On the provision of incentives in finance experiments


Monetary incentives are a procedural pillar in experimental economics. By applying four distinct monetary incentive schemes in three experimental finance applications, we investigate the impact of an incentive scheme’s salience on results and elicit subjects’ perception of the experienced scheme. We find (1) no differences in results between salient schemes but a significant impact if the incentive scheme is non-salient. (2) The number of previous participations has a significant impact on the perception of the incentive scheme by subjects: it strongly correlates with subjects’ motives for participation, positively contributes to subjects’ understanding of the incentive scheme, but has no influence on subjects’ motivation within the experiment. (3) Subjects favor more salient over less- or non-salient schemes in the gain domain and negatively evaluate high salience in the loss domain.

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  1. 1.

    Our paper is closely related to research in experimental methodology by Charness et al. (2016) who study payment approaches in multiple decision games.

  2. 2.

    In most studies experimental currencies are (linearly) converted at a previously announced exchange rate into local currency. We do not include exchange rates in our discussion because we pursue a different approach in this study.

  3. 3.

    By eliminating (selling) all initial endowments which depend on random realizations (assets), subjects could render themselves independent of these realizations. If the endowment value strongly influences subjects’ payouts a hedging motive might play a role for some subjects. Of course to pursue such a strategy might not be feasible for all subjects. Furthermore, note that usually the endowment value cannot become negative (asset values greater or equal to 0).

  4. 4.

    One might argue, that the third condition provided in Friedman and Sunder (1994), dependence on the characteristics of the institution, is met. However, we are reluctant to classify a factor which only meets the third condition but not the more substantial first and the second conditions, as salient.

  5. 5.

    Using a show-up fee to compensate for losses is problematic if losses accumulated during the experiment exceed the show-up fee. To require that subjects cover these losses is almost impossible to implement as it most likely causes severe damage to the subject pool. Thus, most experimental labs explicitly prohibit such rules (e.g., Bonn bonneconlab (https://www.bonneconlab.uni-bonn.de/teilnahmen-an-experimenten/faqs), Innsbruck EconLab (http://eeecon.uibk.ac.at/images/stories/econlab_terms_of_use_v1.3.2.pdf), Munich econlab (https://www.econlab.mpg.de/regeln-datenschutz-und-haftungsbestimmungen/)).

  6. 6.

    A show-up fee in line with the standard convention and amounting to € 4 is paid to supplementary subjects who we invited to an experimental session but could not participate in the experiment due to space constraints.

  7. 7.

    Of course the ex-post manipulation of pd may induce subjects to behave differently in the experiment. The goal of this paper is to analyze these behavioral responses and to evaluate their effects on results.

  8. 8.

    See Kirchler et al. (2012), Noussair and Tucker (2016), and references therein on the effects of cash endowments on mispricing.

  9. 9.

    Similar to Bradbury et al. (2014) the numbers are taken from the time series of the 6-month euribor as a proxy for the risk-free rate (for the time span before its implementation the fibor—Frankfurt Interbank Offered Rate—was taken) and from the dax as a proxy for the risky asset. We calculate returns and SD for a 20-year-period from January 1, 1994–December 31, 2013. The numbers reflect semi-annual returns and SD.

  10. 10.

    In Web Appendix 5 we provide descriptive statistics about subjects attending our experimental sessions. The information includes gender, age, years of study, subjects risk attitude in a general and in an investment context and the share of students from econ study programs. We find no statistical significant differences in the subject pool across experiments and treatments.

  11. 11.

    Web Appendix 1 outlines details on the calculation of these measures. Detailed information on the evolution of individual market prices and individual market results for rad, spread, vola, and st in experiment \(\mathrm {\textsc {price}}\) can be found in Web Appendix 2.

  12. 12.

    We thank an anonymous referee for pointing us at this observation.

  13. 13.

    Web Appendix 1 outlines details on the calculation of these measures. The evolution of individual transaction prices and individual market results for rad, spread, st, and vola in experiment \(\mathrm {\textsc {info}}\) can be found in Web Appendix 3.

  14. 14.

    See Web Appendix 4 for information on individual investment rates per session.

  15. 15.

    Figures are available upon request. We thank an anonymous referee for pointing us at this analysis. Note that subjects learned pd at the end of the experiment. We do not choose final earnings as our performance measure due to the manipulations in the different incentive schemes it is difficult to compare it across treatments, especially when considering \(\mathrm {\textsc {fix}}\).

  16. 16.

    We excluded the category “other motives” from the graphical presentation and statistical examination due to the low number of subjects choosing this category and due to shortage of space.

  17. 17.

    One potential explanation for the observed pattern could be the following: Subjects attending an experiment for the first time do so with a certain mindset regarding incentives. This mindset might be shaped by information studied before signing up or by other sources like fellow students. As linear incentive schemes are a standard procedure, incentive scheme \(\mathrm {\textsc {low}}\) might correspond to inexperienced subjects’ mindset who then evaluate this incentive structure as the most intuitive.


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We thank Stefan Palan, Felix Holzmeister, two anonymous referees and conference participants at Experimental Finance 2015 (Nijmegen) for helpful comments. Financial support by the University of Innsbruck (Hypo (Stöckl) and Nachwuchsförderung (Kleinlercher)) and UniCredit (Modigliani Research Grant, 4th edition, Stöckl) is gratefully acknowledged. The authors hereby declare that this paper reports all experimental sessions conducted within the course of this study.

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Correspondence to Thomas Stöckl.

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Kleinlercher, D., Stöckl, T. On the provision of incentives in finance experiments. Exp Econ 21, 154–179 (2018). https://doi.org/10.1007/s10683-017-9530-7

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  • Experimental finance
  • Incentives
  • Salience
  • Asset market
  • Mispricing
  • Information aggregation
  • Investment decision

JEL Classification

  • C92
  • D82
  • G12
  • G14