crop products (e.g., wheat, potatoes) and the value of five livestock products (i.e., milk, egg, butter, hides, and honey) sold in the market.<sup>14</sup> Several other data sources were utilized. First, the Ethiopian refugee camps location data set from the Humanitarian Data Exchange (HDX)<sup>15</sup> and the total number of refugees by camps from the United Nations High Commissioner for Refugees (UNHCR), Addis Ababa office. We use data from 26 official UNCHR refugee camps in Ethiopia that were operational in 2018 (see Figure 1; 3). Second, we use administrative data sets for Ethiopia and refugee source countries from the database of Global Administrative Areas (GADM).<sup>16</sup> We also use the conflict data set from the Armed Conflict Location and Event Data Project (ACLED)<sup>17</sup> and the population data from the Gridded Population of the World (GPW) data set.<sup>18</sup> On the basis of these data sets and the location of sample households from Ethiopia DRDIP data set, we generated the following variables: i) distance of sample households to the nearest refugee camp, the nearest region (administration level 1 in GADM) to the refugee camps, ii) distance of the refugee camps to the nearest border of the refugee source country, iii) the intensity of conflicts, and iv) population density in refugee host countries by region. Appendix B presents the list of variables along with description and summary statistics.

# **5. Empirical strategy**

To estimate the impact of refugee inflow<sup>19</sup> on host community’s livelihood strategy choice, we use the following basic econometric model:<sup>_(1)_</sup> Where, indexes a household, ii ii<sup>+ γγXX</sup> is an outcome variable of interest (livelihood diversification ii<sup>+ νν+ εε</sup> ii YY = αα+ ββR or commercialization of agriculture), R i ii ii YY population (average of 2017 and 2018) in the nearest refugee camp weighted by the inverse of<sup>is the measure of refugee inflow, i.e., the refugee</sup> distance of the household to the refugee camps, is a set of household controls, is kebele fixed effects, and is the error term. ii XX νν Several variables, from the DRDIP data set, were used as controls in our model. These include εεii total livestock values, size of land owned, distance to all weather roads, membership in

> 14 We focus on livestock products as we do not have data on the number of live animals sold.

> 15 https://data.humdata.org/dataset/ethiopia-refugee-camp-locations.

> 16 https://gadm.org/data.html.

> 17 https://acleddata.com/curated-data-files/.

> 18 https://sedac.ciesin.columbia.edu/data/set/gpw-v4-population-count-rev11.

> 19 One could argue that our estimate commingled with refugee camp and international aid. We believe that refugee inflow and refugee camps are the same if most of the refugees live in the camps as the camps and refugee attributes are the same and could be used interchangeably as it is in the literature. We, however, prefer refugee inflow to refugee camp as our main explanatory variable is constructed as the number of refugees weighted by inverted distance. Drawing experiences from Ethiopia and other refugee host communities, we believe that international aid and other benefits coming to our study communities are because of refugee flow (establishment of a refugee camp) and hence should be looked at as a mechanism through which refugee camps (refugee inflow) affects local communities’ livelihood. Unfortunately, we could not get data on refugee related international aid in the communities to undertake a causal mediation analysis. If there is any cause of concern on its omission, the Kebele fixed effects absorb the bias that could arise as refugee induced international aid is less likely to vary within Kebeles. If there are any other international aid programs that are not related with refugee inflow/the establishment of refugee camps, the aids are more likely to be placed at a Kebele level and hence less likely to vary within kebeles and the Kebele-fixed effects absorb most of the variation to mitigate the resulting bias.

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