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arXiv Machine Learning By Adrienne C. Kinney, Anya Workman, Ademar Takeo Akabane, Jenna Barac, Paulo Fernando Braga Carvalho, Jeova Farias, Fernando Nascimento, Paulo Ricardo da Silva Oliveira

Crowd-Sourced Geographies of Income: Using Google Maps Points of Interest as High-Frequency Proxies for Sub-Municipal Income Estimation in Sao Paulo, Brazil

Read the original on arXiv Machine Learning →

arXiv:2608. 07871v1 Announce Type: cross Abstract: Accurate, up-to-date income data at the sub-municipal scale is essential for social policy in middle-income countries, yet in Brazil it depends on a costly decennial census whose intercensal gap recently exceeded a decade.

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