11 Lack of comprehensive population data Globally, a key issue hindering progress towards ending statelessness is the lack of comprehensive, disaggregated population data. Reliable data is essential to understanding the scale and impact of statelessness, identifying affected individuals, and designing appropriate legal and policy responses.11 In the Western Balkans (as in other parts of the world), data systems frequently fall short of these objectives, and data on statelessness and populations at risk is incomplete or unreliable. While all censuses in the region have included specific questions on citizenship status, there are concerns about the accuracy of census data when it comes to statelessness. A consistent challenge is the significant underreporting of stateless populations in census data compared to data from other sources, including UNHCR estimates in some cases, as well as civil society mapping exercises, casework data, and community-based identification activities.12 The reasons for this include census data collection methodologies that rely heavily on self-identification, a lack of guidance and training on citizenship status and statelessness for census operators, and marginalisation, exclusion, and distrust which all hinder participation in the census. Many impacted individuals do not understand their citizenship status or may unknowingly identify with a citizenship they do not actually possess. Moreover, sometimes ambiguous data categories are used, such as ‘unknown citizenship’ with little guidance on how to apply these.13 Individuals without civil documentation or residence status may be excluded from Beneficiary-led census exercises or, where included, a lack of trust in central authorities or fear of discrimination may reduce participation in official data collection exercises. A related concern is the lack of disaggregation in existing data sets. While in some Beneficiaries, official data is disaggregated by sex or gender, age, and place of residence, most do not capture key risk indicators such as documentation or residence status and similarly do not disaggregate for factors such as ethnicity, which may be highly relevant when designing targeted policy interventions. In rare instances where disaggregation has included ethnicity, the results have been contested by those working directly with affected communities. Compounding these shortcomings is the persistent underreporting of the Roma population more generally across the region. Roma-led and other civil society organisations have repeatedly challenged official census figures, highlighting widespread underreporting due to various factors.14 This underreporting not only has the indirect effect of obscuring the true scale of statelessness, which disproportionately impacts on Roma communities, but also perpetuate cycles of exclusion, as without this accurate data, policymakers lack the necessary evidence to identify challenges and design and prioritise interventions. To fill these information gaps, civil society organisations and international agencies have frequently engaged in community-based mapping, outreach, and individual case identification. Such exercises are invaluable for informing policy responses, as well as identifying individuals in need of legal assistance or support to resolve their documentation and citizenship status. However, without support from public authorities and sustained resourcing, these crucial mapping and outreach activities are at risk. Efforts to monitor or map statelessness, supported by public authorities, have been carried out in the past. However, in recent years, no new initiatives have been undertaken to accurately identify and survey remaining cases.15 There is an urgent need for public authorities to commit to and invest in better population data. This is 11 UNHCR, Global Action Plan to End Statelessness 2.0, 2024, Action 10: Improve quantitative and qualitative data on stateless populations, at: https://www.refworld.org/policy/strategy/unhcr/2024/en/148761. 12 For examples of UNHCR estimates on stateless population data by Beneficiary, see UNHCR Refugee Data Finder, at: https://www.unhcr. org/refugee-statistics/download. 13 States should use standardised definition of statelessness and consistent indicators for collecting statelessness data. See International Recommendations on Statelessness Statistics (IROSS), endorsed by UN Statistical Commission in 2023, at: https://egrisstats.org/recommendations/international-recommendations-on-statelessness-statistics-iross/. 14 This issue was recognised by the Regional Cooperation Council, Roma Integration 2020 report: Data Collection to Monitor the Declaration of Western Balkans Partners on Roma Integration and EU Enlargement, at: https://www.rcc.int/romaintegration2020/inc/download. php?tip=docs&doc=ANNEX%20V%20-%20Concept%20Note%20Data%20Collection%20exercize%20to%20monitor%20the%20Poznan%20 De....pdf&doc_url=052990e2c025341d9437186561831128.pdf. 15 For example, see UNHCR, Mapping of the Population at Risk of Statelessness in Albania, May 2018, jointly conducted by Tirana Legal Aid Society (TLAS), UNHCR, and Albanian ministries, available at: https://www.refworld.org/reference/countryrep/unhcr/2018/en/121478.