IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/51256.html
   My bibliography  Save this paper

The use of accuracy indicators to correct for survey measurement error

Author

Listed:
  • Da Silva, Damião Nóbrega
  • Skinner, Chris J.

Abstract

An accuracy indicator is an observed variable which is related to the size of measurement error. Basic and extended models are introduced to represent the properties of a binary accuracy indicator. Under specified assumptions, it is shown that an accuracy indicator can identify a measurement error model. An approach to estimating a distribution function is presented together with methodology for variance estimation. The approach is applied to data on earnings from the British Household Panel Survey, where the accuracy indicator is whether or not a payslip is observed. A validation study provides justification for the modelling assumptions

Suggested Citation

  • Da Silva, Damião Nóbrega & Skinner, Chris J., 2014. "The use of accuracy indicators to correct for survey measurement error," LSE Research Online Documents on Economics 51256, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:51256
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/51256/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Da Silva, Damião Nóbrega & Skinner, Chris J. & Kim, Jae Kwang, 2016. "Using binary paradata to correct for measurement error in survey data analysis," LSE Research Online Documents on Economics 64763, London School of Economics and Political Science, LSE Library.

    More about this item

    Keywords

    accuracy indicator; finite population distribution function; measurement error; pseudo-maximum-likelihood;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    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:ehl:lserod:51256. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.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.