Abstract
We propose Fieller-type methods for inference on generalized entropy inequality indices in the context of the two-sample problem which covers testing the statistical significance of the difference in indices, and the construction of a confidence set for this difference. In addition to irregularities arising from thick distributional tails, standard inference procedures are prone to identification problems because of the ratio transformation that defines the considered indices. Simulation results show that our proposed method outperforms existing counterparts including simulation-based permutation methods and results are robust to different assumptions about the shape of the null distributions. Improvements are most notable for indices that put more weight on the right tail of the distribution and for sample sizes that match macroeconomic type inequality analysis. While irregularities arising from the right tail have long been documented, we find that left tail irregularities are equally important in explaining the failure of standard inference methods. We apply our proposed method to analyze income per-capita inequality across U.S. states and non-OECD countries. Empirical results illustrate how Fieller-based confidence sets can: (i) differ consequentially from available ones leading to conflicts in test decisions, and (ii) reveal prohibitive estimation uncertainty in the form of unbounded outcomes which serve as proper warning against flawed interpretations of statistical tests.
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The data that support the findings of this study are available from the corresponding author upon request.
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Funding
This work was supported by the William Dow Chair of Political Economy (McGill University), the Bank of Canada (Research Fellowship), the Toulouse School of Economics (Pierre-de-Fermat Chair of excellence), the Universitad Carlos III de Madrid (Banco Santander de Madrid Chair of excellence), the Natural Sciences and Engineering Research Council of Canada, the Social Sciences and Humanities Research Council of Canada, the Fonds de recherche sur la société et la culture (Québec), and by the French government under the “France 2030” investment plan managed by the French National Research Agency (reference: ANR-17-EURE-0020, ANR-17-CE41-0007, ANR-19-FRAL-0006) and from Excellence Initiative of Aix-Marseille University - A*MIDEX.
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Dufour, JM., Flachaire, E., Khalaf, L. et al. Identification-robust methods for comparing inequality with an application to regional disparities. J Econ Inequal (2024). https://doi.org/10.1007/s10888-023-09600-x
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DOI: https://doi.org/10.1007/s10888-023-09600-x