In Simple Words
Imagine a raffle where job seekers are handed lottery tickets that offer different winning probabilities for a temporary paid job. Instead of picking workers based on talent or enthusiasm, the random probability lottery decides who gets work experience. This acts like a roll of the dice that forces work experience onto randomly selected individuals, allowing researchers to measure wage growth without confounding worker ability.
Young male job applicants in Malawi
- No chance of a fallback job
- 16.3% obtained a study job
- 50% chance of a fallback job
- 40.2 points more obtained a job
- Guaranteed fallback job
- 83.7 points more obtained a job
Randomized offer probabilities; unadjusted first-stage estimates. Percentage-point changes versus zero chance. Selected arms; 1%, 5% and 75% omitted.
See source →Research question
Measuring the true economic return of work experience is confounded because workers who acquire jobs often possess unobservable noncognitive skills or motivation. Randomly assigning probabilities of temporary employment isolates exogenous variation in short-term work experience to establish causal impacts on future labor market outcomes.
Participants
N = 268 male youth job seekers (aged 18+, secondary school educated) in Lilongwe, Malawi, with N = 227 successfully re-interviewed at 9-month follow-up.
Study Design
Randomized Controlled Trial (RCT) utilizing Instrumental Variables (IV), assigning random job offer probabilities (0%, 1%, 5%, 50%, 75%, and 100%) stratified by baseline ability quintiles and recruiter history.
Results
The probabilistic job offer assignment strongly predicts short-term employment acquisition with a first-stage F-statistic of 76.36. Assigning 50%, 75%, or 100% probabilities increases job acquisition by 40.2, 56.8, and 83.7 percentage points respectively (p < 0.01).
Takeaway
Structure pilot active labor market evaluations with probabilistic selection lotteries to construct valid instrumental variables for wage effect identification.
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 →- Percentage points
The difference between two percentages.
ExampleA rise from 40% to 50% is 10 percentage points. Relative to the starting value, that is a 25% increase.
Office for National Statistics · Percentages ↗Read more about percentage points →- 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 →