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Emily L Aiken

Dados Biográficos

ID11017467
NOMEEmily L Aiken
PRENOMESEmily L
SOBRENOMEAiken
ASSINATURAAIKEN E L
VERIFICADONão
TOTAL DE OBRAS1
TOTAL DE CITAÇÕES3
TOTAL COMO AUTOR1
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2022
ANO MAIS RECENTE DE PUBLICAÇÃO2022
ÍNDICE H1
  • Program targeting with machine learning and mobile phone data

    Open Access•Emily Aiken, Emily L Aiken et al.•ARTICLE•Journal of Development Economics•2022•Citada por: 3•Referências: 2

    Can mobile phone data improve program targeting? By combining rich survey data from a “big push” anti-poverty program in Afghanistan with detailed mobile phone logs from program beneficiaries, we study the extent to which machine learning methods can accurately differentiate ultra-poor households eligible for program benefits from ineligible households. We show that machine learning methods leveraging mobile phone data can identify ultra-poor hou…

  • Program targeting with machine learning and mobile phone data

    Open Access•Emily Aiken, Emily L Aiken et al.•ARTICLE•Journal of Development Economics•2022•Citada por: 3•Referências: 2

    Can mobile phone data improve program targeting? By combining rich survey data from a “big push” anti-poverty program in Afghanistan with detailed mobile phone logs from program beneficiaries, we study the extent to which machine learning methods can accurately differentiate ultra-poor households eligible for program benefits from ineligible households. We show that machine learning methods leveraging mobile phone data can identify ultra-poor hou…

  • Program targeting with machine learning and mobile phone data

    Open Access•Emily Aiken, Emily L Aiken et al.•ARTICLE•Journal of Development Economics•2022•Citada por: 3•Referências: 2

    Can mobile phone data improve program targeting? By combining rich survey data from a “big push” anti-poverty program in Afghanistan with detailed mobile phone logs from program beneficiaries, we study the extent to which machine learning methods can accurately differentiate ultra-poor households eligible for program benefits from ineligible households. We show that machine learning methods leveraging mobile phone data can identify ultra-poor hou…

Computer Science (1 obras) · Consumption (sociology (1 obras) · Data science (1 obras) · Economic growth (1 obras) · Economics (1 obras) · GSM services (1 obras) · Human Mobility and Location-Based Analysis (1 obras) · ICT in Developing Communities (1 obras) · Income, Poverty, and Inequality (1 obras) · Internet privacy (1 obras)

Ethnos_APP • Projeto Open Source • Licença MIT • Frontend v2.0.0 • Privacidade e Cookies • Documentação da API: api.ethnos.app/docs • Código da API: GitHub • DOI: 10.5281/zenodo.17049435 • Código do Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae