Abstract
Archived Content
Information identified as archived is provided for reference, research or recordkeeping purposes. It is not subject to the Government of Canada Web Standards and has not been altered or updated since it was archived. Please "contact us" to request a format other than those available.
This paper studies the effect of selective attrition on estimates of immigrant earnings growth based on repeated cross-sectional data in Canada. Recent evidence from longitudinal data in the United States shows that the earnings gap between immigrants and the U.S.-born closes more slowly over time in the years following landing than previous cross-sectional estimates have suggested. This is because results based on repeated cross-sectional data contained a bias introduced by selective attrition of immigrants. This study uses longitudinal tax data linked to immigrant landing records in order to estimate the change in immigrant earnings and the immigrant-Canadian-born earnings gap. The results are compared with those from repeated cross-sectional data. When one focuses on the earnings growth of immigrants, earnings trajectories based on repeated cross-sections are found to be biased marginally upwards as a result of selective immigrant attrition. However, no evidence is found of a bias in the trajectory of the immigrant-Canadian-born earnings gap on the basis of repeated cross-sectional data in Canada. While low-earning immigrants are more likely than their high-earning counterparts to leave the cross-sectional samples over time, the same is true of the Canadian-born population. Thus, no evidence of a bias is observed when one compares immigrant earnings trajectories with the trajectories of the Canadian-born.
JEL classifications: J31, J61
Keywords: immigration, assimilation, longitudinal data, selection bias
- Date modified: