which act as the primary sampling units from which households are selected.<sup>24</sup> Individuals within households are enumerated in a full roster; individuals are tracked if they leave a household, though this does result in some individual-level attrition. Starting in 2010, 5,000 households in 500 enumeration areas were selected for the panel dataset; however, due to attrition, by the fourth round (2018–2019), a refresh sample of 360 enumeration areas was required.

Due to this sampling design, two points merit some attention. First, non-random attrition poses a challenge to identification. If, for example, attriting individuals are more or less likely to be those that engage in a particular type of economic activity, estimates will be accordingly biased. A related but distinct concern is that attrition itself is related to violent events, which would make treatment endogenous to violence in the sample. Second, the sampling procedure for the fourth round of the GHS included new enumeration areas. Since the main treatment (e.g., exposure to violent events around the farmer-herder conflict) is determined by location, a panel including those new enumeration areas would be inappropriate and therefore, the refreshment enumeration areas are excluded from all analysis of panel data, where individuals (households) appear over multiple rounds of the GHS. We discuss the relative risk to bias from attrition and our approach to account for non-random attrition below.

The second data source is a panel of violent events taken from the Armed Conflict Location and Event Data (ACLED) project (Raleigh _et al._ , 2010). The ACLED project provides several pieces of detailed information, including the approximate date and geo-coded location of an incident, as well as reported information on primary and associated actors in each event. The recorded events are based on accounts from media, NGOs, international organizations, partner reports, and new media (e.g., social media such as Twitter or Facebook). A single account can include several events (as would be the case of one news article describing a series of violent attacks), however, the ACLED database includes one observation per event-location.

We use the detailed information provided by the ACLED project to code individual events. Since the ACLED project also provides information on events such as treaties and peaceful protests, events are classified as i) violent and/or ii) herder-related. Violent events are defined as those with an ACLED coding with a clearly defined violent event type or sub-type. These events include attacks, murders, and kidnappings, but also civil unrest (e.g., mob violence), which may emanate from reprisal or public reaction. The violent destruction of property (such as arson or burning of fields) is also included, given that such events were frequent around the farmer-herder conflict. All fatal events are considered violent.

We code all incidents as herder-related if they include the terms “pastoralist,” “herder,” or “herdsmen” as either an actor or associated actor.<sup>25</sup> As noted above, the incident data largely rely on public accounts, and so one risk is that the narrative framing of events could affect the terms used to record each event in the ACLED database. This would occur if terms like “herder” are used when these groups were considered perpetrators, but if another term is used when such groups were the victims of, say, reprisal violence. To

> 24Nigeria includes 6 geopolitical zones, which are one administrative level up from states.

> 25Or variants of these terms, including e.g. “Herder.”

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