IDEAS home Printed from https://ideas.repec.org/p/bss/wpaper/17.html
   My bibliography  Save this paper

MTurk Survey on "Mood and Personality". Documentation

Author

Listed:
  • Marc Höglinger
  • Ben Jann

Abstract

Social desirability and the fear of negative consequences often deter a considerable share of survey respondents from responding truthfully to sensitive questions. Thus, resulting prevalence estimates are biased. Indirect techniques for surveying sensitive questions such as the Randomized Response Technique are intended to mitigate misreporting by providing complete concealment of individual answers. However, it is far from clear whether these indirect techniques actually produce more valid measurements than standard direct questioning. In order to evaluate the validity of different sensitive question techniques we carried out an online validation experiment at Amazon Mechanical Turk in which respondents' self-reports of norm-breaking behavior (cheating in dice games) were validated against observed behavior. This document describes the design of the validation experiment and provides details on the questionnaire, the different sensitive question technique implementations, the field work, and the resulting dataset. The appendix contains a codebook of the data and facsimiles of the questionnaire pages and other survey materials.

Suggested Citation

  • Marc Höglinger & Ben Jann, 2016. "MTurk Survey on "Mood and Personality". Documentation," University of Bern Social Sciences Working Papers 17, University of Bern, Department of Social Sciences.
  • Handle: RePEc:bss:wpaper:17
    as

    Download full text from publisher

    File URL: https://boris.unibe.ch/81516/1/ASQ-MTurk-2013.pdf
    File Function: documentation
    Download Restriction: no

    File URL: https://boris.unibe.ch/81516/8/ASQ-MTurk-2013.dta
    File Function: data file (Stata 13)
    Download Restriction: no

    File URL: https://boris.unibe.ch/81516/9/ASQ-MTurk-2013-source.zip
    File Function: raw data and do-files
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    2. Urs Fischbacher & Franziska Föllmi-Heusi, 2013. "Lies In Disguise—An Experimental Study On Cheating," Journal of the European Economic Association, European Economic Association, vol. 11(3), pages 525-547, June.
    3. Andreas Diekmann, 2012. "Making Use of “Benford’s Law†for the Randomized Response Technique," Sociological Methods & Research, , vol. 41(2), pages 325-334, May.
    4. Marc Höglinger & Ben Jann & Andreas Diekmann, 2014. "Online Survey on "Exams and Written Papers". Documentation," University of Bern Social Sciences Working Papers 8, University of Bern, Department of Social Sciences, revised 06 Oct 2014.
    Full references (including those not matched with items on IDEAS)

    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. Marc Höglinger & Ben Jann, 2018. "More is not always better: An experimental individual-level validation of the randomized response technique and the crosswise model," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-22, August.
    2. Heinicke, Franziska & Rosenkranz, Stephanie & Weitzel, Utz, 2019. "The effect of pledges on the distribution of lying behavior: An online experiment," Journal of Economic Psychology, Elsevier, vol. 73(C), pages 136-151.
    3. Dato, Simon & Feess, Eberhard & Nieken, Petra, 2019. "Lying and reciprocity," Games and Economic Behavior, Elsevier, vol. 118(C), pages 193-218.
    4. Valerio Capraro, 2018. "Gender differences in lying in sender-receiver games: A meta-analysis," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(4), pages 345-355, July.
    5. Garbarino, Ellen & Slonim, Robert & Villeval, Marie Claire, 2019. "Loss aversion and lying behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 379-393.
    6. Hardin, Ashley E. & Bauman, Christopher W. & Mayer, David M., 2020. "Show me the … family: How photos of meaningful relationships reduce unethical behavior at work," Organizational Behavior and Human Decision Processes, Elsevier, vol. 161(C), pages 93-108.
    7. Stefania Bortolotti & Ivan Soraperra & Matthias Sutter & Claudia Zoller, 2017. "Too Lucky to be True - Fairness Views under the Shadow of Cheating," CESifo Working Paper Series 6563, CESifo.
    8. Nicolas Jacquemet & Alexander James & Stéphane Luchini & James Murphy & Jason F. Shogren, 2019. "Lying and Shirking Under Oath," Working Papers 19-19, Chapman University, Economic Science Institute.
      • Nicolas Jacquemet & Alexander James & Stéphane Luchini & James J. Murphy & Jason F. Shogren, 2019. "Lying and Shirking Under Oath," Working Papers 2019-02, University of Alaska Anchorage, Department of Economics.
    9. Nicolas Jacquemet & Alexander G James & Stéphane Luchini & James J Murphy & Jason F Shogren, 2021. "Do truth-telling oaths improve honesty in crowd-working?," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-18, January.
    10. Rahwan, Zoe & Hauser, Oliver P. & Kochanowska, Ewa & Fasolo, Barbara, 2018. "High stakes: A little more cheating, a lot less charity," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 276-295.
    11. Christian Schitter & Stefan Palan, 2018. "Should I wait or should I lie? Path dependency and timing in repeated honesty decisions under frames," Working Paper Series, Social and Economic Sciences 2018-05, Faculty of Social and Economic Sciences, Karl-Franzens-University Graz.
    12. Palan, Stefan & Schitter, Christian, 2018. "Prolific.ac—A subject pool for online experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 17(C), pages 22-27.
    13. Christoph Engel, 2016. "Experimental Criminal Law. A Survey of Contributions from Law, Economics and Criminology," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2016_07, Max Planck Institute for Research on Collective Goods.
    14. Potters, Jan & Stoop, Jan, 2016. "Do cheaters in the lab also cheat in the field?," European Economic Review, Elsevier, vol. 87(C), pages 26-33.
    15. Anna Dreber & Tore Ellingsen & Magnus Johannesson & David Rand, 2013. "Do people care about social context? Framing effects in dictator games," Experimental Economics, Springer;Economic Science Association, vol. 16(3), pages 349-371, September.
    16. Rebecca R Carter & Analisa DiFeo & Kath Bogie & Guo-Qiang Zhang & Jiayang Sun, 2014. "Crowdsourcing Awareness: Exploration of the Ovarian Cancer Knowledge Gap through Amazon Mechanical Turk," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    17. Abeler, Johannes & Falk, Armin & Kosse, Fabian, 2021. "Malleability of Preferences for Honesty," Rationality and Competition Discussion Paper Series 282, CRC TRR 190 Rationality and Competition.
    18. Yamada, Katsunori & Sato, Masayuki, 2013. "Another avenue for anatomy of income comparisons: Evidence from hypothetical choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 89(C), pages 35-57.
    19. Corgnet, Brice & Martin, Ludivine & Ndodjang, Peguy & Sutan, Angela, 2019. "On the merit of equal pay: Performance manipulation and incentive setting," European Economic Review, Elsevier, vol. 113(C), pages 23-45.
    20. Houser, Daniel & Vetter, Stefan & Winter, Joachim, 2012. "Fairness and cheating," European Economic Review, Elsevier, vol. 56(8), pages 1645-1655.

    More about this item

    Keywords

    Online Survey; Amazon Mechanical Turk; Sensitive Questions; Randomized Response Technique; Crosswise Model; Dice Game; Validation;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

    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:bss:wpaper:17. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.sowi.unibe.ch/ .

    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: Ben Jann (email available below). General contact details of provider: http://www.sowi.unibe.ch/ .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.