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Bootstrapping inequality measures under the null hypothesis: Is it worth the effort?

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  • Mark Trede
Abstract
This paper discusses methods of statistical inference for inequality measures, in particular the nonparametric bootstrap. Standard resampling techniques and a new method for nonparametric resampling under the null hypothesis are discussed. Monte-Carlo simulations show that some bootstrap methods outperform the commonly used normal approximation while other bootstrap methods—including those which are used in most empirical applications—are hardly any better. Copyright Springer-Verlag 2002

Suggested Citation

  • Mark Trede, 2002. "Bootstrapping inequality measures under the null hypothesis: Is it worth the effort?," Journal of Economics, Springer, vol. 77(1), pages 261-282, December.
    • Handle: RePEc:kap:jeczfn:v:77:y:2002:i:1:p:261-282
    DOI: 10.1007/BF03052507
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    References listed on IDEAS

    as
    1. Heinrich, Georges, 1998. "Ageing Gracefully? A Bootstrap Analysis of Poverty Among Pensioners Using Evidence from the PACO Databases," CEPR Discussion Papers 2039, C.E.P.R. Discussion Papers.
    2. Schluter, Christian, 1998. "Statistical inference with mobility indices," Economics Letters, Elsevier, vol. 59(2), pages 157-162, May.
    3. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, vol. 15(3), pages 361-376, June.
    4. Mills, Jeffrey A & Zandvakili, Sourushe, 1997. "Statistical Inference via Bootstrapping for Measures of Inequality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 133-150, March-Apr.
    5. Biewen, Martin, 2002. "Bootstrap inference for inequality, mobility and poverty measurement," Journal of Econometrics, Elsevier, vol. 108(2), pages 317-342, June.
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    Cited by:

    1. Tim Goedemé, 2013. "How much Confidence can we have in EU-SILC? Complex Sample Designs and the Standard Error of the Europe 2020 Poverty Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(1), pages 89-110, January.
    2. Biewen, Martin, 2002. "Bootstrap inference for inequality, mobility and poverty measurement," Journal of Econometrics, Elsevier, vol. 108(2), pages 317-342, June.
    3. Trauten, Andreas & Schulz, Roland C., 2006. "IPO investment strategies and pseudo market timing," Working Papers 36, University of Münster, Competence Center Internet Economy and Hybrid Systems, European Research Center for Information Systems (ERCIS).
    4. 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.
    5. Zeisberger, Stefan & Langer, Thomas & Trede, Mark, 2007. "A note on myopic loss aversion and the equity premium puzzle," Finance Research Letters, Elsevier, vol. 4(2), pages 127-136, June.
    6. Timothy Moran, 2005. "Bootstrapping the LIS: Statistical Inference and Patterns of Inequality in the Global North," LIS Working papers 378, LIS Cross-National Data Center in Luxembourg.

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    More about this item

    Keywords

    Statistical Inference; Resampling; Bootstrap; C12; D31; D63;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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