Methodology
This cost-benefit analysis used publicly available data to evaluate the economic return to state and local governments and publicly funded institutions associated with investment in EnGen’s English upskilling platform for local adult English learners.
The analysis focused on outcomes from EnGen partnerships with three groups: (1) the Colorado Office of New Americans, a state government agency in Colorado; (2) the Michigan Global Talent Initiative and the Office of Global Michigan, both state-funded initiatives in Michigan; and (3) nearly 20 community colleges across 12 other states.
The primary objective of this analysis was to quantify the broader economic benefit of at-scale English upskilling initiatives. For purposes of this analysis, we utilized conservative ranges of publicly available data to generate a baseline estimate of economic impact; actual impact on local communities may be much higher.
The benefit to the state from learners’ improved English proficiency, calculated as follows:
Total State Benefit = Learners Served × Level Improvement × (Income × Income Effect) × State Benefit Effect
Cost-Benefit Ratio = Total State Benefit / Cost (total public funds invested in EnGen licenses)
Data and Variables
Learners Served: The number of individuals who have used EnGen’s platform to complete at least 10 activities; on average, this translates to at least one hour of engagement on the platform.
Level Improvement: The percentage of EnGen learners in each group who improved at least one level of English proficiency, as defined by the American Community Survey (ACS).
Income: For purposes of this analysis, minimum wage was utilized as a conservative baseline wage estimate for adult English learners. For community colleges included in our analysis, the income variable was the average minimum wage across all states, while for Colorado and Michigan, it was the state-specific minimum wage. Where a state does not have a state-specific minimum wage, the federal minimum wage was used. Annual income was calculated as: Income = Minimum wage × Weekly hours × Weeks worked
Weekly hours were assumed to be 40, and weeks worked were assumed to be 48.(Note: Some learners’ median income may be significantly higher than minimum wage, suggesting a potentially larger cost-benefit ratio for English upskilling programs. For example, Bureau of Labor Statistics data indicates a median hourly wage of nearly $25 for foreign-born, full-time workers, not accounting for English proficiency levels.)
Income Effect: This measure represents the wage increase resulting from an improvement in English proficiency, estimated by researchers at the University of California and University of Houston to be a 10 to 30% increase over a minimum wage base income (Bleakley and Chin 2011). This analysis was based on a wage increase of 10%, representing the conservative range of income effect.
State Benefit Effect: The 1.2 multiplier reflects research from the Economic Policy Institute that documents the ripple effects states experience from wage increases. As the additional spending by low-wage workers boosts local businesses, creates jobs, and increases tax revenues. (Cooper and Hall 2013, Zandi 2011).
Calculation of Benefits and Cost-Benefit Ratio
For each group (Colorado, Michigan, and the group of community colleges), the benefit was calculated by multiplying the number of learners served by the proportion that showed ACS level improvement, the respective minimum wages, the income effect of 0.10, and the state benefit multiplier of 1.2. The total benefit was then divided by the cost to obtain the cost-benefit ratio.
A weighted average cost-benefit ratio was calculated for the combined three groups using the number of learners served as the weighting factor. This ensured that the groups with more learners had a proportionately greater impact on the overall cost-benefit ratio.
Results
In Colorado, the total benefit was $4,696,432, resulting in a cost-benefit ratio of 7:1, that is, $7 in benefit for every $1 invested.
In Michigan, the total benefit was $505,256.99, with a cost-benefit ratio of 7:1.
For the combined community colleges, the benefit was $5,177,006.71, with a cost-benefit ratio of 6:1.
Using the weighted average of the three groups based on the number of learners served, the overall return on investment was calculated as 6:1.
This shows that for every dollar invested in English upskilling using the EnGen platform, states can expect an approximate return of six times their investment, due in large part to increased wage outcomes among workers who improve their English proficiency.
This methodology was drafted by Lane Perry, EnGen’s Director of Data & Analytics. EnGen thanks Blake Heller, PhD, Assistant Professor at the University of Houston Hobby School of Public Affairs and Jon Schwabish, PhD, Senior Fellow at the Urban Institute for providing review and feedback.
References
Bleakley, Hoyt, and Aimee Chin. 2004. "Language Skills and Earnings: Evidence from Childhood Immigrants." The Review of Economics and Statistics 86 (2): 481-496. The MIT Press.
Bureau of Labor Statistics. 2024. “Labor Force Characteristics of Foreign-Born Workers Summary.” May 21, 2024. https://www.bls.gov/news.release/forbrn.nr0.htm
Cooper, David, and Doug Hall. 2013. "Raising the Federal Minimum Wage to $10.10 Would Give Working Families, and the Overall Economy, a Much-Needed Boost." Report. Economic Policy Institute. Briefing Paper #357
Zandi, Mark. 2011. "At Last, the U.S. Begins a Serious Fiscal Debate." Dismal Scientist (Moody’s Analytics’ subscription-based website), April 14, 2011.