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Eliciting Information from Sensitive Survey Questions

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  • Yonghong An
  • Pengfei Liu

Abstract

This paper considers how to elicit information from sensitive survey questions. First we thoroughly evaluate list experiments (LE), a leading method in the experimental literature on sensitive questions. Our empirical results demonstrate that the assumptions required to identify sensitive information in LE are violated for the majority of surveys. Next we propose a novel survey method, called Multiple Response Technique (MRT), for eliciting information from sensitive questions. We require all of the respondents to answer three questions related to the sensitive information. This technique recovers sensitive information at a disaggregated level while still allowing arbitrary misreporting in survey responses. An application of the MRT provides novel empirical evidence on sexual orientation and Lesbian, Gay, Bisexual, and Transgender (LGBT)-related sentiment.

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  • Yonghong An & Pengfei Liu, 2020. "Eliciting Information from Sensitive Survey Questions," Papers 2009.01430, arXiv.org.
  • Handle: RePEc:arx:papers:2009.01430
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    1. Shuaizhang Feng & Yingyao Hu, 2013. "Misclassification Errors and the Underestimation of the US Unemployment Rate," American Economic Review, American Economic Association, vol. 103(2), pages 1054-1070, April.
    2. Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-594, July.
    3. Humphreys, Macartan & de la Sierra, Raúl Sánchez & der Windt, Peter Van, 2019. "Exporting democratic practices: Evidence from a village governance intervention in Eastern Congo," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 140, pages 279-301.
    4. Barrera, Oscar & Guriev, Sergei & Henry, Emeric & Zhuravskaya, Ekaterina, 2020. "Facts, alternative facts, and fact checking in times of post-truth politics," Journal of Public Economics, Elsevier, vol. 182(C).
    5. Christopher Blattman & Julian C. Jamison & Margaret Sheridan, 2017. "Reducing Crime and Violence: Experimental Evidence from Cognitive Behavioral Therapy in Liberia," American Economic Review, American Economic Association, vol. 107(4), pages 1165-1206, April.
    6. Robin, Jean-Marc & Smith, Richard J., 2000. "Tests Of Rank," Econometric Theory, Cambridge University Press, vol. 16(2), pages 151-175, April.
    7. Katherine B. Coffman & Lucas C. Coffman & Keith M. Marzilli Ericson, 2017. "The Size of the LGBT Population and the Magnitude of Antigay Sentiment Are Substantially Underestimated," Management Science, INFORMS, vol. 63(10), pages 3168-3186, October.
    8. Blattman, Christopher & Jamison, Julian & Koroknay-Palicz, Tricia & Rodrigues, Katherine & Sheridan, Margaret, 2016. "Measuring the measurement error: A method to qualitatively validate survey data," Journal of Development Economics, Elsevier, vol. 120(C), pages 99-112.
    9. Karlan, Dean & Osman, Adam & Zinman, Jonathan, 2016. "Follow the money not the cash: Comparing methods for identifying consumption and investment responses to a liquidity shock," Journal of Development Economics, Elsevier, vol. 121(C), pages 11-23.
    10. Imai, Kosuke, 2011. "Multivariate Regression Analysis for the Item Count Technique," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 407-416.
    11. Karlan, Dean S. & Zinman, Jonathan, 2012. "List randomization for sensitive behavior: An application for measuring use of loan proceeds," Journal of Development Economics, Elsevier, vol. 98(1), pages 71-75.
    12. Ronconi, Lucas & Zarazaga S.J., Rodrigo, 2015. "Labor Exclusion and the Erosion of Citizenship Responsibilities," World Development, Elsevier, vol. 74(C), pages 453-461.
    13. Humphreys, Macartan & Sánchez de la Sierra, Raúl & Van der Windt, Peter, 2019. "Exporting democratic practices: Evidence from a village governance intervention in Eastern Congo," Journal of Development Economics, Elsevier, vol. 140(C), pages 279-301.
    14. Andrews, Donald W.K. & Shi, Xiaoxia, 2017. "Inference based on many conditional moment inequalities," Journal of Econometrics, Elsevier, vol. 196(2), pages 275-287.
    15. Bilir, L. Kamran & Chor, Davin & Manova, Kalina, 2019. "Host-country financial development and multinational activity," European Economic Review, Elsevier, vol. 115(C), pages 192-220.
    16. Yuyu Chen & David Y. Yang, 2019. "The Impact of Media Censorship: 1984 or Brave New World?," American Economic Review, American Economic Association, vol. 109(6), pages 2294-2332, June.
    17. Jouni Kuha & Jonathan Jackson, 2014. "The item count method for sensitive survey questions: modelling criminal behaviour," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 321-341, February.
    18. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    19. Carole Treibich & Aurélia Lépine, 2019. "Estimating misreporting in condom use and its determinants among sex workers: Evidence from the list randomisation method," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 144-160, January.
    20. Ronconi, Lucas & Zarazaga S.J., Rodrigo, 2015. "Labor Exclusion and the Erosion of Citizenship Responsibilities," World Development, Elsevier, vol. 74(C), pages 453-461.
    21. Jean-Marc Robin & Richard Smith, 2000. "Tests of rank," Post-Print hal-03587662, HAL.
    22. Davide Cantoni & David Y Yang & Noam Yuchtman & Y Jane Zhang, 2019. "Protests as Strategic Games: Experimental Evidence from Hong Kong's Antiauthoritarian Movement," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(2), pages 1021-1077.
    23. Yusuf Neggers, 2018. "Enfranchising Your Own? Experimental Evidence on Bureaucrat Diversity and Election Bias in India," American Economic Review, American Economic Association, vol. 108(6), pages 1288-1321, June.
    24. Johannes Haushofer & Jeremy Shapiro, 2016. "The Short-term Impact of Unconditional Cash Transfers to the Poor: ExperimentalEvidence from Kenya," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1973-2042.
    25. Imai, Kosuke & Park, Bethany & Greene, Kenneth F., 2015. "Using the Predicted Responses from List Experiments as Explanatory Variables in Regression Models," Political Analysis, Cambridge University Press, vol. 23(2), pages 180-196, April.
    26. Blair, Graeme & Chou, Winston & Imai, Kosuke, 2019. "List Experiments with Measurement Error," Political Analysis, Cambridge University Press, vol. 27(4), pages 455-480, October.
    27. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
    28. Xiaohong Chen & Han Hong & Elie Tamer, 2005. "Measurement Error Models with Auxiliary Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(2), pages 343-366.
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