The paper will make use of data from the completed Mogadishu pilot survey and geo‐referenced maps and three example EAs to explore the following questions: (1) How might a given method be implemented in the field, given the information available and the security constraints? (2) What information is necessary to generate sampling weights, necessary for representative estimates, and how should those weights be calculated? (3) What are the implications in terms of precision and bias for each of the methods described above? (4) What are the implementation concerns for each method, including the options for verification and the impact of non‐household structures?

The next section briefly describes the literature as it relates to the questions above, followed by section 2 describing the data. Section 3 addresses research questions 1 and 2 by giving further detail on the methods considered. Section 4 presents simulation results covering questions 3 and 4. Section 5 concludes by offering some discussion of the overall performance and potential future applications.

# **1. Literature Review**

The most common method for collecting household data in Sub‐Saharan Africa is to use a stratified two‐ stage sample, with census enumeration areas selected proportional to size in the first stage and a set number of households selected with simple random sampling in the second stage (Grosh and Munoz, 1996). Since administrative records are often incomplete and most structures do not have postal addresses, as is the case in Mogadishu, a household listing operation is usually necessary prior to the second‐stage selection. However, due to the security concerns cited above, listing was not feasible.

A number of alternatives for second stage selection can be used when household lists are not available. A common alternative used in both Europe (see Bauer, 2014, for recent examples) and in the developing world is a random‐walk. The Afrobarometer survey, which has been conducted in multiple rounds in 35 African countries since 1999, and the Gallup World Poll, which conducted surveys in 29 Sub‐Saharan African countries in 2012, use random walk methodologies. Although the random walk methods do not necessarily produce equal probability samples, they do not collect any information with which to calculate probabilities of selection. For this reason, weights are not calculable for random walk samples; instead, the samples are analyzed as if they were equal probability. Bauer (2014) shows that this assumption is not correct by simulating all possible random routes using standard procedures within a German city and finds substantial deviation from equal probability. These results apply even when interviewers perfectly implement the routing instructions, which is unlikely given the limited ability to conduct in‐field supervision of random walk selection and strong (though understandable) incentives for interviewers to select respondents who are willing to participate (Alt et al 1991). Several other studies have also shown that data collected via random walk do not match the population on basic demographics such as age, sex, education, household size, and marital status (Bien 1997, Hoffmeyer‐Zlotnick 2003, Blohm 2006, Eckman & Koch 2016).

In the context of Mogadishu, a household listing was too dangerous and costly, a random walk too biased, and no household or person register existed. Therefore the researchers explored several alternative methods using a combination of satellite maps and area‐based sampling. As satellite technology has improved in quality and become more readily available, it has been increasingly used for research in the developing world. Barry and Rüther (2001) and Turkstra and Raithelhuber (2004) use satellite imagery to study informal urban settlements in South Africa and Kenya, respectively. Aminipouri et al (2009) use 3