The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper outlines a procedure to obtain jackknife estimates for several inequality indices with only a few passes through the data. The number of passes is...

The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper outlines a procedure to obtain jackknife estimates for several inequality indices with only a few passes through the data. The number of passes is...

The jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper develops fast algorithms for jackknifing inequality indices with only a few passes through the data. The number of passes is independent of the...

Two prominent features of international labor movements are that the more educated are more likely to emigrate (positive selection) and more-educated migrants are more likely to settle in destination countries with high rewards to skill (positive sorting). Using data on emigrant stocks by...

Two prominent features of international labor movements are that the more educated are more likely to emigrate (positive selection) and more-educated migrants are more likely to settle in destination countries with high rewards to skill (positive sorting). Using data on emigrant stocks by...