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Asymptotic normality of non-parametric estimator for the FGT poverty index via adaptive kernel. (English. French summary) Zbl 1441.62597

Summary: In this paper, we study the kernel estimator of the measurement class of J. Foster et al. [Econometrica 52, 761–766 (1984; Zbl 0555.90029)] to establish the asymptotic normality of the kernel estimator of the FGT poverty index by the adaptive method for the values of \(\alpha = 0\) and \(\alpha \geq 1\). We then provide a performance study of this estimator, on simulated data, compared to the estimator from the non-adaptive kernel and the empirical estimator. The study shows that an adaptive kernel estimator is recommended.

MSC:

62P20 Applications of statistics to economics
62G07 Density estimation
62E20 Asymptotic distribution theory in statistics
91B82 Statistical methods; economic indices and measures

Citations:

Zbl 0555.90029
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References:

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