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Estimation and inference for quantiles and indices of inequality and poverty with survey data: leveraging built-in support for complex survey design and multiply imputed data

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  • Philippe Van Kerm

    (Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg)

Abstract

Stata is the software of choice for many analysts of household surveys, in particular for poverty and inequality analysis. No dedicated suite of command comes bundled with the software, but many user-written commands are freely available for the estimation of various types of indices. This talk will present a set of new tools which complement and significantly upgrade some existing packages. The key feature of the new packages is their ability to leverage Stata's built-in capacity for dealing with survey design features (via the svy prefix), resampling methods (via the bootstrap, jackknife or permute prefixes), multiply imputed data (via mi) and various post-estimation commands for testing purposes. The talk will review basic indices, outline estimation and inference for such non-linear statistics with survey data, show programming tips, and illustrate various uses of the new commands.

Suggested Citation

  • Philippe Van Kerm, 2017. "Estimation and inference for quantiles and indices of inequality and poverty with survey data: leveraging built-in support for complex survey design and multiply imputed data," United Kingdom Stata Users' Group Meetings 2017 12, Stata Users Group.
    • Handle: RePEc:boc:usug17:12
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    Cited by:

    1. Doorley, Karina & Privalko, Ivan & Russell, Helen & Tuda, Dora, 2021. "The Gender Pay Gap in Ireland from Austerity through Recovery," IZA Discussion Papers 14441, Institute of Labor Economics (IZA).

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