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

  • John 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://hdl.handle.net/10.1007/s10683-011-9275-7
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Article provided by Springer in its journal Experimental Economics.

Volume (Year): 14 (2011)
Issue (Month): 4 (November)
Pages: 439-457

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Handle: RePEc:kap:expeco:v:14:y:2011:i:4:p:439-457
Contact details of provider: Web page: http://www.springerlink.com/link.asp?id=102888

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  1. 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.
  2. 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.
  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. 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.
  5. Dean Karlan & John A. List, 2006. "Does Price Matter in Charitable Giving? Evidence From a Large-Scale Natural Field Experiment," NBER Working Papers 12338, National Bureau of Economic Research, Inc.
  6. 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.
  7. Richard Blundell & Monica Costa Dias, 2008. "Alternative approaches to evaluation in empirical microeconomics," CeMMAP working papers CWP26/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
  9. 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.
  10. 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.
  11. repec:feb:artefa:0090 is not listed on IDEAS
  12. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 969, Economic Growth Center, Yale University.
  13. John A. List, 2007. "Field Experiments: A Bridge Between Lab and Naturally-Occurring Data," NBER Working Papers 12992, National Bureau of Economic Research, Inc.
  14. 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.
  15. 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.
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