Essays on the Economics of Forced Displacement and Conflict

Doctoral thesis (2021)

In Chapter 1, we analyze the determinants of the internal mobility of refugees in Turkey. We track down this mobility relying on geolocalized mobile phone calls data and bring these measures to a micro ... [more ▼]

In Chapter 1, we analyze the determinants of the internal mobility of refugees in Turkey. We track down this mobility relying on geolocalized mobile phone calls data and bring these measures to a micro-founded gravity model in order to estimate the main drivers of refugee mobility across 26 regions in 2017. Our results show that the movements of refugees are sensitive to income differentials and contribute therefore to a more efficient allocation of labor across space. Comparing these findings with those of individuals with a non-refugee status, we find that refugees are more sensitive to variations of income at origin and to distance, while less responsive to changes in income at destination. These findings are robust to the way mobility is inferred from phone data and to the choice of the geographical unit of investigation. Further, we provide evidence against some alternative explanations of mobility such as the propensity to leave refugee camps, transit through Turkey, social magnet effects and sensitivity to agricultural business cycles. In Chapter 2, we exploit annual variations in the presence of refugees to approximate the resulting changes in diversity in the refugee-hosting areas across 23 countries in sub-Saharan Africa. We then assess the relationship between the refugee-corrected diversity indices and the likelihood of conflict between 2005 and 2016. In line with our theoretical framework, the refugee-corrected polarization exacerbates the risk of conflict. A one standard deviation increase in the polarization index raises the incidence of violent conflict by 5 percentage points. Such an effect corresponds to a 10 percent increase, at the mean. The opposite effect is found for the fractionalization index. Our results should not be interpreted as evidence that refugees per se impact the likelihood of violence. Indeed, we do not find any significant correlation between the number of refugees and the occurrence of conflict. Instead, our results point to the risk of conflict when refugees exacerbate ethnic polarization in the hosting communities. On the contrary, a situation where refugee flows raises the level of ethnic fractionalization is likely to see an attenuated risk of violence. This certainly calls for specific interventions in refugee-hosting and polarized communities. We also conduct additional analysis based on individual data and recent COVID-related protests. Results tend to support aggregate results. Refugee-corrected polarization raises the likelihood of experiencing physical assault and interpersonal crime by 2.7 resp. 4.2 percentage points, while no effect can be found for ethnic attachment and trust. Finally, the relevance of our results in the context of the COVID-19 pandemic is explored. In Chapter 3, we study the impact of independent media networks on political accountability during the Arab Spring across the Middle East and North Africa region. The study focuses on two major media networks in the Arab world: Al Jazeera and Al Arabiya. Political accountability is proxied using principally a measure of protests. Data on both political accountability measures and the media networks derive from the Arab Barometer surveys. The regional-level analysis is based on Jordan, Lebanon and Palestine due to data availability. The study uses regional ruggedness as an instrumental variable for the non-random use of independent media among individuals. Results are estimated using a Two-Stage least Squares (2SLS) regression analysis and indicate a positive and significant impact of independent media on political accountability. Several extensions are performed. First, the analysis is replicated for the impact of state media networks and results suggest a significant negative impact on participation to protests. Second, the impact of using independent media for public sector workers' participation to protests is compared with non-public workers. While a significant positive impact of using independent media is found among non-public workers, independent media among public workers seem not to affect their participation to protests. Some channels are tested using additional outcomes such as governmental trust, political alignment, signing petitions and general trust as proxies for political accountability. [less ▲]

Refugee Mobility: Evidence from Phone Data in Turkey

in Salah, Albert Ali; Pentland, Alex; Lepri, Bruno (Eds.) et al Guide to Mobile Data Analytics in Refugee Scenarios: The 'Data for Refugees Challenge' Study (2019)

Our research report employs the D4R data and combines it with several <br />other sources to study one of the multiple aspects of integration of refugees, namely <br />the mobility of refugees across ... [more ▼]

Our research report employs the D4R data and combines it with several <br />other sources to study one of the multiple aspects of integration of refugees, namely <br />the mobility of refugees across provinces in Turkey. In particular, we employ a <br />standard gravity model to empirically estimate a series of determinants of refugee <br />movements. These include the standard determinants such as province characteristics, <br />distances across provinces, levels of income, network effects as well as some <br />refugee-specific determinants such as the presence of refugee camps and the intensity <br />of phone call interaction among refugees. Importantly, we explore the effect <br />of certain categories of news events, notably protests, violence, and asylum grants. <br />Considering news as an indicator of policy implemented at the provincial level, we <br />gain a better understanding as to how policy can facilitate refugee mobility and thus <br />enhance integration. To benchmark our findings, we estimate the same model for the <br />mobility of individuals with a non-refugee status. [less ▲]