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Combining Panel Data Sets with Attrition and Refreshment Samples

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Author Info

  • Keisuke Hirano

    (Harvard University)

  • Guido W. Imbens

    (UCLA)

  • Geert Ridder

    ()
    (Vrije Universiteit Amsterdam)

  • Donald B. Rubin

    (Harvard University)

Abstract

With panel data important issues can be resolved that can not beaddressed with cross--sectional data. A major drawback is that paneldata suffer from more severe missing data problems. Adding a sampleconsisting of new units randomly drawn from the original populationas replacements for units who have dropped out of the panel, aso--called refreshment sample, can be helpful in mitigating theeffects of attrition, both by allowing for estimation of richermodels and by making estimation of conventional models moreprecise. In this paper we develop a family of models thatincorporate refreshment samples, and we demonstrate in an applicationto a Dutch data set on travel behaviour that such models can lead tosubstantially different results than models that assume that themissing data process is ignorable or conventional econometric modelsfor panel data with attrition.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 98-033/4.

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Date of creation: 23 Mar 1998
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Handle: RePEc:dgr:uvatin:19980033

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Web page: http://www.tinbergen.nl

Related research

Keywords: panel data; missing data; attrition.;

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References

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  1. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  2. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of income Dynamics," Economics Working Paper Archive 379, The Johns Hopkins University,Department of Economics.
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  11. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," University of California Transportation Center, Working Papers qt3gb0k9b5, University of California Transportation Center.
  12. Manski, C.F., 1992. "Identification Problems in the Social Sciences," Working papers 9217, Wisconsin Madison - Social Systems.
  13. Brownstone, David & Valletta, Robert G, 1996. "Modeling Earnings Measurement Error: A Multiple Imputation Approach," The Review of Economics and Statistics, MIT Press, vol. 78(4), pages 705-17, November.
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  23. repec:fth:inseep:9515 is not listed on IDEAS
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