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Estimation of Households Income from Bracketed Income Survey Data

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Author Info

  • Enrico D’Elia

    (ISAE - Institute for Studies and Economic Analyses)

  • Bianca Martelli

    (ISAE - Institute for Studies and Economic Analyses)

Abstract

As far as data on personal income are highly confidential and sensible, it is a common practice to collect such information by asking people to classify their own earnings along a discrete scale of income “brackets”. This procedure provides an unbiased estimation of average income, under fairly general conditions, but it is well known that standard error of estimates increases with brackets size. On the other hand, people tend to underreport income, and this bias is likely to increase as brackets width gets smaller. Thus, an optimal bracket size can be generally identified, that insures a reduction of underreporting without increasing estimate variance too much. The paper presents an evaluation of brackets size effect on various procedures for estimating Italian households’ income. The first result is that the most reliable and robust procedures are those based on the extrapolation of income distribution in the upper open class by means of very simple functions. Secondly, reducing of the number of income brackets from the actual 22 to 5-7 seems to improve the accuracy of indicators for every procedure.

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Bibliographic Info

Paper provided by ISTAT - Italian National Institute of Statistics - (Rome, ITALY) in its series ISAE Working Papers with number 35.

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Length: 36 pages
Date of creation: Apr 2003
Date of revision:
Handle: RePEc:isa:wpaper:35

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Related research

Keywords: Accuracy; Bracketing; Coarse data; Households’ income; Quantification;

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References

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  1. Kakwani, Nanak C, 1976. "On the Estimation of Income Inequality Measures from Grouped Observations," Review of Economic Studies, Wiley Blackwell, vol. 43(3), pages 483-92, October.
  2. Cowell, Frank A & Mehta, Fatemeh, 1982. "The Estimation and Interpolation of Inequality Measures," Review of Economic Studies, Wiley Blackwell, vol. 49(2), pages 273-90, April.
  3. D'Elia, Enrico, 1991. "La quantificazione dei risultati dei sondaggi congiunturali: un confronto tra procedure
    [Quantifying the results of tendency surveys: a comparison among different procedures]
    ," MPRA Paper 16434, University Library of Munich, Germany.
  4. Winter, Joachim, 0000. "Bracketing effects in categorized survey questions and the measurement of economic quantities," Sonderforschungsbereich 504 Publications 02-35, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.
  5. Martelli, Bianca Maria, 1998. "Le Inchieste Congiunturali dell'ISCO: aspetti metodologici; Chapter 1 of: Le inchieste dell'ISCO come strumento di analisi della congiuntura economica
    [The ISCO short term surveys: methodological a
    ," MPRA Paper 16331, University Library of Munich, Germany.
  6. Torelli, Nicola & Trivellato, Ugo, 1993. "Modelling inaccuracies in job-search duration data," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 187-211, September.
  7. F. Thomas Juster & James P. Smith, 2004. "Improving the Quality of Economic Data: Lessons from the HRS and AHEAD," Labor and Demography 0402010, EconWPA.
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Cited by:
  1. D'Elia, Enrico, 2009. "The first qualitative survey on Albanian firms: preliminary results," MPRA Paper 36019, University Library of Munich, Germany.

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