Top Incomes, Heavy Tails, and Rank-Size Regressions

Christian Schluter (1, 2)

1 GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille
2 AMSE - Aix-Marseille Sciences Economiques

In economics, rank-size regressions provide popular estimators of tail exponents of heavy-tailed distributions. We discuss the properties of this approach when the tail of the distribution is regularly varying rather than strictly Pareto. The estimator then over-estimates the true value in the leading parametric income models (so the upper income tail is less heavy than estimated), which leads to test size distortions and undermines inference. For practical work, we propose a sensitivity analysis based on regression diagnostics in order to assess the likely impact of the distortion. The methods are illustrated using data on top incomes in the UK.

Mots clés: top incomes; heavy tails; rank size regression; extreme value index; regular variation

Domaines: Economies et finances

Christian Schluter. Top Incomes, Heavy Tails, and Rank-Size Regressions. Econometrics, 2018, 6 (1), pp.10. ⟨10.3390/econometrics6010010⟩. ⟨hal-01978497⟩