IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp17332.html

Noncognitive Human Capital and Misreporting Behavior in Online Surveys

Author

Listed:
  • Li, Haizheng

    (Georgia Institute of Technology)

  • Liu, Qinyi

    (University of Nottingham Ningbo China)

  • Xu, Yiting

    (Central University of Finance and Economics Beijing)

Abstract

In this study, we investigate misreporting behavior in online surveys based on the field experiments in a large-scale online training program for rural teachers. We link the digitally recorded data with survey responses and integrate randomized controlled trials (RCTs) in the survey design. Noncognitive human capital is measured using both self-reported personality traits and proxies based on observed behaviors. Our results show that the impact of observed individual characteristics varies depending on the nature of the question and survey specifics. Unobserved heterogeneity affects both survey participation and response accuracy, resulting in sample selectivity. Noncognitive human capital inferred from observed behaviors consistently shows important influence on misreporting, while that measured by self-reported personality traits suffers from the same misreporting problem. However, behavior proxy may also capture factors external to survey respondents, and it is important to separate the effect of noncognitive human capital from the external impacts. Additionally, survey design affects misreporting. Therefore, improving the efficiency of survey such as by changing the saliency and optimizing the sequence of questions, can improve survey quality. These findings carry important implications for using survey data and for improving survey data quality.

Suggested Citation

  • Li, Haizheng & Liu, Qinyi & Xu, Yiting, 2024. "Noncognitive Human Capital and Misreporting Behavior in Online Surveys," IZA Discussion Papers 17332, IZA Network @ LISER.
    • Handle: RePEc:iza:izadps:dp17332
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp17332.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Celhay, Pablo & Meyer, Bruce D. & Mittag, Nikolas, 2024. "What leads to measurement errors? Evidence from reports of program participation in three surveys," Journal of Econometrics, Elsevier, vol. 238(2).
    2. Leonardo Bursztyn & Robert Jensen, 2017. "Social Image and Economic Behavior in the Field: Identifying, Understanding, and Shaping Social Pressure," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 131-153, September.
    3. Abay, Kibrom A. & Barrett, Christopher B. & Kilic, Talip & Moylan, Heather & Ilukor, John & Vundru, Wilbert Drazi, 2023. "Nonclassical measurement error and farmers’ response to information treatment," Journal of Development Economics, Elsevier, vol. 164(C).
    4. Bašić, Zvonimir & Quercia, Simone, 2022. "The influence of self and social image concerns on lying," Games and Economic Behavior, Elsevier, vol. 133(C), pages 162-169.
    5. John M. Abowd & Martha H. Stinson, 2013. "Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1451-1467, December.
    6. 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.
    7. Anke Becker & Thomas Deckers & Thomas Dohmen & Armin Falk & Fabian Kosse, 2012. "The Relationship Between Economic Preferences and Psychological Personality Measures," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 453-478, July.
    8. Abraham, Katharine G. & Filiz-Ozbay, Emel & Ozbay, Erkut Y. & Turner, Lesley J., 2020. "Framing effects, earnings expectations, and the design of student loan repayment schemes," Journal of Public Economics, Elsevier, vol. 183(C).
    9. Dench, Daniel & Joyce, Theodore, 2022. "Information and credible sanctions in curbing online cheating among undergraduates: A field experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 195(C), pages 408-427.
    10. Thomas Dohmen & Tomáš Jagelka, 2024. "Accounting for Individual-Specific Reliability of Self-Assessed Measures of Economic Preferences and Personality Traits," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(3), pages 399-462.
    11. Burke, Mary A. & Carman, Katherine G., 2017. "You can be too thin (but not too tall): Social desirability bias in self-reports of weight and height," Economics & Human Biology, Elsevier, vol. 27(PA), pages 198-222.
    12. Mara Ewers & Florian Zimmermann, 2015. "Image And Misreporting," Journal of the European Economic Association, European Economic Association, vol. 13(2), pages 363-380, April.
    13. Alain Cohn & Ernst Fehr & Michel André Maréchal, 2014. "Business culture and dishonesty in the banking industry," Nature, Nature, vol. 516(7529), pages 86-89, December.
    14. Black, Dan & Sanders, Seth & Taylor, Lowell, 2003. "Measurement of Higher Education in the Census and Current Population Survey," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 545-554, January.
    15. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
    16. 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.
    17. Katharine G. Abraham & John Haltiwanger & Kristin Sandusky & James R. Spletzer, 2013. "Exploring Differences in Employment between Household and Establishment Data," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 129-172.
    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. Ha Trong Nguyen & Huong Thu Le & Luke Connelly & Francis Mitrou, 2023. "Accuracy of self‐reported private health insurance coverage," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2709-2729, December.
    2. Quinn Moore & Irma Perez-Johnson & Robert Santillano, 2018. "Decomposing Differences in Impacts on Survey- and Administrative-Measured Earnings From a Job Training Voucher Experiment," Evaluation Review, , vol. 42(5-6), pages 515-549, October.
    3. Hyslop, Dean R. & Townsend, Wilbur, 2017. "Employment misclassification in survey and administrative reports," Economics Letters, Elsevier, vol. 155(C), pages 19-23.
    4. Engzell, Per, 2017. "What Do Books in the Home Proxy For? A Cautionary Tale," Working Paper Series 1/2016, Stockholm University, Swedish Institute for Social Research.
    5. Bruce D. Meyer & Nikolas Mittag, 2015. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," NBER Working Papers 21676, National Bureau of Economic Research, Inc.
    6. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," IZA Discussion Papers 10943, IZA Network @ LISER.
    7. Andrew S. Green, 2017. "Hours Off the Clock," Working Papers 17-44, Center for Economic Studies, U.S. Census Bureau.
    8. Bruce Meyer & Nikolas Mittag, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," Working Papers 2017-075, Human Capital and Economic Opportunity Working Group.
    9. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Misclassification in binary choice models," Journal of Econometrics, Elsevier, vol. 200(2), pages 295-311.
    10. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, IZA Network @ LISER.
    11. Michele Lalla & Patrizio Frederic & Daniela Mantovani, 2022. "The inextricable association of measurement errors and tax evasion as examined through a microanalysis of survey data matched with fiscal data: a case study," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1375-1401, December.
    12. Sun, Jiandong & Feng, Shuaizhang & Hu, Yingyao, 2021. "Misclassification errors in labor force statuses and the early identification of economic recessions," Journal of Asian Economics, Elsevier, vol. 75(C).
    13. Sofianos, Andis, 2022. "Self-reported & revealed trust: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 88(C).
    14. Erich Battistin & Barbara Sianesi, 2006. "Misreported schooling and returns to education: evidence from the UK," CeMMAP working papers CWP07/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Daniel Wilhelm, 2018. "Testing for the presence of measurement error," CeMMAP working papers CWP45/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Friedrichsen, Jana & König, Tobias & Schmacker, Renke, 2018. "Social image concerns and welfare take-up," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 168, pages 174-192.
    17. Michele Lalla & Maddalena Cavicchioli, 2020. "Nonresponse and measurement errors in income: matching individual survey data with administrative tax data," Department of Economics 0170, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    18. Kautz, Tim & Heckman, James J. & Diris, Ron & ter Weel, Bas & Borghans, Lex, 2014. "Fostering and Measuring Skills: Improving Cognitive and Non-Cognitive Skills to Promote Lifetime Success," IZA Discussion Papers 8696, IZA Network @ LISER.
    19. Glätzle-Rützler, Daniela & Lergetporer, Philipp & Sutter, Matthias, 2021. "Collective intertemporal decisions and heterogeneity in groups," Games and Economic Behavior, Elsevier, vol. 130(C), pages 131-147.
    20. Dan A. Black & Lars Skipper & Jeffrey A. Smith & Jeffrey Andrew Smith, 2023. "Firm Training," CESifo Working Paper Series 10268, CESifo.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    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:iza:izadps:dp17332. See general information about how to correct material in RePEc.

    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: Mark Fallak (email available below). General contact details of provider: https://edirc.repec.org/data/izaaalu.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.