Abstract
Our research report employs the D4R data and combines it with several other sources to study one of the multiple aspects of integration of refugees, namely the mobility of refugees across provinces in Turkey. In particular, we employ a standard gravity model to empirically estimate a series of determinants of refugee movements. These include the standard determinants such as province characteristics, distances across provinces, levels of income, network effects as well as some refugee-specific determinants such as the presence of refugee camps and the intensity of phone call interaction among refugees. Importantly, we explore the effect of certain categories of news events, notably protests, violence, and asylum grants. Considering news as an indicator of policy implemented at the provincial level, we gain a better understanding as to how policy can facilitate refugee mobility and thus enhance integration. To benchmark our findings, we estimate the same model for the mobility of individuals with a non-refugee status.
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Notes
- 1.
This strand of the literature builds upon advancements over the last two decades on the use of new technologies such as remote sensing, geographical information systems, and global positioning systems to study mobility patterns in nonemergency contexts [8].
- 2.
Reference [3] detailed the derivation of the random utility maximization model of migration providing micro-foundations to the empirical specification of the gravity model.
- 3.
Under Sect. 22.5, we construct a stricter mobility measure, i.e., we replicate our analysis with a frequency filter of 20 calls.
- 4.
The number of observations results from pairing each province with another province, given the bilateral nature of mobility. We do so for every month of the year 2017. We miss information on night-light for the month of June.
- 5.
It is worthwhile keeping in mind that the number of calls is based on the universe of calls from dataset 1 from [23], whereas our mobility variable is computed using the sample provided from the third dataset.
- 6.
it is also reassuring as to the fact that light density is a good proxy for income per capita at the province level.
- 7.
Complete result tables are available from the authors of this report upon request.
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Beine, M., Bertinelli, L., Cömertpay, R., Litina, A., Maystadt, JF., Zou, B. (2019). Refugee Mobility: Evidence from Phone Data in Turkey. In: Salah, A., Pentland, A., Lepri, B., Letouzé, E. (eds) Guide to Mobile Data Analytics in Refugee Scenarios. Springer, Cham. https://doi.org/10.1007/978-3-030-12554-7_22
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