This paper estimates the returns of education on the first generation of immigrants in Italy and measures the education pay gap between immigrants and natives. The analysis, drawn on two comparable cross-sectional surveys conducted by the Italian Institute of Statistics in 2009, shows that an immigrant with a tertiary education degree has a 20% increase in hourly wage compared to immigrant workers with a postsecondary education degree. The absence of a legal recognition of the education degree does not produce any return to education for the immigrants. Relevant differences in educational returns are found between immigrants and natives, with an education wage gap of approximately 61%. These results shed new light on the two channels that may contribute to the wage gap between highly educated immigrants and natives in Italy. The first channel moves behind the heterogeneity of highly educated immigrants with respect to their education quality and comparability and on relevant differences in the formal process of recognition of the education degree. The second channel is linked to the job mismatch of the immigrant workforce.

Much of the literature on the determinants of migration considers push and pull and while conflict is considered a push factor it has received surprisingly little empirical scrutiny. When it has the focus is on the most visible result, refugee flows. While political oppression, economic adversities and environmental degradation are important determinants of migration, conflict and wars account for the bulk of low income country refugees and migrants. This paper considers the role that conflict plays in migration, beyond refugee flows, across a range of countries for which data is available. It estimates the impact of conflict on migration allowing for other important factors and different measures of conflict. A large effect of conflict on net migration is found for low income countries. 

ABSTRACT

This paper evaluates the wage effects of a tax credit policy on new hirings in Southern Italy. We use high-quality administrative data and propose a latent class inverse probability weighting method as a strategy to account for workers' unobserved heterogeneity. We find an unexpected negative effect of the tax cut on the wages of treated workers, which is more marked for women. Our results also provide new insights on the job-segregation dimension of the gender gap. We provide a theoretical model with worker and firm fixed effects to analyse the impact of employer tax cuts as a place-based policy in lagging regions. 

ABSTRACT

Inequality in South Africa is the enduring legacy of racial discrimination. We use a dynamic perspective to show the linkages between persistent effects of discrimination in the labour market and the efficacy of redistributive fiscal policy in reducing inequality. We present a machine-learning analysis based on household survey data in the Post-Apartheid Labour Market Series to predict the main drivers of the relationship between workers’ heterogeneous socioeconomic characteristics, the behaviour of variables related to labour market status, and labour income inequality. The empirical investigation covers the period 2000–17. Drawing on this preliminary evidence, we build a dynamic stochastic general equilibrium model with a dual labour market and job search frictions that represents the structural features of South Africa’s economy, which can be used to assess the effects of fiscal policy on inequality in the postapartheid period and to simulate the effects of alternative fiscal measures and labour market reforms.