Cultural and linguistic barriers may also contribute to the segmentation of migration destinations and restrict the choice set for migrants in Uganda. Matsumoto et al. (2006) find cross-sectional evidence that speaking multiple local languages is positively associated with migration status in Uganda. Muto (2012), meanwhile, uses panel data from 94 rural villages across Uganda to explore the relationship between information and ethnic migration networks. Using cell network coverage as an instrument, she finds that households with a mobile phone are more likely to send out a migrant for employment and that this effect is larger for households with smaller ethnic networks in Kampala. Mwesigye and Matsumoto (2013) also find that communities with a higher relative share of migrants are more likely to experience land conflicts.

Recent work using panel data, meanwhile, offers new insights on migration in the Ugandan context. An analysis on the links between migration and schooling, which uses the Uganda National Panel Survey (UNPS) data sets, finds that attendance drops among schoolchildren whose households have lost an adult due to migration. However, school attendance is found to increase when the child migrates either solo or with his or her parents (Ferrone and Giannelli 2015). Gray (2011) analyzes panel data from three regions in Uganda and finds a positive correlation between high quality soil and non-labor migration. And recent unpublished work using the UNPS sample suggests that remittances can be a vehicle for financial inclusion. The authors rely on household fixed effects estimations and uncover a positive relationship between internal remittances and formal credit (Gross and Ntim 2014).

# **III. Data**

This analysis relies primarily on nationally-representative data from the Uganda National Household Survey (2005/06) and the three successive panel waves of the Uganda National Panel Survey (UNPS, 2009/10, 2010/11, 2011/12). The multi-topic surveys elicit rich sets of information on a range of socioeconomic topics, including consumption and migration. The questionnaires were administered at the individual, agricultural plot, household, and community levels. The original 2005/06 household sample used for this longitudinal analysis is made up of 3,123 households. The final 2011/12 survey wave is composed of 2,835 households, of which three-quarters are drawn from the original sample (Table 1).<sup>4</sup>

**Table 1. Survey attrition by UNHS/UNPS wave**

||**Sample**|**Original sample**<br>**retention(%)**|**Split-off**<br>**HHs**|**Total**|
|---|---|---|---|---|
|2005/06|3,123|100|0|3,123|
|2009/10|2,607|83.5|367|2,974|
|2010/11|2,564|82.1|305|2,869|
|2011/12|2,356|75.4|479|2,835|
|_Source: Ug_|_anda Burea_|_u of Statistics_(2013)|||

These detailed panel data sets allow us to examine spatial mobility in Uganda from a number of different angles. First, in Section IV, we estimate the drivers of a household’s decision to send a permanent work migrant. We focus our analysis on work migrants in that section given the importance of labor mobility for individual welfare and for an economy’s structural transformation and development. To identify households who have sent work migrants, we rely on questions in the household roster regarding the

> 4 All estimates presented here are calculated using statistical weights that take into account the complex survey design and survey attrition. See Uganda Bureau of Statistics (2010) for a detailed discussion of the weighting procedure.

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