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

Patterns of Consent: Evidence from a General Household Survey

Author Info

Listed author(s):
  • Stephen P. Jenkins
  • Lorenzo Cappellari
  • Peter Lynn
  • Annette Jäckle
  • Emanuela Sala

Abstract

We analyse consent patterns and consent bias in the context of a large general household survey, the 'Improving survey measurement of income and employment' (ISMIE) survey, also addressing issues that arise when there are multiple consent questions. Using a multivariate probit regression model for four binary outcomes with two incidental truncations, we show that there are biases in consent to data linkage with benefit and tax credit administrative records held by the Department for Work and Pensions, and with wage and employment data held by employers, and also in respondents' willingness and ability to supply their National Insurance Number. The biases differ according to the question considered, however. We also show that modelling consent questions independently rather than jointly may lead to misleading inferences about consent bias. A positive correlation between unobservable individual factors affecting consent to DWP record linkage and consent to employer record linkage is suggestive of a latent individual consent propensity.

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.diw.de/documents/publikationen/73/diw_01.c.43286.de/dp490.pdf
Download Restriction: no

Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 490.

as
in new window

Length: II, 34 p.
Date of creation: 2005
Handle: RePEc:diw:diwwpp:dp490
Contact details of provider: Postal:
Mohrenstraße 58, D-10117 Berlin

Phone: xx49-30-89789-0
Fax: xx49-30-89789-200
Web page: http://www.diw.de/en
Email:


More information through EDIRC

Keywords: Informed consent; Household surveys; Consent bias; Selection bias; Multivariate probit; Incidental truncation; Data linkage; National Insurance number;

Other versions of this item:

Find related papers by JEL classification:
  • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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. Philip J. Smith & David C. Hoaglin & J. N. K. Rao & Michael P. Battaglia & Danni Daniels, 2004. "Evaluation of adjustments for partial non-response bias in the US National Immunization Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(1), pages 141-156.
  2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, July.
  3. Stewart, Mark B & Swaffield, Joanna K, 1999. "Low Pay Dynamics and Transition Probabilities," Economica, London School of Economics and Political Science, vol. 66(261), pages 23-42, February.
  4. Lynn, Peter & Jäckle, Annette & Jenkins, Stephen P. & Sala, Emanuela, 2004. "The effects of dependent interviewing on responses to questions on income sources," ISER Working Paper Series 2004-16, Institute for Social and Economic Research.
  5. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
  6. Jenkins, Stephen P. & Lynn, Peter & Jäckle, Annette & Sala, Emanuela, 2004. "Linking household survey and administrative record data: what should the matching variables be?," ISER Working Paper Series 2004-23, Institute for Social and Economic Research.
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:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

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:diw:diwwpp:dp490. 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: (Bibliothek)

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.