IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_8386.html
   My bibliography  Save this paper

Clustering Standard Errors at the "Session" Level

Author

Listed:
  • Duk Gyoo Kim

Abstract

Session-specific features of a laboratory experiment, if those exist, do not disappear by clustering standard errors at the session level. Randomly ordering sessions, which is crucial to deal with sampling issues, cannot justify clustering the standard errors at the session level. The experimental design should primarily determine the clustering level. In a typical controlled laboratory experiment where subjects make choices in the same environment repeatedly, clustering at a participant level is inherited from the experimental design, and standard errors could be larger (that is, statistical inference can be more conservative) when clustered at the individual or decision-group level than the session level. It implies that clustering standard errors at the session level can lead to false-positive treatment effects if it is mistakenly chosen. A rule of thumb using standard deviations is introduced.

Suggested Citation

  • Duk Gyoo Kim, 2020. "Clustering Standard Errors at the "Session" Level," CESifo Working Paper Series 8386, CESifo.
  • Handle: RePEc:ces:ceswps:_8386
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp8386.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    2. Matthew Embrey & Guillaume R Fréchette & Sevgi Yuksel, 2018. "Cooperation in the Finitely Repeated Prisoner’s Dilemma," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 509-551.
    3. John Duffy & Dietmar Fehr, 2018. "Equilibrium selection in similar repeated games: experimental evidence on the role of precedents," Experimental Economics, Springer;Economic Science Association, vol. 21(3), pages 573-600, September.
    4. Dirk Engelmann & Guillaume Hollard, 2010. "Reconsidering the Effect of Market Experience on the “Endowment Effect”," Econometrica, Econometric Society, vol. 78(6), pages 2005-2019, November.
    5. Brice Corgnet & Mark Desantis & David Porter, 2018. "What Makes a Good Trader? On the Role of Intuition and Reflection on Trader Performance," Journal of Finance, American Finance Association, vol. 73(3), pages 1113-1137, June.
    6. Alberto Abadie & Susan Athey & Guido W Imbens & Jeffrey M Wooldridge, 2023. "When Should You Adjust Standard Errors for Clustering?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 138(1), pages 1-35.
    7. Carpenter, Jeffrey, 2016. "The labor supply of fixed-wage workers: Estimates from a real effort experiment," European Economic Review, Elsevier, vol. 89(C), pages 85-95.
    8. Rafael Hortala-Vallve & Aniol Llorente-Saguer & Rosemarie Nagel, 2013. "The role of information in different bargaining protocols," Experimental Economics, Springer;Economic Science Association, vol. 16(1), pages 88-113, March.
    9. Andreoni, James & Croson, Rachel, 2008. "Partners versus Strangers: Random Rematching in Public Goods Experiments," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 82, pages 776-783, Elsevier.
    10. Borodin A. D., 2016. "World experience of state influence on the economy," Visnyk of National University of Civil Protection of Ukraine. Public Administration series., National University of Civil Protection of Ukraine, vol. 4(1), pages 37-43, January.
    11. Brice Corgnet & Mark Desantis & David Porter, 2018. "What Makes a Good Trader? On the Role of Reflection and Intuition on Trader Performance," Post-Print hal-02312062, HAL.
    12. Anat Bracha & Uri Gneezy & George Loewenstein, 2015. "Relative Pay and Labor Supply," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 297-315.
    13. Andrea Robbett, 2014. "Local Institutions and the Dynamics of Community Sorting," American Economic Journal: Microeconomics, American Economic Association, vol. 6(3), pages 136-156, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Igor Asanov & Christoph Buehren & Panagiota Zacharodimou, 2020. "The power of experiments: How big is your n?," MAGKS Papers on Economics 202032, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yan Peng & Jason Shachat & Lijia Wei & S. Sarah Zhang, 2024. "Speed traps: algorithmic trader performance under alternative market balances and structures," Experimental Economics, Springer;Economic Science Association, vol. 27(2), pages 325-350, April.
    2. Luis Alvarez & Bruno Ferman, 2020. "Inference in Difference-in-Differences with Few Treated Units and Spatial Correlation," Papers 2006.16997, arXiv.org, revised Apr 2023.
    3. Carpenter, Christopher S. & Gonzales, Gilbert & McKay, Tara & Sansone, Dario, 2020. "Effects of the Affordable Care Act Dependent Coverage Mandate on Health Insurance Coverage for Individuals in Same-Sex Couples," IZA Discussion Papers 13119, Institute of Labor Economics (IZA).
    4. Corgnet, Brice & Hernán-González, Roberto & Kujal, Praveen, 2020. "On booms that never bust: Ambiguity in experimental asset markets with bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    5. Hamelin, Nicolas & Bonelli, Marco I., 2022. "Traders’ anticipatory feelings and traders’ profitability: An exploratory study," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    6. Sönke Hendrik Matthewes, 2020. "Better together? Heterogeneous effects of tracking on student achievement," CEP Discussion Papers dp1706.pdf, Centre for Economic Performance, LSE.
    7. Marco Angrisani & Marco Cipriani & Antonio Guarino, 2022. "Strategic Sophistication and Trading Profits: An Experiment with Professional Traders," Staff Reports 1044, Federal Reserve Bank of New York.
    8. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    9. Araujo, Aloisio & Ferreira, Rafael & Lagaras, Spyridon & Moraes, Flavio & Ponticelli, Jacopo & Tsoutsoura, Margarita, 2023. "The labor effects of judicial bias in bankruptcy," Journal of Financial Economics, Elsevier, vol. 150(2).
    10. João Pereira dos Santos & José Tavares & José Mesquita, 2021. "Leave them kids alone! National exams as a political tool," Public Choice, Springer, vol. 189(3), pages 405-426, December.
    11. Brice Corgnet & Mark DeSantis & Christoph Siemroth, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Working Papers 2313, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    12. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    13. Roller, Marcus & Steinberg, Daniel, 2020. "The distributional effects of early school stratification - non-parametric evidence from Germany," European Economic Review, Elsevier, vol. 125(C).
    14. Christopher S. Sutherland, 2020. "Forward Guidance and Expectation Formation: A Narrative Approach," Staff Working Papers 20-40, Bank of Canada.
    15. Bicchieri, Cristina & Dimant, Eugen & Xiao, Erte, 2021. "Deviant or wrong? The effects of norm information on the efficacy of punishment," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 209-235.
    16. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.
    17. Bogliacino, Francesco & Grimalda, Gianluca & Pipke, David, 2021. "Kind or contented? An investigation of the gift exchange hypothesis in a natural field experiment in Colombia," OSF Preprints xmjaq, Center for Open Science.
    18. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    19. Doremus, Jacqueline, 2019. "Unintended impacts from forest certification: Evidence from indigenous Aka households in Congo," Ecological Economics, Elsevier, vol. 166(C), pages 1-1.
    20. Duffy, John & Rabanal, Jean Paul & Rud, Olga A., 2023. "Market reactions to stock splits: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 325-345.

    More about this item

    Keywords

    lab experiment; cluster-adjusted standard errors;

    JEL classification:

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_8386. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.