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So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design

  • John List
  • Mathis Wagner
  • Sally Sadoff

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 The Field Experiments Website in its series Artefactual Field Experiments with number 00094.

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Date of creation: 2010
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Handle: RePEc:feb:artefa:00094
Contact details of provider: Web page: http://www.fieldexperiments.com

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  1. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 969, Economic Growth Center, Yale University.
  2. Glenn Harrison & John List, 2004. "Field experiments," Artefactual Field Experiments 00058, The Field Experiments Website.
  3. Lenth R. V., 2001. "Some Practical Guidelines for Effective Sample Size Determination," The American Statistician, American Statistical Association, vol. 55, pages 187-193, August.
  4. 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.
  5. Karlan, Dean & List, John, 2006. "Does Price Matter in Charitable Giving? Evidence from a Large-Scale Natural Field Experiment," Working Papers 13, Yale University, Department of Economics.
  6. 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.
  7. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean, 2011. "Adaptive Experimental Design Using the Propensity Score," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 96-108.
  8. repec:feb:artefa:0090 is not listed on IDEAS
  9. Levitt, Steven D. & List, John A., 2009. "Field experiments in economics: The past, the present, and the future," European Economic Review, Elsevier, vol. 53(1), pages 1-18, January.
  10. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
  11. John List, 2006. "Field experiments: A bridge between lab and naturally occurring data," Artefactual Field Experiments 00083, The Field Experiments Website.
  12. 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.
  13. John List, 2001. "Do explicit warnings eliminate the hypothetical bias in elicitation procedures? Evidence from field auctions for sportscards," Framed Field Experiments 00163, The Field Experiments Website.
  14. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
  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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