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Statistical Inference for Measures of Inequality With a Cross-National Bootstrap Application

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  • Timothy Patrick Moran

    (State University of New York—Stony Brook)

Abstract

The problem of statistical inference in inequality research has persisted despite the solutions long suggested by asymptotic theory. This article provides a thorough analysis of the theoretical and practical aspects of conducting statistical inference in the context of inequality data. Using the income surveys of the Luxembourg Income Study, the article outlines in detail the new bootstrap procedures, assesses their performance, and demonstrates their effectiveness in evaluating levels and trends in cross-national inequality. It provides an analytical evaluation of current advancements in inequality measurement and for the first time applies these methods in the context of comparative research, but it also can be used as practical guide for handling the problems of statistical inference in more general social scientific settings.

Suggested Citation

  • Timothy Patrick Moran, 2006. "Statistical Inference for Measures of Inequality With a Cross-National Bootstrap Application," Sociological Methods & Research, , vol. 34(3), pages 296-333, February.
    • Handle: RePEc:sae:somere:v:34:y:2006:i:3:p:296-333
    DOI: 10.1177/0049124105283117
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    Cited by:

    1. David Jesuit, 2008. "Subnational Analyses Using the Luxembourg Income Study (LIS) Data Archive," LIS Working papers 494, LIS Cross-National Data Center in Luxembourg.
    2. Shawn F. Dorius, 2008. "Global Demographic Convergence? A Reconsideration of Changing Intercountry Inequality in Fertility," Population and Development Review, The Population Council, Inc., vol. 34(3), pages 519-537, September.

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