|Observations|5,453|5,450|4,105|4,102|
|---|---|---|---|---|
|Root MSE|0.581|0.582|0.612|0.593|
|**_Included controls_**|||||
|Exogenous controls (age, agesq, sex “male==1”)|_No_|_Yes_|_Yes_|_Yes_|
|Other controls (HH size, marital status, education,<br>occupation, other income sources, land ownership)|_No_|_No_|_Yes_|_Yes_|
|Year fixed effects|_Yes_|_Yes_|_Yes_|_Yes_|
|Cluster fixed effects|_Yes_|_Yes_|_Yes_|_No_|
|Household fixed effects|_No_|_No_|_No_|_Yes_|

_Notes: Panel A are the results from the OLS, Panel B represents the second stage of the IV regression and Panel C shows the first stage results from the IV regression. Apart from HH size, the more endogenous controls added are as at the base year of the study. In Regression (4) where household fixed effects replace the cluster fixed effects, all the time invariant variables drop off (only age, agesq & male remain). Sampling weights are considered and Standard errors clustered at the cluster level in all regressions. Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1. The detailed results are presented in Tables A7, A9, and A10._ Several robustness tests confirm the positive effects of the refugee presence on the household welfare. For instance, when constructing the instrumental variable, the parameter of the decay function was modified to give more or less weight to the proximity between the country of origin border point and the destination clusters. The IV regressions with the instruments constructed by dividing the number of refugees from country _O_ by the square or the square root of the distance between border points and the clusters also show similar elasticities between 0.08 and 0.14, for households within 50km and 100km of the closest refugee settlements.<sup>14</sup> Even when Kampala district is included in the analysis, the estimated coefficient remains in the same range across the decay functions of the instrument, for households within the 50km and 100km of the closest refugee settlements.<sup>15</sup> In our main results we do use the average distance to border crossing points for each cluster to construct the instrumental variables. Using the distance to the closest crossing point would not alter much the result, only pushing upward the estimated second-stage coefficient of interest.<sup>16</sup> The results therefore show that the presence of refugees has a significantly positive effect on household welfare. Living closer to refugee settlements is beneficial to the host populations.

# **5.2. The identifying assumption**

The causal identification of a positive impact of refugees on the hosts’ welfare rests on key identifying assumptions. First, the instrument is sufficiently relevant as shown by the relatively high values – above 14 – in the Kleibergen-Paap rk Wald F statistics (see Panel B of Table 3). Second, we assume

> 14 See Appendix 4, Tables A9 & A11; columns 8 & 12. The first stage results are reported in Tables A10 & A12 respectively.

> 15 See Appendix 4, Tables A13 & A15; columns 4, 8 & 12. The first stage results are reported in Tables A14 & A16 respectively.

> 16 See Appendix 4, Tables A17 & A19; column 4, 8 & 12). The first stage results are reported in Tables A18 & A20 respectively.

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