Immigration, Wage Inequality and unobservable skills in the U.S. and the UK

The existing literature investigating the effect of immigration on native-born wages has only addressed the role of observable characteristics (education and experience-between-group) of workers; based on the idea that overall impact of immigration on native wage inequality depends not only on the effects of between-group but also on the effect on within-group inequality (unobservable skills) (Card, 2009) and unlike previous works this paper focuses on the effects of immigration on the residual wage inequality in the UK and US between 1994 and 2006. Using data from Current Population Survey for the U.S. and Labour Force Survey I seek to reconsider whether the rise in immigration observed in those countries can help reconcile one of the 1990s challenges of empirical literature: wage dispersion is not fully explained by variables linked to standard human capital model like education and experience; residual or within-group wage inequality accounts for most of the growth in overall wage inequality. The econometric methodology is based on Lemieux (2006) consisting in a standard variance decomposition and a reweighting approach that allows to control for changes in distributions of observables, by holding skill distribution (education and experience) of the work force constant at a base year. In addition to the original methodology, by adding the immigration dimension this paper also controls for increasing supply of immigration by constructing a weight that holds fix the share of immigrants at a base year. The empirical analysis reveals that wage inequality over all workers is higher than it would have been in the absence of immigration and that residual wage inequality among immigrants is higher than among natives. When the share of immigrants in the labour force is held fix at a base year, the residual components decreases, suggesting that the presence of immigrants can account for a relatively small share (5-6%) of the rise in inequality. However the effect is not causal and composition effects still explains most of the variation.