Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/242322 
Year of Publication: 
2021
Citation: 
[Journal:] Development Engineering [ISSN:] 2352-7285 [Volume:] 6 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2021 [Pages:] 1-17
Publisher: 
Elsevier, Amsterdam
Abstract: 
With recent advances in high-resolution satellite imagery and machine vision algorithms, fine-grain geospatial data on population are now widely available: kilometer-by-kilometer, worldwide. In this paper, we showcase how researchers and policymakers in developing countries can leverage these novel data to precisely identify "education deserts" - localized areas where families lack physical access to education - at unprecedented scale, detail, and cost-effectiveness. We demonstrate how these analyses could valuably inform educational access initiatives like school construction and transportation investments, and outline a variety of analytic extensions to gain deeper insight into the state of school access across a given country. We conduct a proof-of-concept analysis in the context of Guatemala, which has historically struggled with educational access, as a demonstration of the utility, viability, and flexibility of our proposed approach. We find that the vast majority of Guatemalan population lives within 3 km of a public primary school, indicating a generally low incidence of distance as a barrier to education in that context. However, we still identify concentrated pockets of population for whom the distance to school remains prohibitive, revealing important geographic variation within the strong country-wide average. Finally, we show how even a small number of optimally-placed schools in these areas, using a simple algorithm we develop, could substantially reduce the incidence of education deserts in this context. We make our entire codebase available to the public - fully free, open-source, heavily documented, and designed for broad use - allowing analysts across contexts to easily replicate our proposed analyses for other countries, educational levels, and public goods more generally.
Subjects: 
Access to education
Education deserts
Education in developing countries
School placement
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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