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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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File URL: http://www.cerp.carloalberto.org/wp-content/uploads/2010/02/wp_94.pdf?f6fa34
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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. 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.
  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. 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.
  4. 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.
  5. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2009. "Adaptive Experimental Design Using the Propensity Score," Working Papers 969, Economic Growth Center, Yale University.
  6. Lenth R. V., 2001. "Some Practical Guidelines for Effective Sample Size Determination," The American Statistician, American Statistical Association, vol. 55, pages 187-193, August.
  7. 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.
  8. Steven Levitt & John List, 2008. "Field experiments in economics: The past, the present, and the future," Artefactual Field Experiments 00079, The Field Experiments Website.
  9. El-Gamal, Mahmoud A. & Palfrey, Thomas R., 1994. "Economical Experiments: Bayesian Efficient Experimental Design," Working Papers 884, California Institute of Technology, Division of the Humanities and Social Sciences.
  10. 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.
  11. Glenn Harrison & John List, 2004. "Field experiments," Artefactual Field Experiments 00058, The Field Experiments Website.
  12. 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.
  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. repec:feb:artefa:0090 is not listed on IDEAS
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