Andrea Carlomaria Caflisch

Existing accounts of return after forced displacement emphasize current security conditions. Yet present violence is a poor predictor of returnees' future prospects. This paper investigates the relationship between the institutions responsible for security provision and return. I argue that prospective returnees rely on the responsiveness and military capacity of local security providers as signals of future stability. In ethnic conflicts, this relationship is moderated by the geographical distribution of ethnic groups and by control over the central state. I test this theory using granular administrative and survey data from South Sudan. I show that security provision by community-based militias — in-group responsive actors with high military capacity — is associated with more permanent return. Difference-in-differences estimates demonstrate that their effect is concentrated in ethnic borderlands inhabited by the state-controlling group, a pattern consistent with evidence of state repression of minority militias. In line with the theory, shifts in local control to community-based militias also drive economic recovery and changes in security conditions.

How does formalizing property rights affect welfare when only some parties gain recognition? We study the randomized rollout of a national land certification programme in Côte d'Ivoire, in which owners received titles but the land users cultivating their fields under customary leases did not. Land owners gain tenure security and move onto their own fields and out of wage employment. By contrast, land users do not gain tenure security and become more likely to skip meals, yet they invest in tree planting as much as owners — a response concentrated among migrant users, whose claims are weakest. We interpret this as defensive investment by users whose relative standing has weakened, and argue that the effects on both groups operate through changes in dispute resolution. Demand for third-party adjudication falls for owners and users alike: with a public record of who holds legitimate claims, parties settle disputes directly rather than contest them. Users shift away from customary chiefs, who lose the discretion to mediate. An embedded conjoint experiment shows that having a title is the strongest determinant of willingness to appeal and of the adjudicator's perceived favourability — more so than the authority, cost, or the opponent's identity — thereby shifting bargaining power towards titleholders. Selective formalization can therefore reduce open contestation while widening the gap between those whose property rights are made legible and those left out.

Can targeted recovery aid rebuild livelihoods without undermining social cohesion? We study a $2,000 capital grant program in post-conflict Iraq, measuring economic outcomes and social cohesion. We designed an RCT to identify direct effects on beneficiaries and indirect effects on their first-degree social ties and professional peers. The design links applicants to pre-treatment referral networks, which allows us to test whether recovery aid has economic benefits for or generates resentments among applicants' social and professional networks. Grants produce large economic gains for recipients that strengthen over time, raising business ownership by 23.8 percentage points and business revenues by 0.79 SD by twelve months. They also reduce recipients' grievances and perceived competition and increase interpersonal trust. For social ties and professional peers, grants do not affect economic outcomes or broader community attitudes, including trust, civic engagement, and inclusion; confidence intervals rule out indirect exposure effects larger than 0.20 SD. However, grants increase grievances directed toward treated applicants, by 0.16 SD among social ties and 0.24 SD among professional peers, with effects persisting across both survey waves. Evidence suggests this social cost arises when relative deprivation is coupled with unmet sharing expectations directed at beneficiaries. Early increases in trade, debt, and transfers fade, and directed grievance appears without changes in non-recipients' own economic standing. Taken together, the results show that targeted recovery aid can improve recipients' livelihoods and reduce their grievances, while creating localized social costs in the network relationships where informal redistribution is expected.

Political science research often studies difficult-to-locate populations: internally displaced persons (IDPs), returnees, migrants, and others who move during war, disaster, or crisis. We compare machine-learning (ML)-generated building footprints against high-resolution satellite imagery for constructing sampling frames. In displacement-affected communities in Iraq, 15.5% of ML points were invalid or duplicated, and manual additions constituted 19% of the final hybrid frame. Manual additions reached 10.2 percentage points more IDPs in rural communities and 10.1 more returnees in urban areas. We attribute differences to two mechanisms: temporary and informal shelters are harder for ML algorithms to detect, while post-bombardment reconstruction can create structures absent from the imagery underlying ML frames. ML-only frames produce systematic coverage error, and targeted satellite validation can reduce it.

Abstract coming soon.

Abstract coming soon.

Migration is one of the defining issues of the 21st century. Better data is required to improve understanding about how and why people are moving, target interventions and support evidence-based migration policy. Big data, defined as large, complex data from diverse sources, is regularly proposed as a solution to help address current gaps in knowledge. The authors participated in a workshop held in London, UK, in July 2019, that brought together experts from the United Nations (UN), humanitarian non-governmental organisations (NGOs), policy and academia to develop a better understanding of how big data could be used for migration research and policy. We identified six key areas regarding the application of big data in migration research and policy: accessing and utilising data; integrating data sources and knowledge; understanding environmental drivers of migration; improving healthcare access for migrant populations; ethical and security concerns around the use of big data; and addressing political narratives. We advocate the need for careful consideration of the challenges faced by the use of big data, as well as increased cross-disciplinary collaborations to advance the use of big data in migration research whilst safeguarding vulnerable migrant communities.

Relatively few coronavirus disease cases and deaths have been reported from sub-Saharan Africa, although the extent of its spread remains unclear. During August 10–September 11, 2020, we recruited 2,214 participants for a representative household-based cross-sectional serosurvey in Juba, South Sudan. We found 22.3% of participants had severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor binding domain IgG titers above prepandemic levels. After accounting for waning antibody levels, age, and sex, we estimated that 38.3% (95% credible interval 31.8%–46.5%) of the population had been infected with SARS-CoV-2. At this rate, for each PCR–confirmed SARS-CoV-2 infection reported by the Ministry of Health, 103 (95% credible interval 86–126) infections would have been unreported, meaning SARS-CoV-2 has likely spread extensively within Juba. We also found differences in background reactivity in Juba compared with Boston, Massachusetts, USA, where the immunoassay was validated. Our findings underscore the need to validate serologic tests in sub-Saharan Africa populations.