IDEAS home Printed from
   My bibliography  Save this paper

Rescaled Additively Non-ignorable (RAN) Model of Attrition and Substitution


  • Insan Tunali

    () (Department of Economics, Koç University)

  • Emre Ekinci

    () (Department of Business Administration, Universidad Carlos III de Madrid)

  • Berk Yavuzoglu

    () (Department of Economics, University of Wisconsin-Madison)


We modify the Additively Non-ignorable (AN) model of Hirano et. al. (2001) so that it is suitable for data collection efforts that have a short panel component. Our modification yields a convenient semi-parametric bias correction framework for handling endogenous attrition and substitution behavior that can emerge when multiple visits to the same unit are planned. We apply our methodology to data from the Household Labor Force Survey (HLFS) in Turkey, which shares a key design feature (namely a rotating sample frame) of popular surveys such as the Current Population Survey and the European Union Labor Force Survey. The correction amounts to adjusting the observed joint distribution over the state space using reflation factors expressed as parametric functions of the states occupied in subsequent rounds. Unlike standard weighting schemes, our method produces a unique set of corrected joint probabilities that are consistent with the margins used for computing the published cross-section statistics. Inference about the nature of the bias is implemented via Bootstrap methods. Our empirical results show that attrition/substitution in HLFS is a statistically and substantially important concern.

Suggested Citation

  • Insan Tunali & Emre Ekinci & Berk Yavuzoglu, 2012. "Rescaled Additively Non-ignorable (RAN) Model of Attrition and Substitution," Koç University-TUSIAD Economic Research Forum Working Papers 1220, Koc University-TUSIAD Economic Research Forum.
  • Handle: RePEc:koc:wpaper:1220

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Bhattacharya, Debopam, 2008. "Inference in panel data models under attrition caused by unobservables," Journal of Econometrics, Elsevier, vol. 144(2), pages 430-446, June.
    2. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 2001. "Combining Panel Data Sets with Attrition and Refreshment Samples," Econometrica, Econometric Society, vol. 69(6), pages 1645-1659, November.
    3. Abowd, John M & Zellner, Arnold, 1985. "Estimating Gross Labor-Force Flows," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 254-283, June.
    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.

    Cited by:

    1. Heng Chen & Marie-Hélène Felt & Kim Huynh, 2014. "Retail Payment Innovations and Cash Usage: Accounting for Attrition Using Refreshment Samples," Staff Working Papers 14-27, Bank of Canada.

    More about this item


    attrition; substitution; selectivity; short panel; rotating sample frame; labor force survey.;

    NEP fields

    This paper has been announced in the following NEP Reports:


    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:koc:wpaper:1220. 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: (Sumru Oz). 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.

    If CitEc recognized a reference but did not link an item in RePEc 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 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.