What is the cumulative earnings impact of sustained annual workforce investment on Kauaʻi over a 10-year period, and how do additional earnings from upskilling compound?
Workforce Understory Episode: Episode Four — Mobility Through Lifelong Learning
Geography: Kauaʻi County
Topic: STARs, living-wage attainment, upskilling, workforce investment, and regional job capacity
The takeaway
This modeled scenario invests approximately $600,000 annually to help 301 Kauaʻi 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 $120 million in additional cumulative earnings attributable to upskilling.
Across the full ten-year period, the scenario represents approximately $6 million in direct workforce investment. The projected additional earnings are roughly 20 times that amount, although this comparison reflects gross worker earnings rather than a formal calculation of net return on investment.
The Kauaʻi scenario is the smallest among the county models, reflecting the island’s smaller workforce and the comparatively small number of workers supported each year.
The model shows that a relatively modest annual investment could generate substantial cumulative earnings—but only if Kauaʻi has enough higher-wage jobs for each successive worker cohort to enter and remain in.
What this visualization shows
This visualization compares cumulative worker earnings on Kauaʻi under two scenarios from 2027 through 2036:
Earnings without the modeled workforce investment
Earnings with a recurring annual investment of approximately $600,000 supporting 301 workers into higher-wage roles
The difference between the two trajectories represents the additional earnings attributed to upskilling and advancement.
Those gains compound because each annual cohort may contribute to several years of increased earnings. Workers supported in 2027 have the longest period over which to accumulate additional income. Workers entering in later years contribute for fewer years before the projection ends in 2036.
As new cohorts are added, their earnings gains are layered onto those associated with earlier participants. The difference between the two scenarios therefore grows more rapidly over time.
This is a prospective model rather than a record of observed outcomes. Its results depend on assumptions about participation, training completion, movement into higher-paying employment, the size of the wage gain, and how long workers sustain those increased earnings.
The projection also assumes that Kauaʻi’s labor market can provide suitable higher-wage opportunities for approximately 301 newly supported workers each year. It does not by itself demonstrate that those destination jobs currently exist.
The additional earnings shown are projected gross income received by workers. They are not equivalent to government revenue, employer profit, or a guaranteed financial return to the organizations funding the intervention.
Why this matters
Kauaʻi’s small scale makes the modeled investment appear both achievable and unusually dependent on local economic conditions.
Supporting 301 workers each year is far less complex than reaching thousands annually in Honolulu. A coordinated effort involving a focused group of employers, training providers, and occupations could potentially affect a meaningful share of Kauaʻi’s workforce.
But the island also has Hawaiʻi’s smallest living-wage job base.
That means the projection depends on more than the ability to recruit workers and provide training. Employers must have enough higher-paying roles available each year, and those roles must be accessible to workers without requiring them to relocate.
If approximately 301 workers complete upskilling annually but local employers create or open fewer than 301 suitable positions, the model’s assumptions begin to break down. Workers may remain in lower-wage jobs, compete for a limited number of openings, accept work unrelated to their new skills, or leave Kauaʻi to realize the expected earnings gain elsewhere.
For this reason, worker development and sector development must proceed together.
Some gains may come from advancing incumbent workers into higher-level roles within existing employers. Others may require expanding industries such as Healthcare, Construction, Utilities, Transportation, technology-enabled work, or locally rooted professional services.
The island may also need to improve the jobs it already has. Wage increases, redesigned career ladders, skills-based promotion, and stronger employer practices could produce mobility without depending entirely on new job creation.
Kauaʻi’s model therefore tests a central premise of workforce investment: upskilling can create economic value only when the regional economy provides places for newly developed skills to be used and rewarded.
This evidence invites Kauaʻi to ask:
Can the island create, improve, or open at least 301 higher-wage roles each year so that workforce investment translates into lasting local earnings gains?
Evidence:
Questions this visualization helps answer
How much annual workforce investment is included in the Kauaʻi 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 grow more quickly 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?
Why is Kauaʻi’s program smaller than the comparable county models?
How does sustaining earlier wage gains contribute to the cumulative result?
Curiosity:
Questions this visualization raises
Which specific higher-wage occupations are the 301 supported workers expected to enter each year?
How many annual living-wage openings currently exist in those occupations?
Does Kauaʻi’s economy have enough destination jobs to absorb 301 workers every year?
Would the model require new job creation, advancement within existing workplaces, or both?
Which industries are expected to generate the necessary opportunities?
How many workers could advance through Healthcare, Construction, Utilities, Transportation, or other promising sectors?
Can Kauaʻi’s Building industries expand quickly enough to support the model?
What average wage increase is assumed for each participating worker?
What share of participants is expected to complete training and secure a higher-paying role?
How quickly after receiving support are workers expected to realize an earnings gain?
How long are those gains assumed to persist?
Does the model account for unemployment, reduced hours, occupational changes, or declining wages?
What worker attrition rate would produce a more conservative estimate?
How would the result change if only half or three-quarters of participants sustained the projected gain?
Are the earnings expressed in nominal dollars or adjusted for inflation?
Are the 301 participants new and distinct workers each year?
Does the model account for workers who leave Kauaʻi after receiving training?
Would earnings generated by workers who relocate still count as a benefit to the island?
How much outmigration would materially weaken the local impact?
Could upskilling increase worker mobility without improving Kauaʻi’s own workforce capacity?
Are local employers committed to hiring or advancing workers before training cohorts begin?
Which degree requirements could be removed to open existing higher-paying roles to STAR workers?
Could incumbent-worker advancement generate more reliable outcomes than training people for external job transitions?
What investments in employers or industries must occur alongside the worker investment?
Could remote employment create additional higher-wage destinations for Kauaʻi residents?
What broadband, workspace, supervision, and employer infrastructure would remote pathways require?
Does the $600,000 annual investment include worker navigation, coaching, placement, employer engagement, and outcome tracking?
What transportation, childcare, equipment, or financial supports are included?
Is the investment large enough to provide the level of support participants will need?
Could the small scale of the program allow more individualized support and stronger outcomes?
How should Kauaʻi measure whether newly developed skills are being used and rewarded locally?
What early indicators would show that the labor market cannot absorb the annual cohorts?
Should the pace of worker enrollment be tied directly to verified employer demand?
What would need to change in the projection if sector development takes longer than anticipated?
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