IDEAS home Printed from
   My bibliography  Save this article

Responsive design for household surveys: tools for actively controlling survey errors and costs


  • Robert M. Groves
  • Steven G. Heeringa


Over the past few years surveys have expanded to new populations, have incorporated measurement of new and more complex substantive issues and have adopted new data collection tools. At the same time there has been a growing reluctance among many household populations to participate in surveys. These factors have combined to present survey designers and survey researchers with increased uncertainty about the performance of any given survey design at any particular point in time. This uncertainty has, in turn, challenged the survey practitioner's ability to control the cost of data collection and quality of resulting statistics. The development of computer-assisted methods for data collection has provided survey researchers with tools to capture a variety of process data ('paradata') that can be used to inform cost-quality trade-off decisions in realtime. The ability to monitor continually the streams of process data and survey data creates the opportunity to alter the design during the course of data collection to improve survey cost efficiency and to achieve more precise, less biased estimates. We label such surveys as 'responsive designs'. The paper defines responsive design and uses examples to illustrate the responsive use of paradata to guide mid-survey decisions affecting the non-response, measurement and sampling variance properties of resulting statistics. Copyright 2006 Royal Statistical Society.

Suggested Citation

  • Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457.
  • Handle: RePEc:bla:jorssa:v:169:y:2006:i:3:p:439-457

    Download full text from publisher

    File URL:
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Szymanski, Stefan, 2001. "Income Inequality, Competitive Balance and the Attractiveness of Team Sports: Some Evidence and a Natural Experiment from English Soccer," Economic Journal, Royal Economic Society, vol. 111(469), pages 69-84, February.
    2. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
    3. Paapaa, Richard & van Dijk, Herman K., 1998. "Distribution and mobility of wealth of nations," European Economic Review, Elsevier, vol. 42(7), pages 1269-1293, July.
    4. Durlauf, Steven N. & Quah, Danny T., 1999. "The new empirics of economic growth," Handbook of Macroeconomics,in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 4, pages 235-308 Elsevier.
    5. Quah, Danny, 1993. "Empirical cross-section dynamics in economic growth," European Economic Review, Elsevier, vol. 37(2-3), pages 426-434, April.
    6. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    7. Simon Rottenberg, 1956. "The Baseball Players' Labor Market," Journal of Political Economy, University of Chicago Press, vol. 64, pages 242-242.
    8. Nobile, Agostino, 2000. "Comment: Bayesian multinomial probit models with a normalization constraint," Journal of Econometrics, Elsevier, vol. 99(2), pages 335-345, December.
    9. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    10. Vrooman, John, 2000. "The Economics of American Sports Leagues," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(4), pages 364-398, September.
    11. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
    12. John F. Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
    13. Lahiri, Kajal & Gao, Jian, 2002. "Bayesian analysis of nested logit model by Markov chain Monte Carlo," Journal of Econometrics, Elsevier, vol. 111(1), pages 103-133, November.
    14. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    15. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, January.
    16. Quah, Danny T., 1996. "Empirics for economic growth and convergence," European Economic Review, Elsevier, vol. 40(6), pages 1353-1375, June.
    17. Flynn, Michael A & Gilbert, Richard J, 2001. "The Analysis of Professional Sports Leagues as Joint Ventures," Economic Journal, Royal Economic Society, vol. 111(469), pages 27-46, February.
    18. Koop, Gary & Poirier, Dale J., 1993. "Bayesian analysis of logit models using natural conjugate priors," Journal of Econometrics, Elsevier, vol. 56(3), pages 323-340, April.
    19. McCulloch, Robert E. & Rossi, Peter E., 2000. "Reply to Nobile," Journal of Econometrics, Elsevier, vol. 99(2), pages 347-348, December.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Access and download statistics


    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:bla:jorssa:v:169:y:2006:i:3:p:439-457. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.