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Inference in economic experiments

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  • Hirschauer, Norbert
  • Grüner, Sven
  • Mußhoff, Oliver
  • Becker, Claudia

Abstract

Replication crisis and debates about p-values have raised doubts about what we can statistically infer from research findings, both in experimental and observational studies. With a view to the present debate on inferential errors, this paper systematizes and discusses experimental designs with regard to the inferences that can and - perhaps more important - that cannot be made from particular designs.

Suggested Citation

  • Hirschauer, Norbert & Grüner, Sven & Mußhoff, Oliver & Becker, Claudia, 2019. "Inference in economic experiments," Economics Discussion Papers 2019-65, Kiel Institute for the World Economy (IfW Kiel).
    • Handle: RePEc:zbw:ifwedp:201965
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    References listed on IDEAS

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    1. Charness, Gary & Gneezy, Uri & Kuhn, Michael A., 2012. "Experimental methods: Between-subject and within-subject design," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 1-8.
    2. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    3. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    4. Blakeley B. McShane & David Gal & Andrew Gelman & Christian Robert & Jennifer L. Tackett, 2019. "Abandon Statistical Significance," The American Statistician, Taylor & Francis Journals, vol. 73(S1), pages 235-245, March.
    5. Dunning,Thad, 2012. "Natural Experiments in the Social Sciences," Cambridge Books, Cambridge University Press, number 9781107017665, November.
    6. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70(2), pages 111-111.
    7. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    8. Ronald L. Wasserstein & Nicole A. Lazar, 2016. "The ASA's Statement on p -Values: Context, Process, and Purpose," The American Statistician, Taylor & Francis Journals, vol. 70(2), pages 129-133, May.
    9. Jonathan de Quidt & Johannes Haushofer & Christopher Roth, 2018. "Measuring and Bounding Experimenter Demand," American Economic Review, American Economic Association, vol. 108(11), pages 3266-3302, November.
    10. Smith, Vernon L, 1982. "Microeconomic Systems as an Experimental Science," American Economic Review, American Economic Association, vol. 72(5), pages 923-955, December.
    11. Hirschauer Norbert & Grüner Sven & Mußhoff Oliver & Becker Claudia, 2019. "Twenty Steps Towards an Adequate Inferential Interpretation of p-Values in Econometrics," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(4), pages 703-721, August.
    12. Dunning,Thad, 2012. "Natural Experiments in the Social Sciences," Cambridge Books, Cambridge University Press, number 9781107698000, November.
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    Cited by:

    1. Hirschauer, Norbert & Grüner, Sven & Mußhoff, Oliver & Becker, Claudia & Jantsch, Antje, 2020. "Can p-values be meaningfully interpreted without random sampling?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 14, pages 71-91.
    2. Hirschauer, Norbert & Grüner , Sven, 2021. "A Primer on p-Value Thresholds and α-Levels – Two Different Kettles of Fish," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 70(02), January.

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    More about this item

    Keywords

    economic experiments; ceteris paribus; confounders; control; inference; Internal/external validity; randomization; random sampling; superpopulation;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General

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