Mapping poverty at multiple geographical scales
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866912838789890048 |
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| author | De Nicolò, Silvia Fabrizi, Enrico Gardini, Aldo |
| author_facet | De Nicolò, Silvia Fabrizi, Enrico Gardini, Aldo |
| contents | Poverty mapping is a powerful tool to study the geography of poverty. The choice of the spatial resolution is central as poverty measures defined at a coarser level may mask their heterogeneity at finer levels. We introduce a small area multi-scale approach integrating survey and remote sensing data that leverages information at different spatial resolutions and accounts for hierarchical dependencies, preserving estimates coherence. We map poverty rates by proposing a Bayesian Beta-based model equipped with a new benchmarking algorithm that accounts for the double-bounded support. A simulation study shows the effectiveness of our proposal and an application on Bangladesh is discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_12674 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Mapping poverty at multiple geographical scales De Nicolò, Silvia Fabrizi, Enrico Gardini, Aldo Methodology Applications Poverty mapping is a powerful tool to study the geography of poverty. The choice of the spatial resolution is central as poverty measures defined at a coarser level may mask their heterogeneity at finer levels. We introduce a small area multi-scale approach integrating survey and remote sensing data that leverages information at different spatial resolutions and accounts for hierarchical dependencies, preserving estimates coherence. We map poverty rates by proposing a Bayesian Beta-based model equipped with a new benchmarking algorithm that accounts for the double-bounded support. A simulation study shows the effectiveness of our proposal and an application on Bangladesh is discussed. |
| title | Mapping poverty at multiple geographical scales |
| topic | Methodology Applications |
| url | https://arxiv.org/abs/2306.12674 |