In Simple Words
Imagine offering a fuel discount voucher to two drivers: one who rarely drives due to high fuel costs, and another who already drives every single day. The driver who rarely drove increases their trips significantly when given the discount, whereas the daily driver makes no additional trips because their driving behavior was already at capacity.
Chance of sending money in a week
Lower starting remittances
+1.0 percentage point
in the chance of sending money in a week
Higher starting remittances
Result uncertain
Estimated effects of access to labeling during study follow-up. An uncertain result does not mean zero effect. These separate estimates do not establish that the effects differ between groups.
See source →Research question
Financial behavioral interventions can generate divergent outcomes depending on pre-intervention baseline activity levels. Evaluating program impact solely across an aggregated population can mask substantial positive effects occurring within specific sub-groups.
Participants
2,408 low-baseline remitters (below median pre-treatment remittances) and 2,043 high-baseline remitters (above median) out of 4,451 analyzed migrant workers in the United Arab Emirates.
Study Design
Ordinary least-squares (OLS) panel regression with individual and week fixed effects across subsamples split by baseline remittance volume during weeks 1–5.
Results
Among migrants with below-median baseline remittances, labeling access significantly increased the probability of remitting (+1.0 percentage point, p < 0.01), weekly remittance frequency (+0.012 transfers, p < 0.01), winsorized weekly amount (+174.94 PhP, p < 0.05), and log weekly remittance amount (+0.083, p < 0.01), while showing no statistically significant effect on high-baseline remitters.
Takeaway
Segment financial policy evaluations by pre-treatment transaction volume to detect intervention impacts specific to under-performing user segments.
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.
- Median
The middle number after arranging the values from smallest to largest. If there are two middle numbers, use their average.
ExampleFor the values 2, 4 and 12, the middle value is 4. The median is 4.
NIST · Measures of location ↗Read more about median →- 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 →- 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 →