Energy Workforce Retraining Pipeline

Just-Transition Workforce Pipeline

Fossil-fuel layoff rate 60/mo

Renewable job growth 70/mo

Retraining capacity 50/mo

Training duration 9 mo

Dropout rate 12%

Sim speed 1.0 mo/s

Month

Fossil jobs

–

Unemployed

–

In training

–

Awaiting hire

–

Renewable jobs

–

Dropped out (total)

–

Peak unemployed

–

How it works

Every simulated month, workers laid off from the fossil-fuel sector join an unemployment queue. Retraining capacity caps how many can start a training programme at once; the training pool empties itself as a delay — on average a trainee exits after training duration months, a fraction dropping out permanently along the way. Graduates only get hired once the growing renewable sector actually opens a matching position, so a backlog of "awaiting hire" workers builds up whenever hiring can't keep pace with graduation.

unemployed += layoffRate·dt − intake
training  += intake − training/duration·dt
graduates  = training/duration·dt·(1−dropout)
hired      = min(graduates, openPositions)

Layoff rate — how fast fossil-fuel jobs disappear; a spike floods the unemployment queue faster than retraining can drain it.
Retraining capacity — the bottleneck: too low, and laid-off workers pile up long before they can even start training.
Training duration — longer programmes hold more people "in the pipe" at once, delaying when they can be hired.
Dropout rate — workers who never finish retraining; they don't return to the renewable pipeline in this model.
Renewable job growth — how many new positions open each month; if it lags graduation, finished trainees simply wait.

Real-world relevance: this is the exact bottleneck described in "just transition" energy policy — reskilling programmes for coal, oil and gas workers only succeed if training throughput and new green-sector hiring grow together, not in isolation.

Fossil-fuel jobs Unemployed queue In training Awaiting hire Renewable jobs

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