departures of previous household members and their primary motivation for leaving the household. Any household that reported having at least one member (aged 15 or older) permanently leave the household in the 12 preceding months for work is considered as having sent out a work migrant.

Next, in Section V, to identify the causal impact of migration on poverty, we draw on a sub-sample of the UNPS panel data sets, using the 2005/06 and 2009/10 rounds, for which an intensive individual and household tracking exercise was conducted. Two households per enumeration area (approximately 20 percent of surveyed households) from the 2005/06 sample were randomly selected for intensive tracking during the 2009/10 UNPS round. Survey enumerator teams relied on available contact information and local resource persons to locate those households within the tracking sample that had permanently moved. In addition, any individuals who had left their original 2005/06 household during the intervening period (referred to as “split-offs”) were also tracked.<sup>5</sup> This yielded a total panel sample of 15,646 individuals who did not move, 1,163 individuals from intact mover households, and 1,791 split-off individuals who had migrated from their original household during the intervening period. The information collected by the tracking teams allows us to construct an individual-level panel of those who remained in their 2005/06 place of residence (referred to here as “stayers”) and those who migrated elsewhere (referred to here as “movers”). In line with the lag of four to five years between the first two surveys, individuals aged at least 10 during the 2005/06 survey wave are retained in the panel sample as they may be migrants during the 2009/10 survey wave. The structure of this tracking data set is presented in greater detail in Section V.

To construct a set of explanatory variables for these analyses, we also draw on complementary data sources, including the ACLED (Armed Conflict Location and Event Data) database (Raleigh et al. 2010), the WRSI (Water Requirement Satisfaction Index) computed using FAO data (World Bank 2011), 2002 national census data (Minnesota Population Center 2015), and market price data collected by the Uganda Bureau of Statistics.

# **IV. Drivers of household migration decisions**

In this section, we focus our analysis at the household level, arguably the central locus of decision-making around migration, to examine the drivers behind sending out a work migrant. We draw here on information from the UNPS household roster on the residential status of individuals in the household and, for those who have left, their reason for out-migration.<sup>6</sup> We use this information to construct our outcome variable of interest, whether a household has sent a permanent migrant (aged 15 and above) for work in the preceding 12 months. To analyze the potential drivers of this household migration decision, we rely on a multivariate framework that exploits the panel dimension of the survey data.

To examine the correlates associated with a household’s decision to send a permanent work migrant, we first consider the following linear probability model:

> 5 The robust individual-level tracking exercise took place for those household members who no longer resided in their original 2005/06 location and who were related to the household head biologically or through marriage. Servants and non-relatives living in the household were not tracked.

> 6 The reason for out-migration is reported by the household members still residing in the household. With the exception of the sub-set of households and individuals included in the tracking sample, no information was collected on these out-migrants after their departure from the household. Moreover, issues with missing observations and limited information on the type (rural or urban) of out-migrant destination prevent us from analyzing the household’s decision to send a migrant to a rural or urban area. This question is analyzed in detail in Section V.

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