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The impact of different data sources on the level and structure of income inequality

Author

Listed:
  • Luis Ayala

    (UNED: Universidad Nacional de Educacion a Distancia)

  • Ana Pérez

    (Universidad de Valladolid)

  • Mercedes Prieto-Alaiz

    (Universidad de Valladolid)

Abstract

This paper aims to analyze the effect on measured inequality and its structure of using administrative data instead of survey data. Different analyses are carried out based on the Spanish Survey on Income and Living Conditions (ECV) that continued to ask households for their income despite assigning their income data as provided by the Tax Agency and the Social Security Administration. Our main finding is that the largest discrepancies between administrative and survey data are in the tails of the distribution. In addition to that, there are clear differences in the level and structure of inequality across data sources. These differences matter, and our results should be a wake-up call to interpret the results based on only one source of income data with caution.

Suggested Citation

  • Luis Ayala & Ana Pérez & Mercedes Prieto-Alaiz, 2022. "The impact of different data sources on the level and structure of income inequality," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(3), pages 583-611, September.
    • Handle: RePEc:spr:series:v:13:y:2022:i:3:d:10.1007_s13209-021-00258-0
    DOI: 10.1007/s13209-021-00258-0
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    as
    1. Thomas Piketty, 2013. "Le capital au XXIe siècle," Post-Print halshs-00979232, HAL.
    2. Stephen P. Jenkins & Fernando Rios‐Avila, 2021. "Measurement error in earnings data: Replication of Meijer, Rohwedder, and Wansbeek's mixture model approach to combining survey and register data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 474-483, June.
    3. Koen Decancq, 2020. "Measuring cumulative deprivation and affluence based on the diagonal dependence diagram," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 103-117, August.
    4. 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.
    5. DiNardo, John & Fortin, Nicole M & Lemieux, Thomas, 1996. "Labor Market Institutions and the Distribution of Wages, 1973-1992: A Semiparametric Approach," Econometrica, Econometric Society, vol. 64(5), pages 1001-1044, September.
    6. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    7. Reck, Daniel & Guyton, John & Langetieg, Patrick & Risch, Max & Zucman, Gabriel, 2021. "Tax Evasion at the Top of the Income Distribution: Theory and Evidence," CEPR Discussion Papers 15851, C.E.P.R. Discussion Papers.
    8. Joe, Harry, 1990. "Multivariate concordance," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 12-30, October.
    9. Michael D. Carr & Emily E. Wiemers, 2018. "New Evidence on Earnings Volatility in Survey and Administrative Data," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 287-291, May.
    10. Charles Courtemanche & Augustine Denteh & Rusty Tchernis, 2019. "Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation," Southern Economic Journal, John Wiley & Sons, vol. 86(1), pages 202-228, July.
    11. Jeff Larrimore, 2014. "Accounting for United States Household Income Inequality Trends: The Changing Importance of Household Structure and Male and Female Labor Earnings Inequality," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 683-701, December.
    12. Richard V. Burkhauser & Nicolas Hérault & Stephen P. Jenkins & Roger Wilkins, 2016. "What has Been Happening to UK Income Inequality Since the Mid-1990s? Answers from Reconciled and Combined Household Survey and Tax Return Data," NBER Working Papers 21991, National Bureau of Economic Research, Inc.
    13. Bengtsson, Erik & Waldenström, Daniel, 2018. "Capital Shares and Income Inequality: Evidence from the Long Run," The Journal of Economic History, Cambridge University Press, vol. 78(3), pages 712-743, September.
    14. Slemrod, Joel, 1995. "Income Creation or Income Shifting? Behavioral Responses to the Tax Reform Act of 1986," American Economic Review, American Economic Association, vol. 85(2), pages 175-180, May.
    15. Sean Higgins & Nora Lustig & Andrea Vigorito, 2018. "The Rich Underreport Their Income: Assessing Biases In Inequality Estimates And Correction Methods Using Linked Survey And Tax Data," Commitment to Equity (CEQ) Working Paper Series 70, Tulane University, Department of Economics.
    16. Peter Lynn & Annette Jäckle & Stephen P. Jenkins & Emanuela Sala, 2012. "The impact of questioning method on measurement error in panel survey measures of benefit receipt: evidence from a validation study," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(1), pages 289-308, January.
    17. Rolf Aaberge & Anthony B. Atkinson & Sebastian Königs, 2018. "From classes to copulas: wages, capital, and top incomes," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 295-320, June.
    18. Shorrocks, A F, 1982. "Inequality Decomposition by Factor Components," Econometrica, Econometric Society, vol. 50(1), pages 193-211, January.
    19. 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.
    20. Martin Ravallion, 2022. "Missing Top Income Recipients," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 205-222, March.
    21. Bruce D. Meyer & Derek Wu, 2018. "The Poverty Reduction of Social Security and Means-Tested Transfers," NBER Working Papers 24567, National Bureau of Economic Research, Inc.
    22. repec:iae:iaewps:wp2016n5 is not listed on IDEAS
    23. Sean Higgins & Nora Lustig & Andrea Vigorito, 2018. "The rich underreport their income: Assessing bias in inequality estimates and correction methods using linked survey and tax data," Working Papers 475, ECINEQ, Society for the Study of Economic Inequality.
    24. Genest, Christian & Nešlehová, Johanna G. & Rémillard, Bruno, 2013. "On the estimation of Spearman’s rho and related tests of independence for possibly discontinuous multivariate data," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 214-228.
    25. Mary C. Daly & Robert G. Valletta, 2006. "Inequality and Poverty in United States: The Effects of Rising Dispersion of Men's Earnings and Changing Family Behaviour," Economica, London School of Economics and Political Science, vol. 73(289), pages 75-98, February.
    26. Richard V. Burkhauser & Shuaizhang Feng & Stephen P. Jenkins & Jeff Larrimore, 2012. "Recent Trends in Top Income Shares in the United States: Reconciling Estimates from March CPS and IRS Tax Return Data," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 371-388, May.
    27. Bruce D. Meyer & Derek Wu, 2018. "The Poverty Reduction of Social Security and Means-Tested Transfers," ILR Review, Cornell University, ILR School, vol. 71(5), pages 1106-1153, October.
    28. Jean-Yves Duclos & Abdelkrim Araar, 2006. "Poverty and Equity," Economic Studies in Inequality, Social Exclusion, and Well-Being, Springer, number 978-0-387-33318-2, July.
    29. D. L. Oberski & A. Kirchner & S. Eckman & F. Kreuter, 2017. "Evaluating the Quality of Survey and Administrative Data with Generalized Multitrait-Multimethod Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1477-1489, October.
    30. Molly Dahl & Thomas DeLeire & Jonathan A. Schwabish, 2011. "Estimates of Year-to-Year Volatility in Earnings and in Household Incomes from Administrative, Survey, and Matched Data," Journal of Human Resources, University of Wisconsin Press, vol. 46(4), pages 750-774.
    31. Pérez, Ana & Prieto-Alaiz, Mercedes, 2016. "A note on nonparametric estimation of copula-based multivariate extensions of Spearman’s rho," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 41-50.
    32. Jeff Larrimore & Richard V. Burkhauser & Gerald Auten & Philip Armour, 2021. "Recent Trends in US Income Distributions in Tax Record Data Using More Comprehensive Measures of Income Including Real Accrued Capital Gains," Journal of Political Economy, University of Chicago Press, vol. 129(5), pages 1319-1360.
    33. Lerman, Robert I & Yitzhaki, Shlomo, 1985. "Income Inequality Effects by Income," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 151-156, February.
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    More about this item

    Keywords

    Inequality; Administrative data; Measurement error; Dependences; Copula;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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