IDEAS home Printed from https://ideas.repec.org/p/qss/dqsswp/0903.html
   My bibliography  Save this paper

How Reliable are Income Data Collected with a Single Question?

Author

Listed:
  • John Micklewright

    (Depatment of Quantitative Social Science - Institute of Education, University of London.)

  • Sylke V. Schnepf

    (School of Social Sciences and Southampton Statistical Sciences Research Institute, University of Southampton)

Abstract

Income is an important correlate for numerous phenomena in the social sciences. But many surveys collect data with just a single question covering all forms of income. This raises questions over the reliability of the data collected. Issues of reliability are heightened when individuals are asked about the household total rather than own income alone. We argue that the large literature on measuring incomes has not devoted enough attention to ‘single-question’ surveys. We investigate the reliability of single-question data using the ONS Omnibus survey and British Social Attitudes (BSA) survey as examples. We compare the distributions of income in these surveys – individual income in the Omnibus and household income in the BSA --- with those in two larger UK surveys that measure income in much greater detail. Distributions compare less well for household income than for individual income. Disaggregation by gender proves fruitful in much of the analysis. We also establish levels of item non-response to the income question in single-question surveys from a wide range of countries.

Suggested Citation

  • John Micklewright & Sylke V. Schnepf, 2009. "How Reliable are Income Data Collected with a Single Question?," DoQSS Working Papers 09-03, Quantitative Social Science - UCL Social Research Institute, University College London.
  • Handle: RePEc:qss:dqsswp:0903
    as

    Download full text from publisher

    File URL: https://repec.ucl.ac.uk/REPEc/pdf/qsswp0903.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ben Jann, 2008. "Multinomial goodness-of-fit: Large-sample tests with survey design correction and exact tests for small samples," Stata Journal, StataCorp LP, vol. 8(2), pages 147-169, June.
    2. Roberto Rigobon & Thomas M. Stoker, 2007. "Estimation With Censored Regressors: Basic Issues," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1441-1467, November.
    3. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, vol. 70(2), pages 519-546, March.
    4. Bound, John & Brown, Charles & Duncan, Greg J & Rodgers, Willard L, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
    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. Lutz Kilian, 2009. "Pitfalls in Estimating Asymmetric Effects of Energy Price Shocks," 2009 Meeting Papers 473, Society for Economic Dynamics.
    2. John Abowd & Martha Stinson, 2011. "Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Bureau Survey and SSA Administrative Data," Working Papers 11-20, Center for Economic Studies, U.S. Census Bureau.
    3. Kaspar Wüthrich, 2013. "Set Identification of Generalized Linear Predictors in the Presence of Non-Classical Measurement Errors," Diskussionsschriften dp1304, Universitaet Bern, Departement Volkswirtschaft.
    4. Thierry Magnac & Eric Maurin, 2008. "Partial Identification in Monotone Binary Models: Discrete Regressors and Interval Data," Review of Economic Studies, Oxford University Press, vol. 75(3), pages 835-864.
    5. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    6. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    7. Andrew Chesher & Adam Rosen, 2015. "Characterizations of identified sets delivered by structural econometric models," CeMMAP working papers CWP63/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Bauer, Philipp, 2006. "The Intergenerational Transmission of Income in Switzerland - A Comparison between Natives and Immigrants," Working papers 2006/01, Faculty of Business and Economics - University of Basel.
    9. repec:cep:stiecm:em/2012/559 is not listed on IDEAS
    10. Guido Imbens & Charles F. Manski, 2003. "Confidence intervals for partially identified parameters," CeMMAP working papers 09/03, Institute for Fiscal Studies.
    11. Gloria Gonzalez‐Rivera & Yun Luo & Esther Ruiz, 2020. "Prediction regions for interval‐valued time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 373-390, June.
    12. Hiroaki Kaido & Francesca Molinari & Jörg Stoye, 2019. "Confidence Intervals for Projections of Partially Identified Parameters," Econometrica, Econometric Society, vol. 87(4), pages 1397-1432, July.
    13. de Nicola, Francesca & Giné, Xavier, 2014. "How accurate are recall data? Evidence from coastal India," Journal of Development Economics, Elsevier, vol. 106(C), pages 52-65.
    14. Mark Aguiar & Corina Boar & Mark Bils, 2019. "Who Are the Hand-to-Mouth?," 2019 Meeting Papers 525, Society for Economic Dynamics.
    15. Ziliak, James P., 1998. "Does the choice of consumption measure matter? An application to the permanent-income hypothesis," Journal of Monetary Economics, Elsevier, vol. 41(1), pages 201-216, February.
    16. Arie Beresteanu & Francesca Molinari, 2008. "Asymptotic Properties for a Class of Partially Identified Models," Econometrica, Econometric Society, vol. 76(4), pages 763-814, July.
    17. Charles Bellemare & Luc Bissonnette & Sabine Kröger, 2010. "Bounding preference parameters under different assumptions about beliefs: a partial identification approach," Experimental Economics, Springer;Economic Science Association, vol. 13(3), pages 334-345, September.
    18. Christopher Flinn & Ahu Gemici & Steven Laufer, 2017. "Search, Matching, and Training," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 25, pages 260-297, April.
    19. Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
    20. Sule Alan, 2012. "Do disaster expectations explain household portfolios?," Quantitative Economics, Econometric Society, vol. 3(1), pages 1-28, March.
    21. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.

    More about this item

    Keywords

    income measurement; validity;

    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

    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:qss:dqsswp:0903. 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: https://edirc.repec.org/data/dqioeuk.html .

    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: Dr Neus Bover Fonts (email available below). General contact details of provider: https://edirc.repec.org/data/dqioeuk.html .

    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.