Mind the Gap: A Detailed Picture of the Immigrant-Native Earnings Gap in the UK Using Longitudinal Data Between 1978 and 2006

Sara Lemos

No 6058, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Using the underexplored, sizeable and long Lifetime Labour Market Database (LLMDB) we estimated the immigrant-native earnings gap across the entire earnings distribution, across continents of nationality and across cohorts of arrival in the UK between 1978 and 2006. We exploited the longitudinal nature of our data to separate the effect of observed and unobserved individual characteristics on earnings. This helped us to prevent selectivity biases such as cohort bias and survivor bias, which have been long standing unresolved identification issues in the literature. In keeping with the limited existing UK literature, we found a clear and wide dividing line between whites and non-whites in simple comparable models. However, in our more complete models we found a much narrower and subtler dividing line. This confirms the importance of accounting for unobservable individual characteristics, which is an important contribution of this paper. It also suggests that the labour market primarily rewards individual characteristics other than immigration status. We also found that the lowest paid immigrants, whom are disproportionately non-white, suffer an earnings penalty in the labour market, whereas higher paid immigrants, whom are disproportionately white, do not. Finally, we found less favourable earning gaps for cohorts that witnessed proportionately larger non-white and lower paid white immigration.

Keywords: immigration; wages; earnings; earnings-gap; UK (search for similar items in EconPapers)
JEL-codes: F22 J24 J31 J61 J71 J82 (search for similar items in EconPapers)
Pages: 42 pages
Date: 2011-10
New Economics Papers: this item is included in nep-lab, nep-lma and nep-mig
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Related works:
Journal Article: Mind the gap: A detailed picture of the immigrant-native earnings gap in the UK using longitudinal data between 1978 and 2006 (2017)
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