Marginal Priority Group Lottery Instrumentation

In Simple Words

To test if attending a specialty program boosts performance, researchers must ignore applicants who automatically get in due to guaranteed status and applicants who are turned away immediately. Causal evaluation is restricted strictly to the middle group where a random tie-breaker coin flip determined final admission.

Research question

Evaluating the causal impact of attending a chosen school is confounded by self-selection and parental preferences. While oversubscribed lotteries provide quasi-experimental variation, including non-random priority tiers where all applicants are accepted or rejected invalidates instrumental variable identifying assumptions.

Participants

N = 3,065 human students in marginal lottery priority groups out of 37,115 total applicants in Charlotte-Mecklenburg Schools, North Carolina (2,591 with complete baseline data).

Study Design

Two-stage least squares instrumental variables (2SLS/IV) regression using marginal priority group random lottery numbers as instruments for first-choice school attendance, controlling for lottery fixed effects and baseline covariates.

Results

Winning the marginal lottery increased first-choice school attendance by 53.0 percentage points (p < 0.001) and increased attended school test scores by 0.129 standard deviations (p = 0.001), isolating exogenous variation in attendance free from selection bias.

Takeaway

Isolate lottery instrumental variables strictly to oversubscribed marginal priority groups where admission probabilities are strictly bounded between 0 and 1.

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 →

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 →

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