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Theil index estimation by means of the influence function with an application to income surveys

Author

Listed:
  • Lucio Barabesi
  • Federico Crescenzi
  • Lorenzo Mori

Abstract

By assuming the design-based paradigm, an analysis of the Theil index and its estimation is carried out. First, by expressing the population Theil index as a statistical functional, we obtain its influence function and prove the corresponding properties. We also provide some new results on the influence function of the Gini index, which are suitable for a methodological comparison of the two inequality measures. Subsequently, on the basis of these findings, we introduce estimators of the Theil index and its variance. By means of a Monte Carlo study, we show that the variance estimator displays suitable performance in terms of bias and provides confidence intervals with adequate coverage. In addition, by considering such benchmarks, the suggested variance estimation outperforms the corresponding methods based on the nonparametric and parametric bootstrap. An application of our achievements is considered by using the data from the “Survey on Vulnerability to Poverty” held in 2021 in Tuscany (Italy) with the goal to map the socio-economic conditions and inequalities of households and individuals after the Covid-19 pandemic.

Suggested Citation

  • Lucio Barabesi & Federico Crescenzi & Lorenzo Mori, 2024. "Theil index estimation by means of the influence function with an application to income surveys," Department of Economics University of Siena 915, Department of Economics, University of Siena.
  • Handle: RePEc:usi:wpaper:915
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    More about this item

    Keywords

    design-based; inequality measure; influence function; variance estimation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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