Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico

Modern availability of rich geospatial datasets and analysis tools can provide insight germane to the design of field experiments. Design of field experiments, and in particular the choice of sampling strategy, requires careful consideration of its consequences on the external representativity and i...

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Main Authors:	Noriega, Alejandro, Pentland, Alex
Format:	Journal Article
Published:	Published by Oxford University Press on behalf of the World Bank 2021
Subjects:	CASH TRANSFERS RANDOMIZED CONTROL TRIAL NETWORKED INTERFERENCE SUTVA VIOLATIONS SPATIAL ANALYSIS BIG DATA PRENATAL HEALTH
Online Access:	http://hdl.handle.net/10986/36144

id	okr-10986-36144
recordtype	oai_dc
spelling	okr-10986-361442021-08-18T05:10:28Z Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico Noriega, Alejandro Pentland, Alex CASH TRANSFERS RANDOMIZED CONTROL TRIAL NETWORKED INTERFERENCE SUTVA VIOLATIONS SPATIAL ANALYSIS BIG DATA PRENATAL HEALTH Modern availability of rich geospatial datasets and analysis tools can provide insight germane to the design of field experiments. Design of field experiments, and in particular the choice of sampling strategy, requires careful consideration of its consequences on the external representativity and interference (SUTVA violations) of the experimental sample. This paper presents a methodology for a) modeling the geospatial and social interaction factors that drive interference in rural field experiments; and b) eliciting a set of nondominated sample options that approximate the Pareto-optimal tradeoff between interference and external representativity, as functions of sample choice. The study develops and tests the methodology in the context of a large-scale health experiment in rural Mexico, involving more than 3,000 pregnant women and 600 health clinics across 5 states. Relevant for the practitioner, the methodology is computationally tractable and can be implemented leveraging open sourced geo-spatial data and software tools. 2021-08-17T14:33:57Z 2021-08-17T14:33:57Z 2020-02 Journal Article World Bank Economic Review 1564-698X http://hdl.handle.net/10986/36144 CC BY-NC-ND 3.0 IGO http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Published by Oxford University Press on behalf of the World Bank Publications & Research Publications & Research :: Journal Article Latin America Mexico
repository_type	Digital Repository
institution_category	Foreign Institution
institution	Digital Repositories
building	World Bank Open Knowledge Repository
collection	World Bank
topic	CASH TRANSFERS RANDOMIZED CONTROL TRIAL NETWORKED INTERFERENCE SUTVA VIOLATIONS SPATIAL ANALYSIS BIG DATA PRENATAL HEALTH
spellingShingle	CASH TRANSFERS RANDOMIZED CONTROL TRIAL NETWORKED INTERFERENCE SUTVA VIOLATIONS SPATIAL ANALYSIS BIG DATA PRENATAL HEALTH Noriega, Alejandro Pentland, Alex Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
geographic_facet	Latin America Mexico
description	Modern availability of rich geospatial datasets and analysis tools can provide insight germane to the design of field experiments. Design of field experiments, and in particular the choice of sampling strategy, requires careful consideration of its consequences on the external representativity and interference (SUTVA violations) of the experimental sample. This paper presents a methodology for a) modeling the geospatial and social interaction factors that drive interference in rural field experiments; and b) eliciting a set of nondominated sample options that approximate the Pareto-optimal tradeoff between interference and external representativity, as functions of sample choice. The study develops and tests the methodology in the context of a large-scale health experiment in rural Mexico, involving more than 3,000 pregnant women and 600 health clinics across 5 states. Relevant for the practitioner, the methodology is computationally tractable and can be implemented leveraging open sourced geo-spatial data and software tools.
format	Journal Article
author	Noriega, Alejandro Pentland, Alex
author_facet	Noriega, Alejandro Pentland, Alex
author_sort	Noriega, Alejandro
title	Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
title_short	Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
title_full	Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
title_fullStr	Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
title_full_unstemmed	Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico
title_sort	representativity and networked interference in data-rich field experiments : a large-scale rct in rural mexico
publisher	Published by Oxford University Press on behalf of the World Bank
publishDate	2021
url	http://hdl.handle.net/10986/36144
_version_	1764484596248870912

Representativity and Networked Interference in Data-Rich Field Experiments : A Large-Scale RCT in Rural Mexico

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