In this paper, the immigrant-native wage differential is explained through quantile regression estimations. Using repeated cross-sections of the British Labour Force Survey from 1993-2005, we analyse the returns to covariates across the conditional earnings distribution. We estimate a pooled model with an immigrant dummy and separate models for immigrants and natives of the UK. Our results show that the positive wage gap in favour of immigrants is attributed to those at higher quantiles. Returns to education and experience vary wider for natives than for immigrants. We decompose the wage gap in the Blinder-Oaxaca framework and apply quantile regression techniques to see if immigrants simply have more viable labour market characteristics than natives or if there is a preference for immigrant workers (reverse discrimination). Our findings suggest immigrants should actually be earning more and there is sufficient evidence of discrimination. This finding is, however, not symmetric across the conditional wage distribution and immigrants atthe bottom face more discrimination than those at the top
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