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Statistical Inference via Bootstrapping for Measures of Inequality

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Listed:
  • Jeffrey A. Mills

    (The Jerome Levy Economics)

  • Sourushe Zandvakili

    (The Jerome Levy Economics)

Abstract

In this paper we consider the use of bootstrap methods to compute interval estimates and perform hypothesis tests for decomposable measures of economic inequality. The bootstrap potentially represents a significant gain over available asymptotic intervals because it provides an easily implemented solution to the Behrens-Fisher problem. Two applications of this approach, using the PSID (for the study of taxation) and the NLSY (for the study of youth inequality), to the Gini coefficient and Theil's entropy measures of inequality, are provided. The results suggest that (i) statistical inference is essential even when large samples are available, and (ii) the bootstrap appears to perform well in this setting.

Suggested Citation

  • Jeffrey A. Mills & Sourushe Zandvakili, 1999. "Statistical Inference via Bootstrapping for Measures of Inequality," Macroeconomics 9902003, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpma:9902003
    Note: Type of Document - Acrobate PDF File; prepared on IBM PC; to print on PostScript; pages: 32; figures: included
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    References listed on IDEAS

    as
    1. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    2. Bourguignon, Francois, 1979. "Decomposable Income Inequality Measures," Econometrica, Econometric Society, vol. 47(4), pages 901-920, July.
    3. Gastwirth, Joseph L, 1974. "Large Sample Theory of Some Measures of Income Inequality," Econometrica, Econometric Society, vol. 42(1), pages 191-196, January.
    4. Cowell, Frank A., 1989. "Sampling variance and decomposable inequality measures," Journal of Econometrics, Elsevier, vol. 42(1), pages 27-41, September.
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