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An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics

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  • John Fitzgerald
  • Peter Gottschalk
  • Robert Moffitt

Abstract

By 1989 the Michigan Panel Study on Income Dynamics (PSID) had experienced approximately 50 percent sample loss from cumulative attrition from its initial 1968 membership. We study the effect of this attrition on the unconditional distributions of several socioeconomic variables and on the estimates of several sets of regression coefficients. We provide a statistical framework for conducting tests for attrition bias that draws a sharp distinction between selection on unobservables and on observables and that shows that weighted least squares can generate consistent parameter estimates when selection is based on observables, even when they are endogenous. Our empirical analysis shows that attrition is highly selective and is concentrated among lower socioeconomic status individuals. We also show that attrition is concentrated among those with more unstable earnings, marriage, and migration histories. Nevertheless, we find that these variables explain very little of the attrition in the sample, and that the selection that occurs is moderated by regression-to-the-mean effects from selection on transitory components that fade over time. Consequently, despite the large amount of attrition, we find no strong evidence that attrition has seriously distorted the representativeness of the PSID through 1989, and considerable evidence that its cross-sectional representativeness has remained roughly intact.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0220.

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Date of creation: Feb 1998
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Publication status: published as Fitzgerald, John, Peter Gottschalk and Robert Moffitt. "The Impact Of Attrition In The Panel Study Of Income Dynamics On Intergenerational Analysis," Journal of Human Resources, 1998, v33(2,Spring), 300-344.
Handle: RePEc:nbr:nberte:0220

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  17. Colin Cameron, A. & Windmeijer, Frank A. G., 1997. "An R-squared measure of goodness of fit for some common nonlinear regression models," Journal of Econometrics, Elsevier, Elsevier, vol. 77(2), pages 329-342, April.
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