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On Statistical Inference for Inequality Measures Calculated from Complex Survey Data

We examine inference for Generalized Entropy and Atkinson inequality measures with complex survey data, using Wald statistics with variance-covariance matrices estimated from a linearization approximation rather than the d-method. Testing the equivalence of two or more inequality measures, including sub-group decomposition indices and group shares, are covered. We illustrate with Indian data from three surveys, examining children’s height-for-age, an anthropometric measure that can indicate long-term malnutrition. Sampling involved an urban/rural stratification with clustering before selection of households. We compare the linearization complex survey outcomes with those from an incorrect iid assumption and a bootstrap that accounts for the survey design. For our samples, the results from the easy to implement linearization method and more computationally burdensome bootstrap are in close agreement.

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Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0904.

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Length: 38 pages
Date of creation: 15 Jun 2009
Date of revision:
Handle: RePEc:vic:vicewp:0904
Note: ISSN 1485-6441
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Web page: http://web.uvic.ca/econ

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