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So you want to run an experiment, now what? Some Simple Rules of Thumb for Optimal Experimental Design

  • John A. List
  • Sally Sadoff
  • Mathis Wagner

Experimental economics represents a strong growth industry. In the past several decades the method has expanded beyond intellectual curiosity, now meriting consideration alongside the other more traditional empirical approaches used in economics. Accompanying this growth is an influx of new experimenters who are in need of straightforward direction to make their designs more powerful. This study provides several simple rules of thumb that researchers can apply to improve the efficiency of their experimental designs. We buttress these points by including empirical examples from the literature.

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File URL: http://www.nber.org/papers/w15701.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15701.

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Date of creation: Jan 2010
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Publication status: published as John List & Sally Sadoff & Mathis Wagner, 2011. "So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design," Experimental Economics, Springer, vol. 14(4), pages 439-457, November.
Handle: RePEc:nbr:nberwo:15701
Note: EEE LS PE
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  1. David Reiley & John List, 2008. "Field experiments," Artefactual Field Experiments 00091, The Field Experiments Website.
  2. Dean Karlan & John A. List, 2006. "Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment," Working Papers 1, The Field Experiments Website.
  3. Elisabet Rutstrom & Glenn Harrison & Morten Lau, 2005. "Risk attitudes, randomization to treatment, and self-selection into experiments," Artefactual Field Experiments 00061, The Field Experiments Website.
  4. Lenth R. V., 2001. "Some Practical Guidelines for Effective Sample Size Determination," The American Statistician, American Statistical Association, vol. 55, pages 187-193, August.
  5. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
  6. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 969, Economic Growth Center, Yale University.
  7. El-Gamal, Mahmoud A & Palfrey, Thomas R, 1996. "Economical Experiments: Bayesian Efficient Experimental Design," International Journal of Game Theory, Springer, vol. 25(4), pages 495-517.
  8. List John A., 2007. "Field Experiments: A Bridge between Lab and Naturally Occurring Data," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(2), pages 1-47, April.
  9. John A. List, 2001. "Do Explicit Warnings Eliminate the Hypothetical Bias in Elicitation Procedures? Evidence from Field Auctions for Sportscards," American Economic Review, American Economic Association, vol. 91(5), pages 1498-1507, December.
  10. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2011. "Adaptive Experimental Design Using the Propensity Score," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 96-108, January.
  11. repec:feb:artefa:0090 is not listed on IDEAS
  12. John List & Steven Levitt, 2009. "Field experiments in economics: The past, the present, and the future," Artefactual Field Experiments 00079, The Field Experiments Website.
  13. Rutström, E. Elisabet & Wilcox, Nathaniel T., 2009. "Stated beliefs versus inferred beliefs: A methodological inquiry and experimental test," Games and Economic Behavior, Elsevier, vol. 67(2), pages 616-632, November.
  14. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
  15. Camerer, Colin F. & Hogarth, Robin M., 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Working Papers 1059, California Institute of Technology, Division of the Humanities and Social Sciences.
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