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Aidan Coville

Dados Biográficos

ID6447028
NOMEAidan Coville
PRENOMESAidan
SOBRENOMECoville
ASSINATURACOVILLE A
AFILIAÇÕESWorld Bank
ORCID0000-0002-3437-6239
VERIFICADOSim
TOTAL DE OBRAS6
TOTAL DE CITAÇÕES8
TOTAL COMO AUTOR6
TOTAL COMO EDITOR0
PRIMEIRO ANO DE PUBLICAÇÃO2021
ANO MAIS RECENTE DE PUBLICAÇÃO2025
ÍNDICE H2
  • Financing Municipal Water and Sanitation Services in Nairobi’s Informal Settlements

    Aidan Coville, Sebastián Galiani et al.•ARTICLE•The Review of Economics and…•2025

    We test two ways to improve revenue collection efficiency for water and sanitation utilities: (i) face-to-face engagement between utility staff and customers and (ii) contract enforcement for service disconnection due to nonpayment in the form of transparent and credible disconnection notices. Engagement has no effect, while enforcement significantly increases payment. We find no effect on access to water, perceptions of the utility, relationship…

  • Quality signaling and demand for renewable energy technology

    Open Access•Aidan Coville, Joshua Graff Zivin et al.•ARTICLE•Journal of Development Economics•2025•Referências: 11

    Solar technologies have been associated with private and social returns, but their technological potential often remains unachieved because of persistently low demand for high-quality products. In a randomized field experiment in Senegal, we assess the potential of three types of quality signaling to increase demand for high-quality solar lamps. We find no effect on demand when consumers are offered a money-back guarantee but increased demand wit…

  • Local knowledge, formal evidence, and policy decisions

    Open Access•Eva Vivalt, Aidan Coville et al.•ARTICLE•Journal of Development Economics•2024•Citada por: 1•Referências: 1

    How do policymakers value advice from local experts versus formal evidence from impact evaluations when making policy decisions? Using a discrete choice experiment conducted in collaboration with the World Bank and Inter-American Development Bank, we show that policymakers were willing to accept a program that had a 5.0 percentage point smaller estimated effect on enrollment rates if it were recommended by a local expert. They also preferred prog…

  • How do policymakers update their beliefs

    Open Access•Eva Vivalt, Aidan Coville•ARTICLE•Journal of Development Economics•2023•Citada por: 4•Referências: 1

  • 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…

  • Effects of a community-driven water, sanitation and hygiene intervention on water and sanitation infrastructure, access, behaviour, and governance

    Open Access•John Quattrochi, Aidan Coville et al.•ARTICLE•BMJ Global Health•2021

    INTRODUCTION: (VEA), with support from UNICEF, financed by UK's Foreign, Commonwealth and Development Office. METHODS: A cluster-level randomised controlled trial of VEA was implemented throughout 2019 across 332 rural villages, grouped into 50 treatment and 71 control clusters. Primary outcomes included time spent collecting water; quantity of water collected; prevalence of improved primary source of drinking water; and prevalence of improved pr…

  • How do policymakers update their beliefs

    Open Access•Eva Vivalt, Aidan Coville•ARTICLE•Journal of Development Economics•2023•Citada por: 4•Referências: 1

  • 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…

  • Local knowledge, formal evidence, and policy decisions

    Open Access•Eva Vivalt, Aidan Coville et al.•ARTICLE•Journal of Development Economics•2024•Citada por: 1•Referências: 1

    How do policymakers value advice from local experts versus formal evidence from impact evaluations when making policy decisions? Using a discrete choice experiment conducted in collaboration with the World Bank and Inter-American Development Bank, we show that policymakers were willing to accept a program that had a 5.0 percentage point smaller estimated effect on enrollment rates if it were recommended by a local expert. They also preferred prog…

  • Effects of a community-driven water, sanitation and hygiene intervention on water and sanitation infrastructure, access, behaviour, and governance

    Open Access•John Quattrochi, Aidan Coville et al.•ARTICLE•BMJ Global Health•2021

    INTRODUCTION: (VEA), with support from UNICEF, financed by UK's Foreign, Commonwealth and Development Office. METHODS: A cluster-level randomised controlled trial of VEA was implemented throughout 2019 across 332 rural villages, grouped into 50 treatment and 71 control clusters. Primary outcomes included time spent collecting water; quantity of water collected; prevalence of improved primary source of drinking water; and prevalence of improved pr…

  • 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…

  • How do policymakers update their beliefs

    Open Access•Eva Vivalt, Aidan Coville•ARTICLE•Journal of Development Economics•2023•Citada por: 4•Referências: 1

  • Local knowledge, formal evidence, and policy decisions

    Open Access•Eva Vivalt, Aidan Coville et al.•ARTICLE•Journal of Development Economics•2024•Citada por: 1•Referências: 1

    How do policymakers value advice from local experts versus formal evidence from impact evaluations when making policy decisions? Using a discrete choice experiment conducted in collaboration with the World Bank and Inter-American Development Bank, we show that policymakers were willing to accept a program that had a 5.0 percentage point smaller estimated effect on enrollment rates if it were recommended by a local expert. They also preferred prog…

  • Financing Municipal Water and Sanitation Services in Nairobi’s Informal Settlements

    Aidan Coville, Sebastián Galiani et al.•ARTICLE•The Review of Economics and…•2025

    We test two ways to improve revenue collection efficiency for water and sanitation utilities: (i) face-to-face engagement between utility staff and customers and (ii) contract enforcement for service disconnection due to nonpayment in the form of transparent and credible disconnection notices. Engagement has no effect, while enforcement significantly increases payment. We find no effect on access to water, perceptions of the utility, relationship…

  • Quality signaling and demand for renewable energy technology

    Open Access•Aidan Coville, Joshua Graff Zivin et al.•ARTICLE•Journal of Development Economics•2025•Referências: 11

    Solar technologies have been associated with private and social returns, but their technological potential often remains unachieved because of persistently low demand for high-quality products. In a randomized field experiment in Senegal, we assess the potential of three types of quality signaling to increase demand for high-quality solar lamps. We find no effect on demand when consumers are offered a money-back guarantee but increased demand wit…

Economics (4 obras) · Business (3 obras) · Child Nutrition and Water Access (2 obras) · Economic growth (2 obras) · Psychology (2 obras) · Sanitation (2 obras) · Attendance (1 obras) · Cluster randomised controlled trial (1 obras) · Computer Science (1 obras) · Consumption (sociology (1 obras)

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