Designing Experiments to Measure Spillover Effects

Sarah Baird, Aislinn Bohren, Craig McIntosh () and Berk Özler
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Craig McIntosh: University of California, San Diego

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

Abstract: This paper formalizes the design of experiments intended specifically to study spillover effects. By first randomizing the intensity of treatment within clusters and then randomly assigning individual treatment conditional on this cluster-level intensity, a novel set of treatment effects can be identified. We develop a formal framework for consistent estimation of these effects, and provide explicit expressions for power calculations. We show that the power to detect average treatment effects declines precisely with the quantity that identifies the novel treatment effects. A demonstration of the technique is provided using a cash transfer program in Malawi.

Keywords: Experimental Design; Networks; Cash Transfers (search for similar items in EconPapers)
JEL-codes: C93 I25 O22 (search for similar items in EconPapers)
Pages: 54 pages
Date: 2014-02-07
New Economics Papers: this item is included in nep-ecm and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (53)

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https://economics.sas.upenn.edu/sites/default/files/filevault/14-006.pdf (application/pdf)

Related works:
Working Paper: Designing Experiments to Measure Spillover Effects (2014)
Working Paper: Designing Experiments to Measure Spillover Effects (2014)
Working Paper: Designing experiments to measure spillover effects (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:pen:papers:14-006

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