IDEAS home Printed from
   My bibliography  Save this paper

A statistical approach to detect cheating interviewers


  • Bredl, Sebastian
  • Winker, Peter
  • Kötschau, Kerstin


Survey data are potentially affected by cheating interviewers. Even a small number of fabricated interviews might seriously impair the results of further empirical analysis. Besides reinterviews some statistical approaches have been proposed for identifying fabrication of interviews. As a novel toolin this context, cluster and discriminant analysis are used. Several indicators are combined to classify 'at risk' interviewers based solely on the collected data. An application to a dataset with known cases of cheating interviewers demonstrates that the methods are able to identify the cheating interviewers with a high probability. The multivariate classiffication is superior to the application of a singleindicator such as Benford's law.

Suggested Citation

  • Bredl, Sebastian & Winker, Peter & Kötschau, Kerstin, 2008. "A statistical approach to detect cheating interviewers," Discussion Papers 39, Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU).
  • Handle: RePEc:zbw:zeudps:39

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Darby, Julia, et al, 1999. "The Impact of Exchange Rate Uncertainty on the Level of Investment," Economic Journal, Royal Economic Society, vol. 109(454), pages 55-67, March.
    2. Cross, Rod, 1994. "The Macroeconomic Consequences of Discontinuous Adjustment: Selective Memory of Non-dominated Extrema," Scottish Journal of Political Economy, Scottish Economic Society, vol. 41(2), pages 212-221, May.
    3. I. Agur, 2003. "Trade-volume hysteresis: an investigation using aggregate data," WO Research Memoranda (discontinued) 740, Netherlands Central Bank, Research Department.
    4. Richard Baldwin, 1989. "Sunk-Cost Hysteresis," NBER Working Papers 2911, National Bureau of Economic Research, Inc.
    5. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    6. N/A, 2009. "On the Recession," Local Economy, London South Bank University, vol. 24(3), pages 253-253, May.
    7. Campa, Jose Manuel, 2004. "Exchange rates and trade: How important is hysteresis in trade?," European Economic Review, Elsevier, vol. 48(3), pages 527-548, June.
    8. Pindyck, Robert S, 1988. "Irreversible Investment, Capacity Choice, and the Value of the Firm," American Economic Review, American Economic Association, vol. 78(5), pages 969-985, December.
    9. Kannebley Jr., Sergio, 2008. "Tests for the hysteresis hypothesis in Brazilian industrialized exports: A threshold cointegration analysis," Economic Modelling, Elsevier, vol. 25(2), pages 171-190, March.
    10. Gocke, Matthias, 2002. " Various Concepts of Hysteresis Applied in Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 16(2), pages 167-188, April.
    11. Roberts, Mark J & Tybout, James R, 1997. "The Decision to Export in Colombia: An Empirical Model of Entry with Sunk Costs," American Economic Review, American Economic Association, vol. 87(4), pages 545-564, September.
    12. Parsley, David C & Wei, Shang-Jin, 1993. "Insignificant and Inconsequential Hysteresis: The Case of U.S. Bilateral Trade," The Review of Economics and Statistics, MIT Press, vol. 75(4), pages 606-613, November.
    13. Andrew Bernard & Joachim Wagner, 2001. "Export entry and exit by German firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 137(1), pages 105-123, March.
    14. Godart, Olivier N. & Görg, Holger & Görlich, Dennis, 2009. "Back to normal? The future of global production networks after the crisis," Open Access Publications from Kiel Institute for the World Economy 32840, Kiel Institute for the World Economy (IfW).
    15. Ansgar Belke & Matthias Göcke, 2005. "Real Options Effects on Employment: Does Exchange Rate Uncertainty Matter for Aggregation?," German Economic Review, Verein für Socialpolitik, vol. 6(2), pages 185-203, May.
    16. Kostas Axarloglou & Painos Kouvelis, 1999. "Multinational corporations and the hysteresis in foreign direct investment flows," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 5(2), pages 271-271, May.
    17. Stahn, Kerstin, 2006. "Has the export pricing behaviour of German enterprises changed? Empirical evidence from German sectoral prices," Discussion Paper Series 1: Economic Studies 2006,37, Deutsche Bundesbank.
    18. Nick Bloom & Max Floetotto, 2009. "In brief: The recession will be over sooner than you think," CentrePiece - The Magazine for Economic Performance 271, Centre for Economic Performance, LSE.
    19. repec:jns:jbstat:v:227:y:2007:i:3:p:295-329 is not listed on IDEAS
    20. Paul R. Krugman & Richard E. Baldwin, 1987. "The Persistence of the U.S. Trade Deficit," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 18(1), pages 1-56.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. De Haas Samuel & Winker Peter, 2016. "Detecting Fraudulent Interviewers by Improved Clustering Methods – The Case of Falsifications of Answers to Parts of a Questionnaire," Journal of Official Statistics, De Gruyter Open, vol. 32(3), pages 643-660, September.
    2. Schräpler Jörg-Peter, 2011. "Benford’s Law as an Instrument for Fraud Detection in Surveys Using the Data of the Socio-Economic Panel (SOEP)," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(5-6), pages 685-718, October.
    3. Finn, Arden & Ranchhod, Vimal, 2013. "Genuine Fakes: The prevalence and implications of fieldworker fraud in a large South African survey," SALDRU Working Papers 115, Southern Africa Labour and Development Research Unit, University of Cape Town.
    4. Storfinger, Nina & Winker, Peter, 2011. "Robustness of clustering methods for identification of potential falsifications in survey data," Discussion Papers 57, Justus Liebig University Giessen, Center for international Development and Environmental Research (ZEU).
    5. Josten Michael & Trappmann Mark, 2016. "Interviewer Effects on a Network-Size Filter Question," Journal of Official Statistics, De Gruyter Open, vol. 32(2), pages 349-373, June.
    6. Michael Spagat, 2010. "Estimating the Human Costs of War: The Sample Survey Approach," HiCN Research Design Notes 14, Households in Conflict Network.


    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:zbw:zeudps:39. 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: (ZBW - German National Library of Economics). 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.