Decision Theoretic Approaches to Experiment Design and External Validity

48 Pages Posted: 18 Apr 2016

See all articles by Abhijit V. Banerjee

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics

Sylvain Chassang

New York University (NYU) - Department of Economics

Erik Snowberg

California Institute of Technology - Division of the Humanities and Social Sciences; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: April 2016

Abstract

A modern, decision-theoretic framework can help clarify important practical questions of experimental design. Building on our recent work, this chapter begins by summarizing our framework for understanding the goals of experimenters, and applying this to re-randomization. We then use this framework to shed light on questions related to experimental registries, pre-analysis plans, and most importantly, external validity. Our framework implies that even when large samples can be collected, external decision-making remains inherently subjective. We embrace this conclusion, and argue that in order to improve external validity, experimental research needs to create a space for structured speculation.

Suggested Citation

Banerjee, Abhijit V. and Chassang, Sylvain and Snowberg, Erik, Decision Theoretic Approaches to Experiment Design and External Validity (April 2016). NBER Working Paper No. w22167. Available at SSRN: https://ssrn.com/abstract=2766152

Abhijit V. Banerjee (Contact Author)

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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Sylvain Chassang

New York University (NYU) - Department of Economics ( email )

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New York, NY 10012
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Erik Snowberg

California Institute of Technology - Division of the Humanities and Social Sciences ( email )

1200 East California Blvd.
Pasadena, CA 91125
United States

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

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