done so as to ensure a minimum of 10 EAs per combination of urban‐rural and state distinction, according to the following rule: where n� is the sample size in stratum _h, n_ is the total sample size, _H_ is the total number of strata, N� is the total population of stratum _h_ , _N_ is the total overall population, and S� is the standard deviation in stratum _h._ The results from the sample size calculations are shown in Appendix B, Table 3. The chosen sample allocation provides estimates that are representative at the national, urban/rural, and state level. Sampling weights were calculated on the basis of the 5<sup>th</sup> Sudan Population and Housing Census from 2008 (Appendix B). In cases where fewer than 12 households were interviewed in an EA, the sampling weights were adjusted at the EA level to reflect this.

Data collection was intended to be implemented in two phases, by randomly splitting each stratum into two equal‐ sized parts, where each phase of data collection would cover half of the sample. The advantage of a two‐phased approach was early availability of representative data after half of the survey was implemented. The two‐phased approach reduces the risk that an eruption of violence during field work invalidates the representativeness of the survey. However, such an approach is not guaranteed to maintain representativeness if some areas remain inaccessible throughout the entirety of fieldwork. It also comes at the cost of optimizing the organization of fieldwork by reducing the enumerators’ ability to sweep over their intended area.

# Survey Implementation

The survey was implemented using tablets as survey devices. The data collection system consisted of Samsung Galaxy Tablet computers equipped with SIM cards, mobile data plans, microSD cards (16 GB capacity), and external battery packs.<sup>13</sup> Teams of four enumerators and one supervisor were provided with a mobile generator using fuel to ensure that tablets could be charged overnight. Computer Assisted Personal Interviewing (CAPI) data collection can be used to improve data quality by imposing sophisticated systems of constraints on the enumerators’ entries. This was particularly relevant for consumption and price data, which need to be measured precisely as a prerequisite for a reliable poverty analysis. Indeed, CAPI has been experimentally shown to improve data collection while minimizing the potential for enumerator error (Caeyers et al., 2012; Fafchamps et al., 2010). Furthermore, it can be used to create more sophisticated questionnaires, with elaborate conditional skipping patterns that are much easier to implement (De Leeuw et al., 1995).

The rapidly expanding cellular network in South Sudan meant that the data could be transmitted via mobile networks and made available quickly to data analysts (Pape and Mistiaen, 2014). The near real‐time transmission of data to a cloud enabled the implementation of a monitoring system including a dashboard tracking the cumulative number of interviews, the fraction of missing variables, as well as additional quality indicators at any level of disaggregation.<sup>14</sup> This helped to identify challenges in the field work as well as weak enumerators early on and mitigate their impact on data quality, e.g. by providing individually tailored extra trainings for selected enumerators. In addition, the real‐ time analysis code calculates core indicators of the survey, e.g. consumption, educational attainment, and unemployment, to check incoming data while field work is still ongoing. This head‐start on building the analysis code ensures that swiftly after the end of data collection the cleaned data can be made available, which considerably accelerated the process from data collection to the publication of results.

The availability of real‐time data facilitated monitoring by allowing much closer tracking of the geographic progression of fieldwork. The GPS coordinates for each interview were recorded and uploaded along with the data,

> 13 The Android application AirDroid was used to remotely manage devices, this remote management software meant that errors in the tablet configuration were detected and could be solved by updating the tablets remotely in cases where enumerators may have needed help from the survey analysts.

> 14 In areas without 3G activities, enumerators saved conducted interviews on the tablet and submitted data once they had 3G connectivity.

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