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Measurement Error and Poverty Rates of Widows

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  • Kathleen McGarry
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    Abstract

    Estimates of the poverty rate and of the probability of entering or exiting poverty are biased when income is observed with error. I estimate a variance components model of income which contains a white noise error term and then treat this component as an approximation of the error in observed income. By comparing poverty rates calculated with and without this estimated measurement error, I conclude that observation error causes the poverty rate to be overestimated around two percentage points on average. However, eliminating observation error substantially reduces the probability of transiting either into or out of poverty. These reductions imply that the amount of permanent poverty is underestimated when measurement error is ignored.

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    Bibliographic Info

    Article provided by University of Wisconsin Press in its journal Journal of Human Resources.

    Volume (Year): 30 (1995)
    Issue (Month): 1 ()
    Pages: 113-134

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    Handle: RePEc:uwp:jhriss:v:30:y:1995:i:1:p:113-134

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    Web page: http://jhr.uwpress.org/

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    Cited by:
    1. Nayoung Lee & Geert Ridder & John Strauss, 2010. "Estimation of Poverty Transition Matrices with Noisy Data," Textos para discussão 576, Department of Economics PUC-Rio (Brazil).
    2. Namkee Ahn, . "Economic Consequences of Widowhood in Europe: Cross-country and Gender Differences," Working Papers 2004-27, FEDEA.
    3. Cooper, D. & McCausland, W.D. & Theodossiou, I., 2006. "The health hazards of unemployment and poor education: The socioeconomic determinants of health duration in the European Union," Economics & Human Biology, Elsevier, vol. 4(3), pages 273-297, December.
    4. David R. Weir & Robert J. Willis & Purvi A. Sevak, 2002. "The Economic Consequences of Widowhood," Working Papers wp023, University of Michigan, Michigan Retirement Research Center.

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