Europe is recently welcoming a large flow of migrants, mostly from the Asian countries and the southern Mediterranean coast. European policy makers need the tools to understand and manage these migration flows, in order to operationalize the complex adjustment process of immigrants with the economic and social context of European regions. We propose to develop a theoretical model, that explains how two groups of regions, which differ in productivity and public good endowments, compete in tax and public goods for attracting or rejecting migrants. In our framework the less productive regions receive public transfers which increase their panoply of public goods. The model should show that whenever public transfers are sufficiently high, migration to the less productive regions is observed only in the case when the productivity gap between regions is not extremely wide. We want to empirically test the model using a regression discontinuity design to empirically assess the causal relationship between the reception of large amount of public funds - generally spent to finance health, infrastructure and public service investments - and migration flows in the EU-15 regions. We expect a wide expansion in the share of foreign citizens in the high-subsidized regions, when compared to low-subsidized regions with similar pre-treatment characteristics. Our model suggests that previous empirical studies might have underestimated the importance of public goods and services in attracting immigrants. We argue that the use of detailed data at regional level and the adoption of an evaluation strategy which allowed to convincingly isolate the role of public goods and services from economic factors can improve the analysis of the impact of the European Regional Policy on migration flows.
Given the increasing share of the EU budget devoted to the Cohesion Policy since the mid-1970s and the dramatic increase in migratory flows to Europe, the policy¿s contribution to the attraction of migrants is a crucial information to the EU policy makers in shaping the regional distribution of EUF. Our study contributes to this increasingly important topic by making three substantial contributions to the current literature. First, we combine fiscal policy, public goods and migration in a unified setting. Indeed, we consider the effects of tax competition among regions with heterogeneous public goods for attracting labor migration flows, while taking into account the role of a regional policy. Our approach is related to the literature which observes how governments strategically set their taxation to make the net income of residents particularly attractive (Epple and Romer, 1991; Gabszewicz et al., 2016; Razin, 2003; Wildasin, 2006). Nonetheless, as regional policies can hugely enhance the provision of public goods, we complement this literature considering these policies as a tool for improving public goods and services, in shaping the optimal taxation. Second, although there is a vast empirical literature on the economic impact of EUF (see the meta-analysis by Dall¿Erba and Fang, 2017), the linkage between the EU regional policy and migration is arguably an under-researched topic, and regional data on migration are scarce. The two most relevant exceptions are Kessler et al. (2011), who adopt a model of residential and political choice, and Egger et al. (2014), whose analysis is based on a new economic geography model. However, the empirical analyses of these papers are based on country level data, which - considering the regional nature of the policy and the large regional inequalities within most EU countries - lead to a limited explanatory power of the empirical models used. In our empirical analysis, we have created a new dataset containing migration flows among European regions at the NUTS 2 level for the years 2001 and 2011, considering intra- and extra-European migration flows. To the best of our knowledge, it is the first time that a similar dataset has been set up. Finally, the causal relationship between EUF and final destination is evaluated for the first time, using a RDD, which is a quasi-experimental method with a very high internal validity (Lee and Lemieux, 2010).