In Simple Words
Think of Statistically Assisted Programme Selection like a digital navigation app for job training. Instead of a driver guessing which route is fastest based on personal habit, the app analyzes millions of past trips taken by similar drivers under similar weather conditions to show the driver which specific turn gives them the highest probability of arriving on time.
Swiss jobseekers in the SAPS trial
- Caseworker has no access
- 12% matched the top recommendation
- Caseworker has access
- 12% matched the top recommendation
2005 trial, excluding Geneva. First programme within 90 days; no significant difference. Caseworkers retained full choice.
See source →Research question
Active labour market programmes frequently generate disappointing or negative employment outcomes because public employment services fail to match unemployed jobseekers to measures that maximize individual employment probabilities. Statistically Assisted Programme Selection addresses this misallocation by providing caseworkers with econometric predictions of individual net programme impacts derived from comprehensive administrative historical datasets.
Participants
Historical estimation sample of N = 460,442 jobseekers aged 25 to 55 from Swiss administrative databases (2001–2003); field experiment evaluated N = 18,713 treatment jobseekers and N = 16,677 control jobseekers across 21 Swiss employment offices.
Study Design
Randomized Control Trial (RCT) randomized at the caseworker level (142 treatment vs. 137 control caseworkers), utilizing biweekly econometric potential outcome predictions matched with Multiple Comparison with the Best routines.
Results
Providing econometric predictions to treatment caseworkers produced zero statistically significant change in programme assignment behaviour, with short-term compliance between recommended and assigned programmes remaining identical at 12% (Definition 1) and 29–30% (Definition 2) for both treatment and control groups.
Takeaway
Calculate individual potential employment outcomes using disaggregated administrative data, and integrate statistical prediction sets into caseworker workflow interfaces alongside explicit compliance monitoring protocols.
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.
- 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 →- Statistically significant
A label used when a result passes a chosen statistical threshold, often p < 0.05. It does not show how large or useful an effect is. A result that is not statistically significant does not prove there is no effect.
ExampleA study reports p = 0.03 against a 0.05 threshold. It passes that test, but the effect could still be too small to matter.
American Statistical Association · Statement on p-values ↗Read more about statistically significant →