10 While countries hosting a greater number of FDP tend to have a greater number of publicly available FDP datasets, some countries defy this overall pattern – having no FDP dataset despite a relatively large size of FDP they host. Figure 3 Panel A plots the relationship between the size of FDP (or the total of refugees, Venezuelan refugees and migrants, and IDPs combined) and the number of publicly available FDP datasets.<sup>27</sup> The upward slope seen in the plot indicates that overall there is a positive correlation between the number of FDP and the number of publicly available FDP datasets. Bangladesh, Cameroon, Kenya, Lebanon and Uganda top the list in terms of the number of publicly available FDP datasets. It is worth highlighting that there are a number of countries that, despite having a sizable number of refugees or IDPs, have no FDP dataset identified through this analysis. Notable cases include the Syrian Arab Republic, Türkiye, Yemen, Pakistan, and China where the number of FDP exceeds 1 million, but no publicly available FDP dataset is found in the MDLs.

FDP data is also relatively lacking among countries in fragile and conflict-affected situations (FCS). Indeed, the level of conflict intensity is negatively correlated with the number of publicly available FDP datasets, meaning that the more fragile and violent a country, the fewer datasets it has available in the MDLs. This pattern is certainly not unique to FDP microdata. For instance, comparable poverty measures over time are often lacking in FCS countries (World Bank 2021).

A confluence of factors explains data deprivation in FCS countries. To inform discussions about policy responses towards FDP in a given country, the surveys must be representative at least for the target population of interest to policy makers. However, a reliable sampling frame is often missing in such conflict situations where population census rarely takes place, and registration data may also be obsolete, thereby complicating the implementation of sample household survey (Aguilera et al. 2020). Furthermore, collecting data in the fragile context also raises a concern for the safety of enumerators, inhibiting survey implementation in the unsafe regions (Corral et al. 2020). Furthermore, FCS countries also suffer from limited statistical capacity and a lack of resources to implement data collection (Cas et al. 2022).

In terms of the regional representation of publicly available FDP datasets, data is relatively rich in SubSaharan Africa in contrast to other regions.<sup>28</sup> In fact, Sub-Saharan Africa accounts for 53 percent of all FDP micro-level datasets (excluding project-specific datasets and those datasets collected before 2010). These patterns hold even after accounting for the above-mentioned baseline country characteristics such as GDP per capita, conflict intensity, and number of FDP (see Figure 3 Panel B). The average marginal effects of regional dummies are all negative and significant (except for South Asia) using Sub-Saharan Africa as a benchmark.

Data is particularly rich in East Africa. This skew is primarily driven by three countries that have a higher number of datasets than expected given the number of FDPs they host: Uganda, Kenya, and Tanzania. This pattern is reflective of a broader data and evidence landscape in Africa. Indeed, these three countries are also among the top in the region with the largest number of general micro-level datasets in the WB MDL. Additionally, Kenya and Uganda are among the most extensively studied countries in impact 27 For this country-level analysis, we exclude those micro-level datasets that are collected prior to 2010 or projectspecific datasets. Furthermore, some survey datasets are stored as separate entries in the WB and UNHCR MDL even though they are indeed part of the same survey (e.g., entries by camp or by wave). Those independent entries are collapsed as one when they are part of the same survey.

> 28 Throughout this paper, we adopt the regional classification of the World Bank:

<u>https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups.</u>