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Aggregate versus Disaggregate Data in Measuring School Quality

Aggregate versus Disaggregate Data in Measuring School Quality

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OLS 101.94 62.86<br />

Variance Estimates Dis. With<strong>in</strong> Sch. 0.560 0.008<br />

Dis. Between Sch. 0.070 0.012<br />

Agg.With<strong>in</strong> Sch. 0.556 0.444<br />

Agg Between Sch. 0.067 0.015<br />

Note: Results are for 1000 simulations, each <strong>in</strong>clud<strong>in</strong>g 100 schools. The number of students per school is<br />

a lognormal random variable with mean 120 and variance 50000. Mean is the average over all<br />

simulations, RMSE is root mean squared error, Top Ten is the average number of schools ranked <strong>in</strong> the<br />

top ten with the estimator, that belong to the true top ten set. Estimators compared are the disaggregate<br />

estimator, its standardized version, the aggregate estimator, its standardized version, and the OLS<br />

estimator of school effects. Variance estimates are also presented for the disaggregate and aggregate<br />

methods.<br />

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