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Inducing natural group identity: A RDP analysis

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  • Daniel John Zizzo

    (School of Economics, University of East Anglia)

Abstract

A relevance, distinctiveness and plausibility (RDP) analysis is a conceptual framework that can be used to identify when potential confounds are a problem for interpreting experimental results. We illustrate this analysis using the creation or enhancement of natural group identity by the means of priming manipulations as employed in the experiments of five target papers. Such priming manipulations may lead to experimenter demand effects and may spuriously induce behavior change. Using a RDP analysis, we show how these potential confounds are likely to be problematic for all but one of the target papers.

Suggested Citation

  • Daniel John Zizzo, 2012. "Inducing natural group identity: A RDP analysis," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 12-01, School of Economics, University of East Anglia, Norwich, UK..
    • Handle: RePEc:uea:wcbess:12-01
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    References listed on IDEAS

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    1. Shaun Hargreaves Heap & Daniel John Zizzo, 2011. "Emotions and chat in a financial markets experiment," Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) 11-11, School of Economics, University of East Anglia, Norwich, UK..
    2. Afridi, Farzana & Li, Sherry Xin & Ren, Yufei, 2015. "Social identity and inequality: The impact of China's hukou system," Journal of Public Economics, Elsevier, vol. 123(C), pages 17-29.
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    7. Li, Sherry Xin & Dogan, Kutsal & Haruvy, Ernan, 2011. "Group identity in markets," International Journal of Industrial Organization, Elsevier, vol. 29(1), pages 104-115, January.
    8. Zafar, Basit, 2011. "An experimental investigation of why individuals conform," European Economic Review, Elsevier, vol. 55(6), pages 774-798, August.
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    10. Daniel Zizzo, 2010. "Experimenter demand effects in economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 13(1), pages 75-98, March.
    11. Francesco Guala, 2002. "On the scope of experiments in economics: comments on Siakantaris," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 26(2), pages 261-267, March.
    12. Zizzo, Daniel John & Fleming, Piers, 2011. "Can experimental measures of sensitivity to social pressure predict public good contribution?," Economics Letters, Elsevier, vol. 111(3), pages 239-242, June.
    13. Vernon L. Smith, 1994. "Economics in the Laboratory," Journal of Economic Perspectives, American Economic Association, vol. 8(1), pages 113-131, Winter.
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    Cited by:

    1. Zhixin Dai & Fabio Galeotti & Marie Claire Villeval, 2018. "Cheating in the Lab Predicts Fraud in the Field: An Experiment in Public Transportation," Management Science, INFORMS, vol. 64(3), pages 1081-1100, March.
    2. Brit Grosskopf & Graeme Pearce, 2020. "Do You Mind Me Paying Less? Measuring Other-Regarding Preferences in the Market for Taxis," Management Science, INFORMS, vol. 66(11), pages 5059-5074, November.
    3. Francesca Gioia, 2017. "Peer effects on risk behaviour: the importance of group identity," Experimental Economics, Springer;Economic Science Association, vol. 20(1), pages 100-129, March.

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    More about this item

    Keywords

    Confounds; objectives; economic experiments; group identity; natural groups; priming;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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