the price index between 2011 and February 2016. In the second step, consumption shares of 114 food and 89 nonfood items were aggregated by COICOP code, in combination with weekly price series from the MPS for 109 products. This resulted in 49 matched COICOP codes that were then used to estimate the price index until December 2017.

# 4.3. Imputing consumption data in North‐East and Jubbaland regions

Despite methodological innovations, field team training, and a stringent security protocol (section 3.2), some challenges with data collection persisted in certain geographic areas. These were mainly related to human resource capacity constraints and remote monitoring to ensure the quality of the data. Specifically, in the Jubbaland and rural North‐East regions,<sup>17</sup> the information collected turned out to be only representative of a very small, idiosyncratic part of the population or did not consistently meet the survey’s high‐quality standards.

# Jubbaland

The implementation of Wave 2 of the SHSF required some concessions to the local authorities in terms of the recruitment of field teams. Some enumerators who performed sub‐optimally during training and the pilot were recruited as agreed with local authorities in Jubbaland. Likewise, there were some constraints to replace enumerators during the data collection if they were found to underperform. Based on internal discussions and consultations with trusted team leaders, the SHFS team judged that this affected the quality of the data collected in Jubbaland, particularly of the more demanding consumption modules, compared to other regions. Furthermore, insecurity remained widespread in Jubbaland, mainly due to a strong presence of Al‐Shabaab. The entire region of Middle Juba was excluded from wave 2 of the SHFS due to security reasons. Likewise, large parts of Lower Juba, and to a lesser extent Gedo were also excluded (see Table 1 for accessibility rates by pre‐war region).

In rural Jubbaland, field teams only collected data in areas that were relatively close to main cities (e.g. within a 10‐km radius around Kismayo, Afmadow and Dhobley in Lower Juba). This was due to insecurity and because many rural EAs considered in the sampling frame were found to be empty after reviewing the satellite imagery. The EAs sampled for rural Jubbaland were peri‐urban areas that correspond to large villages or small cities and thus the information was not representative of the rural population there. In addition, data from teams surveying rural Jubbaland showed signs of inconsistency and relatively low quality (highest percentage of invalid submissions compared to other urban and rural areas (Table 4); largest number of flags in the cleaning process of the consumption modules (Table 6), and large differences in the consumption of many food items relative to other rural areas (Table 7)). Interviews with rural households from this region were therefore entirely excluded from the final data set, and poverty estimated from satellite imagery and other geo‐spatial data (section 5).

In urban areas, data collection lasted longer than in any other area covered due to over‐sampling. Insecurity also made it more difficult collecting interviews and thus required more time. Team leaders reported that these issues contributed to fatigue on the part of enumerators, presumably impacting the quality of the data collected in urban Jubbaland.

> 17 Jubbaland region consists of pre‐war regions Gedo, Middle Juba, and Lower Juba (Middle Juba was completely inaccessible). North‐East region consists of pre‐war regions Nugaal, Bari, and Mudug (Table A.12).

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