ADJUSTING THE UNITED-STATES CENSUS OF 1990 - LOSS FUNCTIONS

Considering the difficulties, the Census Bureau does a remarkably good job at counting people. This article discusses techniques for adjusti ng the census. If there is a large undercount, these techniques may be accurate enough for adjustment. With a small undercount, adjustment c ould easily degrade the accuracy of the data. The Bureau argued that e rrors in the census were more serious than errors in the proposed adju stment, using ''loss function analysis'' to balance the risks. This pr ocedure turns out to depend on quite unreasonable assumptions With oth er and more realistic assumptions, the balance favors the census. The story has a broader moral. Statistical models are often defended on gr ounds of robustness. However, internally generated measures of precisi on may be critical. If the model is at all complicated. these measures of precision may turn out to be driven by assumptions not data-the an tithesis of robustness.