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International migration is an expensive form of investment, that only households relatively better off can afford. However poorer households have the higher incentive to migrate. Migration decision is conditional on the entry cost, expected returns and risks of migration. This paper, using data from Mexican rural and urban areas, examines the relation between household and community networks and costs and risks of migration focusing on the optimal investment in migration. To investigate an household optimal number of migrants this paper introduces a Three Step procedure to solve simultaneously for the endogeneity of network size and possible selection of migrants. The analysis confirms the inverted U-shaped relation between wealth and migration, stressing the importance of networks particularly in facilitating the migration of social strata belonging to the left tail of the income distribution. Moreover, in presence of sunk costs and/or high initial investment, household and community networks accomplish different functions.

This paper models the dynamic of migration with a particular focus on the cumulative process that causes a variation in the distribution of income in sending communities and therefore a variation in the distribution of skills across different cohorts. The model provides a theoretical framework to Cumulative Causation theory of migration and specifically a theoretical rationale behind the use of migration prevalence ratio to study migration flows. Moreover the model shows how brain drain (in sending communities) and negative cohort effect in terms of education (in receiving communities) are the result of a positive selection of migrants in terms of skills if there is a intergenerational transmission of education.

Among the many studies on migration before the Great War, Italy has received little attention, with a few notable exceptions and without providing a convincing explanation of its economic and demographic determinants. Standard neoclassical approaches explain emigration as driven by relative wages, relative employment rates and the stock of previous emigrants. We aim at improving on earlier contributions by covering all migration outflows from Italy to the most significant destination countries and by adopting the most consistent and up-to-date econometric approaches. As it turns out, the standard model is not fully confirmed and a more nuanced analysis is needed.

AbstractThis study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.