On Statistical Inference for Inequality Measures Calculated from Complex Survey Data
Judith A. Clarke
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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