Nothing Special   »   [go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp4011.html
   My bibliography  Save this paper

Measuring Inequality Using Censored Data: A Multiple Imputation Approach

Author

Listed:
  • Jenkins, Stephen P.

    (London School of Economics)

  • Burkhauser, Richard V.

    (University of Texas at Austin)

  • Feng, Shuaizhang

    (Shanghai University of Finance and Economics)

  • Larrimore, Jeff

    (Federal Reserve Board)

Abstract
To measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference uses Reiter’s (Survey Methodology 2003) formulae. Using Current Population Survey (CPS) internal data, we find few statistically significant differences in income inequality for pairs of years between 1995 and 2004. We also show that using CPS public use data with cell mean imputations may lead to incorrect inferences about inequality differences. Multiply-imputed public use data provide an intermediate solution.

Suggested Citation

  • Jenkins, Stephen P. & Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," IZA Discussion Papers 4011, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp4011
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp4011.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Richard Burkhauser & Jeff Larrimore, 2008. "Using Internal Current Population Survey Data to Reevaluate Trends in Labor Earnings Gaps by Gender, Race, and Education Level," Working Papers 08-18, Center for Economic Studies, U.S. Census Bureau.
    2. Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2008. "Measuring Labor Earnings Inequality using Public-Use March Current Population Survey Data: The Value of Including Variances and Cell Means When Imputing Topcoded Values," NBER Working Papers 14458, National Bureau of Economic Research, Inc.
    3. Gartner, Hermann & Rässler, Susanne, 2005. "Analyzing the changing gender wage gap based on multiply imputed right censored wages," IAB-Discussion Paper 200505, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    4. Stephen P. Jenkins, 2006. "SVYLORENZ: Stata module to derive distribution-free variance estimates from complex survey data, of quantile group shares of a total, cumulative quantile group shares," Statistical Software Components S456602, Boston College Department of Economics, revised 15 Sep 2015.
    5. Angle, John & Tolbert, Charles M., 1999. "Topcodes and the Great U-Turn in Nonmetro/Metro Wage and Salary Inequality," Staff Reports 278835, United States Department of Agriculture, Economic Research Service.
    6. Cowell, F.A., 2000. "Measurement of inequality," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 2, pages 87-166, Elsevier.
    7. Beach, Charles M & Richmond, James, 1985. "Joint Confidence Intervals for Income Shares and Lorenz Curves," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 26(2), pages 439-450, June.
    8. Feng, Shuaizhang & Burkhauser, Richard V. & Butler, J.S., 2006. "Levels and Long-Term Trends in Earnings Inequality: Overcoming Current Population Survey Censoring Problems Using the GB2 Distribution," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 57-62, January.
    9. Richard Burkhauser & Jeff Larrimore, 2008. "Trends in the Relative Household Income of Working-Age Men with Work Limitations: Correcting the Record Using Internal Current Population Survey Data," Working Papers 08-05, Center for Economic Studies, U.S. Census Bureau.
    10. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    11. Peter Gottschalk & Sheldon Danziger, 2005. "Inequality Of Wage Rates, Earnings And Family Income In The United States, 1975–2002," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(2), pages 231-254, June.
    12. Bishop, John A & Chiou, Jong-Rong & Formby, John P, 1994. "Truncation Bias and the Ordinal Evaluation of Income Inequality," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(1), pages 123-127, January.
    13. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    14. Jeff Larrimore & Richard Burkhauser & Shuaizhang Feng & Laura Zayatz, 2008. "Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1976-2007)," Working Papers 08-06, Center for Economic Studies, U.S. Census Bureau.
    15. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    16. Cowell, Frank A & Victoria-Feser, Maria-Pia, 1996. "Robustness Properties of Inequality Measures," Econometrica, Econometric Society, vol. 64(1), pages 77-101, January.
    17. Thomas Lemieux, 2006. "Increasing Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill?," American Economic Review, American Economic Association, vol. 96(3), pages 461-498, June.
    18. Martin Biewen & Stephen P. Jenkins, 2006. "Variance Estimation for Generalized Entropy and Atkinson Inequality Indices: the Complex Survey Data Case," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(3), pages 371-383, June.
    19. A.B. Atkinson & F. Bourguignon (ed.), 2000. "Handbook of Income Distribution," Handbook of Income Distribution, Elsevier, edition 1, volume 1, number 1.
    20. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2008. "Trends in U.S. Wage Inequality: Revising the Revisionists," The Review of Economics and Statistics, MIT Press, vol. 90(2), pages 300-323, May.
    21. Schluter, Christian & Trede, Mark, 2002. "Tails of Lorenz curves," Journal of Econometrics, Elsevier, vol. 109(1), pages 151-166, July.
    22. Stephen P. Jenkins & Martin Biewen, 2005. "SVYGEI_SVYATK: Stata module to derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data," Statistical Software Components S453601, Boston College Department of Economics, revised 31 Aug 2017.
    23. repec:bla:econom:v:58:y:1991:i:232:p:461-77 is not listed on IDEAS
    24. Di An & Roderick J. A. Little, 2007. "Multiple imputation: an alternative to top coding for statistical disclosure control," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 923-940, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2009. "Recent Trends in Top Income Shares in the USA: Reconciling Estimates from March CPS and IRS Tax Return Data," Working Papers 09-26, Center for Economic Studies, U.S. Census Bureau.
    2. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    3. Doerrenberg, Philipp & Duncan, Denvil & Fuest, Clemens & Peichl, Andreas, 2012. "Nice Guys Finish Last: Are People with Higher Tax Morale Taxed More Heavily?," IZA Discussion Papers 6275, Institute of Labor Economics (IZA).
    4. Kitov, Ivan & Kitov, Oleg, 2015. "Gender income disparity in the USA: analysis and dynamic modelling," MPRA Paper 67146, University Library of Munich, Germany.
    5. SOLOGON Denisa & VAN KERM Philippe, 2014. "Earnings dynamics, foreign workers and the stability of inequality trends in Luxembourg 1988-2009," LISER Working Paper Series 2014-03, Luxembourg Institute of Socio-Economic Research (LISER).
    6. Weber, Jan David & Scharfenaker, Ellis, 2024. "Measures of firm performance and concentration: Stylized facts and a dilemma of data reproduction," Economics Letters, Elsevier, vol. 234(C).
    7. Nora Lustig, 2016. "Commitment to Equity Handbook. A Guide to Estimating the Impact of Fiscal Policy on Inequality and Poverty," Commitment to Equity (CEQ) Working Paper Series 1301, Tulane University, Department of Economics.
    8. Jonathan D. Fisher & David S. Johnson & Timothy M. Smeeding, 2013. "Measuring the Trends in Inequality of Individuals and Families: Income and Consumption," American Economic Review, American Economic Association, vol. 103(3), pages 184-188, May.

    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. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2011. "Estimating trends in US income inequality using the Current Population Survey: the importance of controlling for censoring," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(3), pages 393-415, September.
    2. Stephen P. Jenkins & Richard V. Burkhauser & Shuaizhang Feng & Jeff Larrimore, 2011. "Measuring inequality using censored data: a multiple‐imputation approach to estimation and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 63-81, January.
    3. Philip Armour & Richard V. Burkhauser & Jeff Larrimore, 2016. "Using The Pareto Distribution To Improve Estimates Of Topcoded Earnings," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 1263-1273, April.
    4. Frank A. Cowell & Emmanuel Flachaire, 2014. "Statistical Methods for Distributional Analysis," Working Papers halshs-01115996, HAL.
    5. Richard Burkhauser & Shuaizhang Feng & Stephen Jenkins & Jeff Larrimore, 2009. "Recent Trends in Top Income Shares in the USA: Reconciling Estimates from March CPS and IRS Tax Return Data," Working Papers 09-26, Center for Economic Studies, U.S. Census Bureau.
    6. Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2010. "Improving imputations of top incomes in the public-use current population survey by using both cell-means and variances," Economics Letters, Elsevier, vol. 108(1), pages 69-72, July.
    7. Vladimir Hlasny & Paolo Verme, 2022. "The Impact of Top Incomes Biases on the Measurement of Inequality in the United States," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 749-788, August.
    8. Salverda, Wiemer & Checchi, Daniele, 2014. "Labour-Market Institutions and the Dispersion of Wage Earnings," IZA Discussion Papers 8220, Institute of Labor Economics (IZA).
    9. Markus P. A. Schneider, 2013. "Race & Gender Differences in the Experience of Earnings Inequality in the US from 1995 to 2010," Working Papers 1303, New School for Social Research, Department of Economics.
    10. Salvatore Morelli & Timothy Smeeding & Jeffrey Thompson, 2014. "Post-1970 Trends in Within-Country Inequality and Poverty: Rich and Middle Income Countries," CSEF Working Papers 356, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    11. Flávio Cunha & James Heckman, 2016. "Decomposing Trends in Inequality in Earnings into Forecastable and Uncertain Components," Journal of Labor Economics, University of Chicago Press, vol. 34(S2), pages 31-65.
    12. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    13. Danny Ben-Shahar & Jacob Warszawski, 2016. "Inequality in housing affordability: Measurement and estimation," Urban Studies, Urban Studies Journal Limited, vol. 53(6), pages 1178-1202, May.
    14. João Nicolau & Pedro Raposo & Paulo M. M. Rodrigues, 2023. "Measuring wage inequality under right censoring," Economic Inquiry, Western Economic Association International, vol. 61(2), pages 377-401, April.
    15. Nora Lustig, 2019. "The “Missing Rich” in Household Surveys: Causes and Correction Approaches," Commitment to Equity (CEQ) Working Paper Series 75, Tulane University, Department of Economics.
    16. Ellis Scharfenaker, Markus P.A. Schneider, 2019. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Paper Series, Department of Economics, University of Utah 2019_08, University of Utah, Department of Economics.
    17. Schluter, Christian & van Garderen, Kees Jan, 2009. "Edgeworth expansions and normalizing transforms for inequality measures," Journal of Econometrics, Elsevier, vol. 150(1), pages 16-29, May.
    18. Nora Lustig, 2020. "The ``missing rich'' in household surveys: causes and correction approaches," Working Papers 520, ECINEQ, Society for the Study of Economic Inequality.
    19. Theodore Koutmeridis, 2013. "The Market for "Rough Diamonds": Information, Finance and Wage Inequality," CDMA Working Paper Series 201307, Centre for Dynamic Macroeconomic Analysis, revised 14 Oct 2013.
    20. Francois, Joseph & Rojas-Romagosa, Hugo, 2005. "The Construction and Interpretation of Combined Cross-Section and Time-Series Inequality Datasets," CEPR Discussion Papers 5214, C.E.P.R. Discussion Papers.

    More about this item

    Keywords

    topcoding; income inequality; CPS; Current Population Survey; partially synthetic data; Generalized Beta of the Second Kind distribution;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

    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:dp4011. 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: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.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.