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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

    ()

    (University of Chicago and NBER)

  • Sally Sadoff

    (University of Chicago)

  • Mathis Wagner

    ()

    (CeRP - Collegio Carlo Alberto, Turin)

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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Paper provided by Center for Research on Pensions and Welfare Policies, Turin (Italy) in its series CeRP Working Papers with number 94.

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Length: 27 pages
Date of creation: Feb 2010
Date of revision:
Handle: RePEc:crp:wpaper:94
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  1. Dean Karlan & John A. List, 2007. "Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment," American Economic Review, American Economic Association, vol. 97(5), pages 1774-1793, December.
  2. Harrison, Glenn W. & Lau, Morten I. & Elisabet Rutström, E., 2009. "Risk attitudes, randomization to treatment, and self-selection into experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 70(3), pages 498-507, June.
  3. 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.
  4. David Reiley & John List, 2008. "Field experiments," Artefactual Field Experiments 00091, The Field Experiments Website.
  5. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 59, Yale University, Department of Economics.
  6. repec:feb:artefa:0090 is not listed on IDEAS
  7. John List, 2006. "Field experiments: A bridge between lab and naturally occurring data," Artefactual Field Experiments 00083, The Field Experiments Website.
  8. Richard Blundell & Monica Costa Dias, 2002. "Alternative approaches to evaluation in empirical microeconomics," CeMMAP working papers CWP10/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  9. Steven D. Levitt & John A. List, 2008. "Field Experiments in Economics: The Past, The Present, and The Future," NBER Working Papers 14356, National Bureau of Economic Research, Inc.
  10. Lenth R. V., 2001. "Some Practical Guidelines for Effective Sample Size Determination," The American Statistician, American Statistical Association, vol. 55, pages 187-193, August.
  11. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 969, Economic Growth Center, Yale University.
  12. 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.
  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. 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.
  15. 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.
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