In Simple Words
Receiving a modest annual check causes a worker to make small adjustments like reducing overtime, whereas winning a huge jackpot causes complete career withdrawal; fitting a straight line through both extreme events creates an inaccurate average that misrepresents typical behavior at both ends.
Research question
Linear regression models assume that each additional dollar of unearned income reduces labor supply by a constant proportion regardless of total windfall size. Large outlier prizes can distort linear labor supply estimates across smaller cash transfers.
Participants
N = 496 human lottery players in Massachusetts, including N = 43 big winners receiving >$100,000 annually (averaging $160,000/year).
Study Design
Comparative evaluation of linear versus quadratic OLS regressions, and sub-sample specifications excluding extreme outlier winners.
Results
Linear specification yields an underestimated MPE of -0.051 due to extreme prize skewness, whereas a quadratic specification yields MPE derivatives of -0.114 at prize = $0 and -0.097 at median prize ($32,000), with a highly significant quadratic term (t-statistic = 4.8).
Takeaway
1. Implement quadratic functional specifications or trim extreme upper-tail outliers when modeling labor supply elasticities from skewed financial transfer distributions.
Source and citation
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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 →