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Robust Inferences from Random Clustered Samples: Applications Using Data from the Panel Survey of Income Dynamics

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  • John Pepper

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Abstract

Many large data sets are created using clustered, rather than random sampling schemes. Clustered data arise when multiple observations exist on the same respondent, as in panel data, and when respondents share a common factor, such as a neighborhood or family. In the presence of clustered data, methods that rely on random sampling to measure the precision of an estimator may be incorrect. Many researchers, however, continue to treat respondents from the same sampling cluster as independent observations and thus implicitly ignore the potential intracluster correlation. In this paper, I use a robust method for drawing inferences and data from the Panel Survey of Income Dynamics, to examine the implications of clustered samples on inference. Consistent with the previous survey sampling literature, important differences are revealed in comparisons between the estimated asymptotic variances derived assuming random and clustered sampling, even when there are only a few observations per cluster. The estimates derived under random sampling are generally biased downward.

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File URL: http://www.virginia.edu/economics/RePEc/vir/virpap/papers/virpap348.pdf
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Bibliographic Info

Paper provided by University of Virginia, Department of Economics in its series Virginia Economics Online Papers with number 348.

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Length: 14 pages
Date of creation: Jun 2006
Date of revision:
Handle: RePEc:vir:virpap:348

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Web page: http://www.virginia.edu/economics/home.html

Related research

Keywords: Clustered Samples; Design Effects; PSID;

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  1. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
  2. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-38, May.
  3. Solon, Gary, 1992. "Intergenerational Income Mobility in the United States," American Economic Review, American Economic Association, American Economic Association, vol. 82(3), pages 393-408, June.
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