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The impact of alternative imputation methods on the measurement of income and wealth: Evidence from the Spanish survey of household finances

  • Cristina Barceló

    ()

    (Banco de España)

The goal of this paper is to emphasise the importance of the way of handling missing data and its impact on the outcome of empirical studies. Using the 2002 wave of the Spanish Survey of Household Finances (EFF), I study the performance of alternative methods: listwise deletion, non-stochastic, multiple and single imputation based on linear-regression models, and hot-deck procedures. Using descriptive statistics of the marginal and conditional distributions of income and wealth and estimating mean and quantile regressions, listwise deletion brings imprecise and biased estimates, non-stochastic imputation underestimates variance and dispersion and hot deck fails to capture the potential relationships among survey variables.

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File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/08/Fic/dt0829e.pdf
File Function: First version, December 2008
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Paper provided by Banco de Espa�a in its series Banco de Espa�a Working Papers with number 0829.

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Length: 63 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:bde:wpaper:0829
Contact details of provider: Web page: http://www.bde.es/
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  1. Martin Browning & Thomas F. Crossley & Guglielmo Weber, 2002. "Asking Consumption Questions in General Purpose Surveys," Social and Economic Dimensions of an Aging Population Research Papers 77, McMaster University.
  2. Martin Browning & Annamaria Lusardi, 1996. "Household Saving: Micro Theories and Micro Facts," Journal of Economic Literature, American Economic Association, vol. 34(4), pages 1797-1855, December.
  3. Karen E. Dynan & Jonathan Skinner & Stephen P. Zeldes, 2000. "Do the Rich Save More?," NBER Working Papers 7906, National Bureau of Economic Research, Inc.
  4. Giuseppe De Luca & Franco Peracchi, 2012. "Estimating Engel curves under unit and item nonresponse," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1076-1099, November.
  5. Albarran, P., 2000. "Income Uncertainty and Precautionary Saving: Evidence from Household Rotating Panel Data," Papers 0008, Centro de Estudios Monetarios Y Financieros-.
  6. Cristina Barceló, 2006. "Imputation of the 2002 wave of the Spanish survey of household finances (EFF)," Banco de Espa�a Occasional Papers 0603, Banco de Espa�a.
  7. Olympia Bover, 2005. "Wealth effects on consumption: microeconometric estimates from the Spanish survey of household finances," Banco de Espa�a Working Papers 0522, Banco de Espa�a.
  8. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2005. "An econometric method of correcting for unit nonresponse bias in surveys," Policy Research Working Paper Series 3711, The World Bank.
  9. Christopher D. Carroll, 1992. "How does future income affect current consumption?," Working Paper Series / Economic Activity Section 126, Board of Governors of the Federal Reserve System (U.S.).
  10. Paul Kofman & Ian G. Sharpe, 2003. "Using Multiple Imputation in the Analysis of Incomplete Observations in Finance," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(2), pages 216-249.
  11. Karen E. Dynan, 1993. "How prudent are consumers?," Working Paper Series / Economic Activity Section 135, Board of Governors of the Federal Reserve System (U.S.).
  12. Dynan, Karen E, 1993. "How Prudent Are Consumers?," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1104-13, December.
  13. J. L. Hutton, 2000. "Number needed to treat: properties and problems," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 381-402.
  14. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2005. "Survey nonresponse and the distribution of income," Policy Research Working Paper Series 3543, The World Bank.
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