IDEAS home Printed from https://ideas.repec.org/a/sae/jinter/v29y2017i2p87-131.html
   My bibliography  Save this article

What Drives Reticence? Reporting Bias from Monopolies and Distrustful Firm Managers

Author

Listed:
  • Fola Malomo

Abstract

This article examines the determinants of underreporting (reticence) on randomized response questions. A simple model is created to describe the interview process and draw some conclusion as to why people might misreport their true status despite given the assurance of institutional and statistical confidentiality. By looking at the relationship between firm-specific reticence and other firm-specific and industry-location-specific variables, it is found that (mis)trust (proxied by the proportion of contracts arranged before delivery) is a significant predictor of reticence. Underreporting does not seem to be significantly related to a misunderstanding of the procedure, education, profit levels or guilt. This seems to suggest that firms which are more cautious in their business dealings are also more cautious with the randomized response (RR) technique. In such cases, weighted estimates of the prevalence of sensitive traits might be derived without the use of the RR technique but through the use of variables relating to the nature of firm-level contracts. Moreover, more accurate data on sensitive topics can be extracted from large homogeneous populations. JEL: C81, C83, D81

Suggested Citation

  • Fola Malomo, 2017. "What Drives Reticence? Reporting Bias from Monopolies and Distrustful Firm Managers," Journal of Interdisciplinary Economics, , vol. 29(2), pages 87-131, July.
  • Handle: RePEc:sae:jinter:v:29:y:2017:i:2:p:87-131
    as

    Download full text from publisher

    File URL: http://jie.sagepub.com/content/29/2/87.abstract
    Download Restriction: no

    More about this item

    Keywords

    Trust; behavioural economics; social behaviour; risk; reticence;

    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
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:sae:jinter:v:29:y:2017:i:2:p:87-131. 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: (SAGE Publications). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

    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.