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Experimentation at Scale

Bibliographic Data

ID4029819
AuthorsKarthik Muralidharan (0000-0001-8135-6225, Karthik Muralidharan, Associate Professor of Economics, University of California at San Diego, La Jolla, California. Research Associate, National Bureau of Economic Research, Cambridge, Massachusetts. Affiliated Professor with the Abdul Latif Jameel Poverty Action Lab, Cambridge, Massachusetts.), Paul Niehaus (0000-0001-5119-8270, Paul Niehaus, Associate Professor of Economics, University of California at San Diego, La Jolla, California. Research Associate, National Bureau of Economic Research, Cambridge, Massachusetts. Affiliated Professor with the Abdul Latif Jameel Poverty Action Lab, Cambridge, Massachusetts.)
Year2017
Volume31
Issue4
Pages103-124
Publication date2017-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Journal of Economic Perspectives (JOURNAL)
Journal identifiersISSN: 0895-3309 • E-ISSN: 1944-7965
PublisherAmerican Economic Association (PUBLISHER • US)
DOI10.1257/jep.31.4.103
OpenAlexW2766046948
LanguageEN
Citations received44
References cited24

This paper makes the case for greater use of randomized experiments "at scale." We review various critiques of experimental program evaluation in developing countries, and discuss how experimenting at scale along three specific dimensions-the size of the sampling frame, the number of units treated, and the size of the unit of randomization- can help alleviate the concerns raised. We find that program-evaluation randomized controlled trials published over the last 15 years have typically been "small" in these senses, but also identify a number of examples-including from our own work- demonstrating that experimentation at much larger scales is both feasible and valuable

Cartography · Data science · Econometrics · Geography · Industrial engineering · Mathematics education · Population · Randomization · Randomized controlled trial · Randomized experiment · Sampling frame · Sociology · Statistics · Advanced Causal Inference Techniques · Computer Science · Engineering · Income, Poverty, and Inequality · Mathematics · Medicine · Poverty, Education, and Child Welfare · Psychology

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Unique citing works44
Citations per year5.5
Citation span2018 - 2026 (9)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 43

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