2

# 1. Introduction

The current era is marked by the highest number of forcibly displaced people (FDP) in history. As a result of the war in Ukraine coupled with ongoing conflict and disaster in countries such as Afghanistan, Ethiopia, Somalia, the Syrian Arab Republic, the República Bolivariana de Venezuela, and the Republic of Yemen, the number of people forced to flee due to fears of persecution, conflict, violence, human rights violations, and other events seriously disturbing public order had reached more than 110 million.<sup>2</sup> Understanding the extent and nature of the challenges they face is crucial for developing effective policy responses to address their needs and support their successful integration into their host communities or return to their places of origin or previous residence. However, existing data gaps on FDP make it challenging to design and implement such responses.

The aim of this paper lies in understanding existing gaps in microdata on FDP – refugees and internally displaced persons (IDPs). This paper does this by undertaking a review of all existing micro-level datasets in the UNHCR Microdata Library (MDL)<sup>3</sup> and World Bank (WB)<sup>4</sup> MDL from 53 low-income and middleincome countries with a significant presence of FDP.<sup>5</sup> The microdata in these databases are documented in compliance with international standards and practices. They contain a rich source of information on various attributes of datasets, including the country and dates of data collection, sampling strategy, survey modules, and other related aspects. While submission of datasets to the libraries is voluntary and thus does not guarantee an exhaustive list of all publicly available existing datasets on FDP, they are considered to be among the largest databases of microdata concerning development and forced displacement (Thompson 2010; EGRISS 2023).

For the purpose of this study, microdata are defined as primary data collected from household surveys. Our focus lies in identifying micro-level datasets that are publicly available and designed to have a representative sample<sup>6</sup> of FDP so that collected data can be disaggregated for refugees and/or IDPs specifically. By studying the geographical and thematic coverage of existing FDP microdata, we seek to also shed light on critical data gaps that remain to be filled with further data collection efforts.

The paper identifies critical gaps in geographical and thematic coverage as well as compliance with international recommendations for proper identification of displacement status. The paper highlights that microdata is comparatively rich in Sub-Saharan Africa in contrast to other regions. However, data scarcity is notably pronounced in countries facing fragility and conflict and also among IDPs. There are also certain topics that are relatively lacking in the FDP microdata. These include topics like labor, finance (e.g., credit, debt, banking), agriculture/livestock/fishery, and education whereas FDP datasets are relatively rich in health, food insecurity, and water and sanitation in addition to coping strategies and protection. Furthermore, a large majority of questionnaires for these existing micro-level datasets do not include a core set of questions needed for proper identification of displacement status. This calls for further efforts

> 2 See https://www.unhcr.org/news/stories/unhcr-s-grandi-110-million-displaced-indictment-our-world.

> 3 The UNHCR MDL is available at https://microdata.unhcr.org/index.php/about.

> 4 The WB MDL is available at https://microdata.worldbank.org/index.php/about.

> 5 We focus on low-income and middle-income countries because they account for roughly 95 percent of FDP (refugees + IDPs) in the world based on data from UNHCR Refugee Finder and IDMC.

> 6 A representative sample means that when analyzed, the observed characteristics of the sample reflect the true characteristics in the target population that is being researched (Baal and Ronkainen, 2017).