survey.<sup>10</sup> In the first round, 3,295 observations completed interviews. This sampling frame is complemented using Random Digital Dialing (RDD) to ensure that all households that existed in 2020 and who had access to a phone are considered, regardless of whether they had a phone in 2015/16. Using RDD, we generate 93 million phone numbers among which a random subset of 5,000 numbers were sent an introductory SMS to confirm operational capability. 4,075 numbers were confirmed active out of which we successfully interviewed 763 households in the first wave. Based on the collected data, we classify respondents from the national samples into three groups: 1) existed in 2015/16 and did not change number; 2) existed in 2015/16 but changed number; 3) did not exist in 2015/16. The KIHBS households are representative of type-1 households while the RDD households are representative of type-1, 2 and 3 households. We merge the two samples by adjusting weights for KIHBS households and RDD type-1 households to account for the possibility of double-selection.<sup>11</sup> The refugee sample was constructed using four strata: Kakuma camp, Dadaab camp, Kalobeyei settlement and urban refugees. For refugees in Kakuma and Kalobeyei, sampling was based on previously conducted representative socioeconomic surveys (UNHCR & World Bank, 2020; UNHCR & World Bank, 2020; UNHCR & World Bank, 2020), while for urban refugees and refugees living in Dadaab no such data was available, and sampling was based on phone numbers obtained from official UNHCR registration records (proGres). For each stratum, 1,000 phone numbers were drawn and sent an introductory SMS. From the list of active numbers 500 households per stratum and 375 replacements were drawn, from which 1,326 households were interviewed in total in the first wave, 1,687 in the second wave, 1,469 in the third wave, 1,357 in the fourth wave and 1,536 in the fifth wave.<sup>12</sup>

# **3.2 Variable definitions**

We measure the extensive margin by an employment indicator which equals one for any refugee aged 18 to 64 who was employed or self-employed in agriculture or other nonagricultural household businesses and equal to zero if an individual was not working in a given period. To construct a pre-COVID-19 employment indicator we use a set of retrospective questions available from waves 2 to 4 which ask for every household member if they were working in either wage work, household businesses or agriculture in February 2020.<sup>13</sup> We also use work stoppages measured by the proportion of individuals who were employed before COVID-19 and who stopped working afterwards. We construct an indicator equal to one if an individual worked in February 2020 and did not work at time the time of interview. Work stoppage equals to zero when an individual was working both before COVID-19 as well as at the time of interview.

For measuring the intensive margin of labor supply, we consider hours worked per week and monthly per capita household income. Total hours worked is only available for wave 1 to 5 (without retrospective questions for before wave 1) and defined for each adult member in

> 10 The Kenya Integrated Household and Budget survey is nationally representative of the population of Kenya and is administered by the Kenyan Bureau of Statistics (KNBS) using computer assisted personal interviewing (CAPI) methodology.

> 11 We multiply weights with 1/(number of phone numbers the household uses) such that households with more phone numbers, which are more likely to be called randomly in the RDD, receive a lower weight.

> 12 For a detailed discussion on the construction of survey weights for refugees, please see the appendix. For a discussion on survey design and representativeness, we provide detailed information in the methodological annex of our in-depth survey report (World Bank, 2021).

> 13 Unfortunately, retrospective questions on agricultural and enterprise work were not available at the household member level in wave 1.

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