The uneven reach of the state: A novel approach to mapping local state presence

• 成果类型: Article
• 署名作者: Agneman, Gustav; Cappelen, Christoffer; Brandt, Kasper; Sjoeberg, David
• 署名单位: Norwegian University of Science & Technology (NTNU); University of Copenhagen
• 刊物名称: JOURNAL OF DEVELOPMENT ECONOMICS
• ISSN/ISSBN: 0304-3878
• DOI: 10.1016/j.jdeveco.2025.103453
• 发表日期: 2025
• 关键词: State presence; Machine Learning; CONFLICT

摘要

The ability of states to exercise authority often varies considerably within their borders, yet we lack reliable empirical measures of the uneven reach of states. In this paper, we develop a methodology to predict state presence at granular spatial resolutions and demonstrate the approach using data from Sub-Saharan Africa. We link a range of indicators of state presence, e.g., infrastructural data, with geolocated survey data of residents' experiences with subnational governance. Then, we employ a machine learning algorithm that learns how the input variables relate to experienced state presence and extrapolates the predictions to all of Sub-Saharan Africa. We validate the predicted measure through a range of tests and document how local state presence influences development outcomes.