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A Theory of Experimenters: Robustness, Randomization, and Balance
- Chassang, Sylvain (NYU)
- Banerjee, Abhijit (MIT)
- Snowberg, Erik (UBC)
- Montero, Sergio (University of Rochester)
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NSF
- Award Number: SES-1156154
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Abstract
Readme for simulation/replication code for "A Theory of Experimenters:
Robustness, Randomization, and Balance" by Banerjee, Chassang, Montero
and Snowberg in the American Economic Review
Use Matlab R2019b or later to run simulations.m to produce fig1.csv,
fig2.csv, and fig3.csv.
Use Stata version 15 to run theoryOfExperimentersDrawFigures.do, which
will produce three figures: bayesLoss.eps, N100.eps, and
errorBalance.eps.
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Is supplement to
DOI: 10.1257/aer.20171634 (Text)
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Is cited by
URL: https://github.com/sylvaingchassang/rct (Text)
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Is previous version of
DOI: 10.3886/E115410V2
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Banerjee, Abhijit V., Sylvain Chassang, Sergio Montero, and Erik Snowberg. “A Theory of Experimenters: Robustness, Randomization, and Balance.” American Economic Review 110, no. 4 (April 2020): 1206–30. https://doi.org/10.1257/aer.20171634.
- ID: 10.1257/aer.20171634 (DOI)
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chassang, sylvain. “A Software Implementation of Robust and Balanced Experimental Assignment Schemes,” November 5, 2019. https://github.com/sylvaingchassang/rct.
- ID: https://github.com/sylvaingchassang/rct (URL)
Update Metadata: 2020-05-18 | Issue Number: 3 | Registration Date: 2019-11-09
Chassang, Sylvain; Banerjee, Abhijit; Snowberg, Erik; Montero, Sergio (2019): A Theory of Experimenters: Robustness, Randomization, and Balance. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E115410V1
