What is the cumulative earnings impact of sustained annual workforce investment in Maui County over a 10-year period, and how do additional earnings from upskilling compound?
Workforce Understory Episode: Episode Four — Mobility Through Lifelong Learning
Geography: Maui County
Topic: STARs, living-wage attainment, upskilling, workforce investment, and regional delivery capacity
The takeaway
This modeled scenario invests approximately $1.3 million annually to help 651 Maui County workers move into higher-wage roles.
The earnings effect accumulates as each new annual cohort joins workers supported in prior years. By 2036, the model projects approximately $255 million in additional cumulative earnings attributable to upskilling.
Across the full ten-year period, the scenario represents approximately $13 million in direct workforce investment. The projected additional earnings are nearly 20 times that amount, although this comparison reflects gross worker earnings rather than a formal calculation of net return on investment.
Maui County’s relatively large population of STAR workers within reach of a living wage—and its comparatively high share already earning above the threshold—suggest that it may offer a strong Neighbor Island setting in which to test the model.
The projection suggests that sustained investment could generate substantial earnings gains, but the result depends on Maui County’s ability to connect each annual worker cohort with enough durable, higher-wage opportunities.
What this visualization shows
This visualization compares cumulative worker earnings in Maui County under two scenarios from 2027 through 2036:
Earnings without the modeled workforce investment
Earnings with a recurring annual investment of approximately $1.3 million supporting 651 workers into higher-wage roles
The difference between the two trajectories represents the additional earnings attributed to worker upskilling and advancement.
The gains compound because each annual cohort can contribute to several years of increased earnings. Workers supported in 2027 have the longest period over which to accumulate additional income. Workers entering the model in later years contribute for fewer years before the projection ends in 2036.
As successive cohorts are added, their earnings gains are layered onto those associated with workers supported previously. The difference between the two scenarios therefore grows more rapidly in the later years.
The arithmetic implies an annual investment of approximately $2,000 per supported worker. That appears to reflect a standardized modeling assumption and may not capture the actual cost of delivering training, coaching, employer engagement, placement, and supportive services across Maui County.
This is a prospective model rather than a record of observed outcomes. Its results depend on assumptions about worker recruitment, completion, placement, wage gains, employment continuity, and how long higher earnings are sustained.
The projection also assumes that the county can provide suitable higher-wage opportunities for approximately 651 newly supported workers each year. It does not independently demonstrate that those destination jobs currently exist.
Why this matters
Maui County may offer an important test of whether sustained workforce investment can produce economic mobility at meaningful scale outside Honolulu.
Approximately 14,700 Maui County STAR workers earn within $20,000 of a living wage. That creates a substantial population that may be responsive to targeted wage growth, advancement, or occupational transition.
The county also has a comparatively strong starting point. Approximately 34% of its STAR workers already earn above a living wage—nearly matching Honolulu’s share and exceeding those of Hawaiʻi and Kauaʻi counties.
That pattern may indicate that Maui County already has employers, occupations, or pathways capable of rewarding some STAR workers with living-wage earnings. It does not by itself prove that the county can absorb another 651 upskilled workers annually, but it provides a reason to examine which existing pathways are working and whether they can be expanded.
The county’s tourism-heavy economy remains a constraint.
Many workers may be close to the living-wage threshold while employed in occupations with limited wage progression. For them, the barrier may involve the structure and quality of available jobs as much as their individual skills.
Reaching the modeled earnings gains may therefore require several strategies at once: advancing incumbent workers, improving wages and scheduling, expanding skills-based hiring, strengthening career ladders, and growing industries capable of providing more higher-paying roles.
The cost of delivering those interventions may also differ from Oʻahu.
Maui County includes three inhabited islands, each with different populations, employers, transportation systems, and access to education and training. Smaller cohorts, instructor travel, equipment, facilities, interisland transportation, and limited provider capacity could increase the cost per worker—particularly on Molokaʻi and Lānaʻi.
At the same time, existing institutions and employer partnerships on Maui may reduce some costs. A realistic investment model should distinguish between standardized program assumptions and the actual resources required to provide equitable access throughout the county.
This evidence invites Maui County to ask:
Can the county build on the pathways already producing living-wage outcomes while developing enough additional opportunities to support 651 workers into higher-wage roles each year?
Evidence:
Questions this visualization helps answer
How much annual workforce investment is included in the Maui County scenario?
How many workers would receive support each year?
How do cumulative earnings with investment compare with earnings under the no-intervention scenario?
How much additional cumulative earnings could be generated by 2036?
Why does the projected earnings difference accelerate in later years?
How do gains from earlier cohorts combine with those of newly supported workers?
What is the cumulative direct investment across the full ten-year period?
How do projected gross earnings gains compare with the modeled investment?
What approximate investment per supported worker is implied by the scenario?
How does Maui County’s projected impact compare with those of the other Neighbor Island counties?
Why might Maui County provide a useful setting in which to test sustained workforce investment?
Curiosity:
Questions this visualization raises
Which specific higher-wage roles are the 651 supported workers expected to enter each year?
How many annual living-wage openings exist in those occupations?
Can Maui County’s employers absorb 651 newly upskilled workers every year?
Which industries are expected to generate the necessary opportunities?
How much of the projected mobility could occur through advancement within existing workplaces?
How much would require workers to change occupations or industries?
What average wage increase is assumed for each participant?
What share of workers is expected to complete training and secure a higher-paying role?
How quickly are workers expected to realize their earnings gains?
How long are those gains assumed to persist?
What participant attrition rate is included in the model?
How would the projection change if only half or three-quarters of participants sustained the expected earnings gain?
Are the earnings expressed in nominal dollars or adjusted for inflation?
Are the 651 participants new and distinct workers each year?
Does the model account for unemployment, reduced hours, seasonal work, or employment disruptions?
Which industries currently account for Maui County’s comparatively high share of STAR workers above a living wage?
Can those successful pathways be expanded to serve more workers?
Do Construction, Healthcare, Utilities, Transportation, or professional services have sufficient growth potential?
Can tourism and Hospitality create stronger mobility through improved wages, job design, and career ladders?
How much sector diversification is necessary for the projection to remain credible?
Does the approximately $2,000 investment per worker reflect actual delivery costs?
What services are included in the $1.3 million annual estimate?
Does it include recruitment, navigation, coaching, tuition, equipment, wage replacement, placement, and outcome tracking?
Are training costs higher in Maui County than on Oʻahu?
How do instructor availability, facilities, equipment, and cohort size affect program costs?
What additional costs arise from serving Molokaʻi and Lānaʻi?
Does the model account for interisland travel or remote instructional delivery?
Could shared statewide infrastructure reduce costs while preserving local delivery?
Which services must remain locally based and relationship-driven?
Could employers contribute training facilities, instructors, paid learning time, or tuition assistance?
How should the model account for the continuing effects of the Maui wildfires and recovery?
Could rebuilding investments expand Construction and infrastructure pathways?
How many supported workers might leave Maui County after training?
Would earnings generated after relocation still count toward the projected impact?
Should annual cohort size be tied to verified employer demand?
What early evidence would show whether Maui County can absorb workers at the modeled scale?
What would a realistic pilot look like before expanding to 651 workers annually?
Youth Perspective
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