Metadata

A Theory of Experimenters: Robustness, Randomization, and Balance

Version
1
Resource Type
Dataset
Creator
  • Chassang, Sylvain (NYU)
  • Banerjee, Abhijit (MIT)
  • Snowberg, Erik (UBC)
  • Montero, Sergio (University of Rochester)
Publication Date
2019-11-08
Funding Reference
  • NSF
    • Award Number: SES-1156154
Free Keywords
experiment design; balance; rerandomization
Description

  • 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.

Availability
Download
Relations
  • Is supplement to
    DOI: 10.1257/aer.20171634 (Text)
  • Is cited by
    URL: https://github.com/sylvaingchassang/rct (Text)
  • Is previous version of
    DOI: 10.3886/E115410V2
Publications
  • 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)
  • 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