Using novel registry data on persons receiving asylum welfare benefits in Germany for the period from 2010 to 2016, and quasi-experimental variation induced by German allocation policies, we identify the role that the size and composition of local co-national networks of asylum seekers play for formal labor market access within the same group. While the individual employment probability is not linked to network size, it increases with the number of employed local co-national asylum seekers and decreases with the number of nonemployed network members, thereby underlining the central importance of network quality.

Background Assessing the impact of government responses to Covid-19 is crucial to contain the pandemic and improve preparedness for future crises. We investigate here the impact of non-pharmaceutical interventions (NPIs) and infection threats on the daily evolution of cross-border movements of people during the Covid-19 pandemic. We use a unique database on Facebook users’ mobility, and rely on regression and machine learning models to identify the role of infection threats and containment policies. Permutation techniques allow us to compare the impact and predictive power of these two categories of variables. Results In contrast with studies on within-border mobility, our models point to a stronger importance of containment policies in explaining changes in cross-border traffic as compared with international travel bans and fears of being infected. The latter are proxied by the numbers of Covid-19 cases and deaths at destination. Although the ranking among coercive policies varies across modelling techniques, containment measures in the destination country (such as cancelling of events, restrictions on internal movements and public gatherings), and school closures in the origin country (influencing parental leaves) have the strongest impacts on cross-border movements. Conclusion While descriptive in nature, our findings have policy-relevant implications. Cross-border movements of people predominantly consist of labor commuting flows and business travels. These economic and essential flows are marginally influenced by the fear of infection and international travel bans. They are mostly governed by the stringency of internal containment policies and the ability to travel.

We study the impact of a portable "soft" commitment device on the financial behavior of low-income slum dwellers in Maharashtra, India. 1525 individuals were randomly allocated to receiving either a zip purse and a lockbox (treatment arm) or a lockbox only (control arm). Based on self-reported measures and hand counts of money held in the distributed saving devices, we document an 81% increase in total savings in the treatment group. We do not find significant reductions in temptation spending, thus suggesting that increases in savings were not primarily realized through improvements in self-control. Instead, we suggest that reduced sharing obligations are driving the effect. In additional analyses, we document a 35% decrease in past-month transferst of cash to other household members. Hence, our findings suggest that saving can be more effectively promoted by alleviating access-related rather than behavior-related constraints and by giving women access to a saving device of their own.

BackgroundWe use a unique database on Facebook users’ mobility to study the daily evolution of cross-border movements of people during the Covid-19 pandemic. To limit censoring issues, we focus on 45 pairs of European countries, and document the changes in daily traffic during an entire pandemic year. We rely on regression and machine learning models to identify the role of infection threats and containment policies. Permutation techniques allow us to compare the impact and predictive power of these two categories of variables. ResultsIn contrast with studies on within-border mobility, our models point to a stronger importance of containment policies in explaining changes in cross-border traffic as compared with international travel bans and fears of being infected. The latter are proxied by the numbers of Covid-19 cases and deaths at destination. Although the ranking among coercive policies varies across modelling techniques, containment measures in the destination country (such as cancelling of events, restrictions on internal movements and public gatherings), and school closures in the origin country (influencing parental leaves) have the strongest impacts on cross-border movements. ConclusionWhile descriptive in nature, our findings have policy-relevant implications. Cross-border movements of people predominantly consist of labor commuting flows and business travels. These economic and essential flows are marginally influenced by the fear of infection and international travel bans. They are mostly governed by the stringency of internal containment policies and the ability to travel.