allowing tracking enumerators and ensuring the sampling design was implemented. Furthermore, GPS tracking software helped to track devices at all times using a web interface (www.gps‐server.net), the exact path of the devices was recorded even retrospectively and uploaded to the server once they entered areas with 3G/WIFI connection. Given the frequent disruptions and slow rate of data collection their combination provided a useful reference to understand where field teams were at any time, and could be cross‐checked with reports of conflict activity etc. Overall, this system allowed close supervision of the implementation of the sampling design (Pape and Mistiaen, 2014).

# Fieldwork and Insecurity

Sporadic eruptions of fighting meant that teams of enumerators were at times forced to remain idle and wait for the situation to deescalate before reaching certain areas. A few areas that had been subjected to heavy fighting and that may have experienced mass displacement could not be reached at all. Therefore, fieldwork was delayed and the quality of documentation was negatively affected. In the end, despite the relatively long duration of data collection, the final sample fell short of the intended sample. Fortunately, the two‐phased approach described above implies that representative data are already available after the first half of the survey implementation. Indeed, the final sample that was collected during Wave 3 only reaches only about 50 percent of the intended sample size, i.e. the first of the two phases. This was true across all states (Table 4 in Appendix E).

Nevertheless, many of the selected EAs had to be replaced when security rendered field work unfeasible.<sup>15</sup> One hundred EAs were surveyed of the 350 EAs in the original sample, the rest of the 64 EAs were replacement EAs. Replacements were done in three batches where each time new enumeration areas had to be drawn from the master sample frame. The replacement sequence was defined by assigning enumeration areas randomly to the original enumeration areas, maintaining the order of the original enumeration areas as in the original sample. The large number of replacements was concerning given fear of selection bias. Therefore, the team ran checks to ensure that the set of EAs surveyed do not systematically differ from a random sample as best as it could. It is important to keep in mind that assessing representativeness is a difficult task, generally due to the lack of a counterfactual or a point of reference to compare estimates. Despite these checks, it is plausible that selection bias in favor of less conflict‐affected areas leads to an under‐estimation of poverty. The resulting estimates are therefore interpreted as lower‐bound estimates.

The checks are based on comparisons of Wave 3 data from 2016 with the nearest available reference point, Wave 1 data from 2015. Specific outcomes were compared across the two waves as well as at lower levels of aggregation and within specific regions (Table 8 in Appendix E shows an example). This process was severely complicated by the magnitude of the South Sudanese crisis. The conflict, displacement crisis, and near‐hyperinflationary price increases are powerful shocks, which are expected to cause severe disruption even in a relatively short amount of time.<sup>16</sup> The checks therefore concentrated on outcomes that are less likely to be affected by the crises and are relatively time‐ invariant.

Adults’ educational outcomes is one such indicator which is expected to remain relatively stable from one year to the next assuming only small demographic changes. In South Sudan, the adult literacy rate (18+), the proportion of adults with no education, and the proportion of adults with only primary education were comparable between 2015 and 2016 (Table 8). Similarly, cultural norms should be expected to remain stable, such as the prevalence of polygamy and the gender of the household head, both of which are again seemingly unchanged. Some types of infrastructure can provide good indicators if they are not susceptible to be destroyed in the fighting. Mobile

> 15 Replacement EAs were approved by the project manager. Replacement of households were approved by the supervisor after a total of three unsuccessful visits of the household.

> 16 At the very start of Wave 3 data collection year‐on‐year inflation was equal to almost 650 percent. The CPI between the start of Wave 1 and the end of Wave 3 had increased by almost 1,600 percent. Similarly, more than a third of the population was displaced by mid‐2018.

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