ACHIEVING SUSTAINABILITY VIA OFFICIAL STATISTICS: INSIGHTS FROM LITERATURE AND BIBLIOMETRIC APPROACHES - William Ben Gunawan (RAGAM: Journal of Statistics & Its Application, 2026)
In the pursuit of sustainable development, data-driven decision-making is essential. This study explores the pivotal roles that official statistics, systematically produced by national statistical offices and related agencies, play in advancing sustainability agendas. While extensive research has examined big data and sustainability metrics, the specific contributions of official statistics remain underexplored. To bridge this gap, the study employs a mixed-methods approach combining bibliometric analysis and a structured literature review. A total of 865 Scopus-indexed documents were analyzed to map the intellectual landscape, disciplinary scopes, and thematic clusters associated with the intersection of official statistics and sustainability. The results reveal a growing scholarly interest, with a dominant presence in decision sciences, social sciences, economics, and business fields, and emerging contributions in engineering, environmental sciences, and medicine. Official statistics are found to support sustainability by enabling evidence-based governance, monitoring progress toward the Sustainable Development Goals (SDGs), and fostering accountability and transparency. Thematic cluster analysis further highlights the roles of official statistics in policy modeling, health surveillance, environmental monitoring, and socio-economic planning. However, gaps in disciplinary engagement and geographical representation signal the need for greater integration and capacity-building, particularly in data-intensive scientific domains. This study underscores the strategic value of official statistics as a public good, and recommends strengthening statistical systems, fostering interdisciplinary collaboration, and enhancing data accessibility. These actions are vital to align national and global sustainability efforts with reliable, standardized, and inclusive statistical evidence.