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Evaluation Of Variance Estimators For The Concentration And Health Achievement Indices: A Monte Carlo Simulation

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  • Zhuo Chen
  • Kakoli Roy
  • Carol A. Gotway Crawford

Abstract

Although the concentration index (CI) and the health achievement index (HAI) have been extensively used, previous studies have relied on bootstrapping to compute the variance of the HAI, whereas competing variance estimators exist for the CI. This paper provides methods of statistical inference for the HAI and compares the available variance estimators for both the CI and the HAI using Monte Carlo simulation. Results for both the CI and the HAI suggest that analytical methods and bootstrapping are well behaved. The convenient regression method gives standard errors close to the other methods, provided the CI is not too large ( 0.1. Published 2011. This article is a US Government work and is in the public domain in the USA.

Suggested Citation

  • Zhuo Chen & Kakoli Roy & Carol A. Gotway Crawford, 2012. "Evaluation Of Variance Estimators For The Concentration And Health Achievement Indices: A Monte Carlo Simulation," Health Economics, John Wiley & Sons, Ltd., vol. 21(11), pages 1375-1381, November.
    • Handle: RePEc:wly:hlthec:v:21:y:2012:i:11:p:1375-1381
    DOI: 10.1002/hec.1796
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    References listed on IDEAS

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    1. ERREYGERS, Guido & CLARKE, Philip & VAN OURTI, Tom, 2010. "Mirror, mirror, on the wall, who in this land is fairest of all? Revisiting the extended concentration index," Working Papers 2010015, University of Antwerp, Faculty of Business and Economics.
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    4. Owen O'Donnell & Eddy van Doorslaer & Adam Wagstaff & Magnus Lindelow, 2008. "Analyzing Health Equity Using Household Survey Data : A Guide to Techniques and Their Implementation," World Bank Publications - Books, The World Bank Group, number 6896.
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    7. 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.
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