The current study examines the importance of country of origin in predicting the labour market earnings among recent immigrants to Canada. The authors argue that, in addition to individual-level characteristics associated with immigrant capital, macro-level features associated with immigrant origins must be taken into account when considering the economic performance of immigrants in their host country. Country-level factors are said to accompany immigrants to their destination country, which generate disparities in the "quality" of immigrants' human and social capital across origin groups, as well as differences in how they are received by the resident population. The present study uses random effects multilevel modelling to investigate the extent to which immigrant incomes vary randomly across source country while taking into consideration individual-level characteristics selected on the basis of human capital, social capital, and discrimination theories. Multilevel regression analysis confirms that immigrant incomes indeed vary significantly by country of origin, though the effect is small. Furthermore, it is revealed that the gross domestic product (GDP) of the sending country explains much of the level 2 variability in the labour market earnings of recent immigrants, as well as the relationship between racial minority status and immigrant incomes. The practical significance and policy implications of these findings are discussed. © 2010 The Authors. International Migration © 2010 IOM.

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international migration Canada immigration policy prediction immigrant social capital labor market human capital