In Simple Words
A randomized controlled trial acts like a scientific coin flip that creates two identical twin groups of job seekers. By randomly assigning qualified applicants either to receive sectoral training or to a control group receiving standard services, any subsequent difference in earnings can be attributed solely to the training program itself.
Low-wage job seekers in three US programs
- Without the sectoral program
- Group used for comparison
- With the sectoral program
- Earned $4,500 more over two years
In the randomized Sectoral Employment Impact Study, participants across three programs earned $4,500, or 18%, more than controls over the two-year study period. This is a cumulative two-year difference, not an annual amount and not a comparison of the effects of different studies.
See source →Research question
Non-experimental evaluations of employment interventions frequently produce misleading results due to selection bias, as highly motivated candidates self-select into training programs. Without rigorous counterfactuals, policymakers cannot determine whether observed wage increases stem from program quality or unobserved participant characteristics.
Participants
Thousands of human adult and youth job seekers across 9 sectoral programs evaluated in 4 multi-site randomized trials in the United States.
Study Design
Randomized Controlled Trial (RCT) methodology comparing treatment and control group outcomes over 2-year to 11-year follow-up windows (Maguire et al. 2010; Hendra et al. 2016; Fein et al. 2021; Roder & Elliott 2021).
Results
Randomized sorting ensured baseline equivalence between groups, establishing that sectoral programs causally increased 2-year earnings by $4,500 in SEIS (18% increase, p < 0.01), 5-year earnings by $2,716 in WorkAdvance (11.5% increase, p < 0.01), and 11-year earnings by $4,616 in Project QUEST (15% increase, p < 0.01).
Takeaway
Mandate randomized lottery assignment among qualified workforce applicants during pilot program rollouts to establish rigorous causal evidence of earnings impact before national scaling.
Source and citation
See source →Read alongside the research
Plain-English glossary
Original explanations, informed by the references below. Examples are illustrations, not data from the studies above. The research text stays unchanged.
- Follow-up
Collecting more information about participants later in a study to see what has happened to them. The term can also mean the length of time researchers keep track of them.
ExampleResearchers interview the same workers three months after a programme ends. That later interview is a follow-up.
GET-IT glossary · Follow-up ↗Read more about follow-up →- Baseline
The starting measurements in a study. Researchers use these to compare what participants were like at the start with what happens later.
ExampleBefore a training programme starts, researchers measure workers’ earnings. That first measurement is the baseline.
GET-IT glossary · Baseline characteristics ↗Read more about baseline →- Randomized controlled trial
A study that uses chance, like drawing lots, to decide who receives each option being compared. Researchers compare the groups’ outcomes to estimate the effect of those options.
ExampleA lottery assigns volunteers to a training programme or a comparison group. Researchers then compare their outcomes.
GET-IT glossary · Randomized study ↗Read more about randomized controlled trial →