Simon Winter’s research while affiliated with University of Münster and other places

The present study empirically analyzes determinants of immigration to EU member countries for the period 1998–2016. By performing PPML regression, it investigates the dynamics of different political and economic determinants. In general, there are two opposing effects: better living conditions in the origin country increase the feasibility of migration (feasibility hypothesis), but they also decrease international differentials, thus diminishing the incentive to migrate (incentive hypothesis). Indeed, better economic conditions in the origin country ease the budget constraints of potential migrants and thereby stimulate emigration to EU countries (feasibility hypothesis). At the same time, the income differential between destination and origin country is also positively related to migration, supporting the incentive hypothesis. Contrary to these findings about economic determinants, the impact of political determinants is only robust in one direction, for migration from outside the EU. Here, worse political conditions in the origin country increase the need to migrate, causing flight migration (need hypothesis). Altogether, economic determinants appear to outweigh political factors.

In the context of the German energy transition, the financial burdens associated with subsidies for renewable energies have increased substantially in recent years. These costs are passed on to consumers in the form of the EEG levy as a component of the electricity price. However, some households benefit from owning photovoltaic (PV) systems because they receive the corresponding feed-in tariffs. In order to investigate how the benefits (and burdens) of this subsidization scheme are distributed, we use micro-data from SOEP for private households during the period of 2010–2017, and we employ three different inequality metrics – the Gini coefficient, the Theil index and the Atkinson index. We conclude that subsidy costs are almost evenly distributed among the population and are therefore regressive. At the same time, feed-in tariffs are increasingly flowing into higher-income households because PV systems are more prevalent in these households. We estimate the overall impact of this subsidization scheme on several measures of (income) inequality at 1.0–2.4%, most of which is due to the EEG levy. We also find regional distortions in favor of the South and especially at the expense of the East.

The German energy transition and the rising share of renewable energies in electricity generation have led to an increase in network costs and to higher network charges in recent years. We use socioeconomic data in order to investigate distributional effects within the period 2010-2016, and employ three different inequality metrics – the Gini coefficient, the Theil Index and the Atkinson index – all of which unambiguously indicate regressive effects of network charges. Most recently, the three metrics show an increase of economic inequality of at least 0.67% when accounting for network charges. This finding is due to (1) the relative inferiority of electricity, (2) the regressive impact of a fixed component of network charges, (3) considerable regional disparities, and (4) the higher prevalence of prosumers within high-income households.