7 own right for evaluating or monitoring the impact or outcomes of a certain intervention, the data collected through such a survey cannot be used to generate reliable statistics for any population outside the beneficiaries (or control group if any) of that particular project or program. Examples of project-specific datasets include energy monitoring framework survey, program monitoring beneficiary survey, postdistribution monitoring survey, among others. As we note in the following section, a non-negligible share of the existing FDP datasets turns out to be project specific.

Second, we code the topic coverage of each dataset based on its questionnaire modules. The metadata of each dataset contains information on survey modules or main topics covered in the questionnaires (e.g., health, education, food insecurity). Since there is no pre-determined list of thematic areas commonly included in the corpus of FDP micro-level datasets that are known to us _ex ante_ , we need to create our own taxonomy of topic areas. To this end, we look at keywords that are frequently mentioned in the descriptions of the survey modules in the metadata, rank-order them based on frequency, and then map them into 14 different broad topic areas. For instance, words such as “consumption”, “income”, “expenditure”, “non-food”, and “welfare” are clustered under the topic area of _consumption and welfare_ and if a given dataset mentions at least one of these keywords in the description of the survey modules in its metadata, the dataset is coded as relevant to that topic area.<sup>19</sup> To assess gaps in topic coverage among FDP datasets, we also apply the same methodology to all other micro-level datasets in the WB MDL and compare differences in topic coverage between FDP datasets as identified in our analysis and other non-FDP datasets contained in the WB MDL.

Third, we also evaluate whether a given dataset contains the core set of questions recommended by EGRISS.<sup>20</sup> EGRISS recommends a set of questions that are essential for proper identification of refugees and IDPs through the International Recommendations on Refugee Statistics (IRRS)<sup>21</sup> and the International Recommendations on Internally Displaced Persons Statistic (IRIS),<sup>22</sup> respectively. For refugees, the identification questions recommended by EGRISS include (EGRISS 2018): a) Country of birth b) Country of citizenship c) Acquisition of citizenship d) Year or period of arrival in the country e) Reason for migration For IDPs, these are (EGRISS 2020): a) Place of birth b) Date of first displacement c) Date of most recent displacement d) Main reason for initial displacement e) Main reason for most recent displacement f) Place of usual residence g) Place of habitual residence We download questionnaires for each dataset from the UNHCR/WB MDLs and review each question in the questionnaires to assess whether they include any of the core questions listed above.

> 19 See Annex C: Taxonomy of  for details on the procedure taken to create a list of topic areas examined in this study. 20 EGRISS is a multi-stakeholder group that was established by the United Nations Statistical Commission (UNSC) in 2016 and now consists of members from 56 national authorities and 36 regional and international organizations.

> 21 The full document of IRRS is available at <u>https://egrisstats.org/recommendations/internationalrecommendations-on-refugee-statistics-irrs/.</u>

> 22 The full document of IRIS is available at <u>https://egrisstats.org/recommendations/international-recommendationson-idp-statistics-iris/.</u>