IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v144y2008i2p430-446.html
   My bibliography  Save this article

Inference in panel data models under attrition caused by unobservables

Author

Listed:
  • Bhattacharya, Debopam

Abstract

This paper concerns identification and estimation of a finite-dimensional parameter in a panel data-model under nonignorable sample attrition. Attrition can depend on second period variables which are unobserved for the attritors but an independent refreshment sample from the marginal distribution of the second period values is available. This paper shows that under a quasi-separability assumption, the model implies a set of conditional moment restrictions where the moments contain the attrition function as an unknown parameter. This formulation leads to (i) a simple proof of identification under strictly weaker conditions than those in the existing literature and, more importantly, (ii) a sieve-based root-n consistent estimate of the finite-dimensional parameter of interest. These methods are applicable to both linear and nonlinear panel data models with endogenous attrition and analogous methods are applicable to situations of endogenously missing data in a single cross-section. The theory is illustrated with a simulation exercise, using Current Population Survey data where a panel structure is introduced by the rotation group feature of the sampling process.

Suggested Citation

  • Bhattacharya, Debopam, 2008. "Inference in panel data models under attrition caused by unobservables," Journal of Econometrics, Elsevier, vol. 144(2), pages 430-446, June.
  • Handle: RePEc:eee:econom:v:144:y:2008:i:2:p:430-446
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(08)00038-9
    Download Restriction: Full text for ScienceDirect subscribers only

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

    References listed on IDEAS

    as
    1. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-473, March.
    2. Nevo, Aviv, 2003. "Using Weights to Adjust for Sample Selection When Auxiliary Information Is Available," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 43-52, January.
    3. 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.
    4. Ridder, Geert, 1992. "An empirical evaluation of some models for non-random attrition in panel data," Structural Change and Economic Dynamics, Elsevier, vol. 3(2), pages 337-355, December.
    5. Nijman, T.E. & Verbeek, M.J.C.M., 1992. "Testing for selectivity in panel data models," Other publications TiSEM 7ec34a6c-1d84-4052-971c-d, Tilburg University, School of Economics and Management.
    6. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    7. Nicoletti, Cheti, 2006. "Nonresponse in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 461-489, June.
    8. Jeffrey M. Wooldridge, 2002. "Inverse probability weighted M-estimators for sample selection, attrition and stratification," CeMMAP working papers CWP11/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Chunrong Ai & Xiaohong Chen, 2003. "Efficient Estimation of Models with Conditional Moment Restrictions Containing Unknown Functions," Econometrica, Econometric Society, vol. 71(6), pages 1795-1843, November.
    10. Nevo, Aviv, 2002. "Sample selection and information-theoretic alternatives to GMM," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 149-157, March.
    11. Das, M., 2004. "Simple estimators for nonparametric panel data models with sample attrition," Journal of Econometrics, Elsevier, vol. 120(1), pages 159-180, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Xavier d'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear difference-in-differences in repeated cross sections with continuous treatments," CeMMAP working papers CWP40/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. repec:bla:jorssa:v:180:y:2017:i:2:p:503-530 is not listed on IDEAS
    3. Rene Segers & Philip Hans Franses, 2014. "Panel design effects on response rates and response quality," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 1-24, February.
    4. 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.
    5. Das, J.W.M. & van Soest, A.H.O. & Toepoel, V., 2011. "Nonparametric tests of panel conditioning and attrition bias in panel surveys," Other publications TiSEM 76b0a827-e4b6-403d-8465-a, Tilburg University, School of Economics and Management.
    6. Sasaki, Yuya, 2015. "Heterogeneity and selection in dynamic panel data," Journal of Econometrics, Elsevier, vol. 188(1), pages 236-249.
    7. Sasaki, Yuya & Xin, Yi, 2017. "Unequal spacing in dynamic panel data: Identification and estimation," Journal of Econometrics, Elsevier, vol. 196(2), pages 320-330.
    8. Seik Kim, 2013. "Wage Mobility of Foreign-Born Workers in the United States," Journal of Human Resources, University of Wisconsin Press, vol. 48(3), pages 628-658.
    9. Emre Ekinci & Insan Tunah & Berk Yavuzoglu, 2017. "Rescaled Additivity Non-Ignorable (RAN) Model of Generalized Attrition," Working Papers 1702, Nazarbayev University, Department of Economics, revised Mar 2017.
    10. Laurent Davezies & Xavier d'Haultfoeuille, 2013. "Endogenous Attrition in Panels," Working Papers 2013-17, Center for Research in Economics and Statistics.
    11. Seik Kim & Nalina Varanasi, "undated". "Labor Supply of Married Women in Credit-Constrained Households: Theory and Evidence," Working Papers UWEC-2010-01, University of Washington, Department of Economics.
    12. 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.
    13. Seik Kim, "undated". "Sample Attrition in the Presence of Population Attrition," Working Papers UWEC-2009-02, University of Washington, Department of Economics.

    More about this item

    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:eee:econom:v:144:y:2008:i:2:p:430-446. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.