IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

To misreport or not to report? The measurement of household financial wealth

Author Info

Listed author(s):
  • Andrea Neri

    ()

    (Bank of Italy)

  • Maria Giovanna Ranalli

    ()

    (Department of Economics, Finance and Statistics, University of Perugia)

Abstract

The objective of the paper is to adjust for the bias due to unit non-response and measurement error in survey estimates of total household financial wealth. Sample surveys are a useful source of information on household wealth. Yet, survey estimates are affected by non-sampling errors. In particular, in the case of household wealth, unit non-response and measurement error can severely bias the estimates. Using the Italian Survey on Household Income and Wealth (SHIW), we exploit the available auxiliary information in order to assess the magnitude of this bias. We find evidence that for this kind of survey, non-sampling errors are a major issue, possibly more serious than sampling errors. Moreover, in the case of SHIW the potential bias due to measurement error seems to outweigh that induced by non-response.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.bancaditalia.it/pubblicazioni/temi-discussione/2012/2012-0870/en_tema_870.pdf
Download Restriction: no

Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 870.

as
in new window

Length:
Date of creation: Jul 2012
Handle: RePEc:bdi:wptemi:td_870_12
Contact details of provider: Postal:
Via Nazionale, 91 - 00184 Roma

Web page: http://www.bancaditalia.it

More information through EDIRC

Keywords: unit non-response; measurement error; auxiliary information; subsampling; imputation;

Find related papers by JEL classification:

  • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
  • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
  • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, September.
  2. Claudia Biancotti & Giovanni D'Alessio & Andrea Neri, 2008. "Measurement Error In The Bank Of Italy'S Survey Of Household Income And Wealth," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 54(3), pages 466-493, 09.
  3. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, September.
  4. Giovanni D'Alessio & Ivan Faiella, 2002. "Non-response behaviour in the Bank of Italy�s Survey of Household Income and Wealth," Temi di discussione (Economic working papers) 462, Bank of Italy, Economic Research and International Relations Area.
  5. Emilia Bonaccorsi di Patti & Enrico Sette, 2012. "Bank balance sheets and the transmission of financial shocks to borrowers: evidence from the 2007-2008 crisis," Temi di discussione (Economic working papers) 848, Bank of Italy, Economic Research and International Relations Area.
  6. Leandro D�Aurizio & Ivan Faiella & Stefano Iezzi & Andrea Neri, 2006. "The under-reporting of financial wealth in the Survey on Household income and Wealth," Temi di discussione (Economic working papers) 610, Bank of Italy, Economic Research and International Relations Area.
Full references (including those not matched with items on IDEAS)

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

as
in new window


Cited by:

  1. Giovanni D'Alessio & Andrea Neri, 2015. "Income and wealth sample estimates consistent with macro aggregates: some experiments," Questioni di Economia e Finanza (Occasional Papers) 272, Bank of Italy, Economic Research and International Relations Area.
  2. Philip Vermeulen, 2016. "Estimating the Top Tail of the Wealth Distribution," American Economic Review, American Economic Association, vol. 106(5), pages 646-650, May.

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Access and download statistics

When requesting a correction, please mention this item's handle: RePEc:bdi:wptemi:td_870_12. 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: ()

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.