On Zipf’s law and the bias of Zipf regressions - Aix-Marseille Université Accéder directement au contenu
Article Dans Une Revue Empirical Economics Année : 2021

On Zipf’s law and the bias of Zipf regressions

Résumé

City size distributions are not strictly Pareto, but upper tails are rather Pareto like (i.e. tails are regularly varying). We examine the properties of the tail exponent estimator obtained from ordinary least squares (OLS) rank size regressions (Zipf regressions for short), the most popular empirical strategy among urban economists. The estimator is then biased towards Zipf’s law in the leading class of distributions. The Pareto quantile–quantile plot is shown to offer a simple diagnostic device to detect such distortions and should be used in conjunction with the regression residuals to select the anchor point of the OLS regression in a data-dependent manner. Applying these updated methods to some well-known data sets for the largest cities, Zipf’s law is now rejected in several cases.
Fichier principal
Vignette du fichier
s00181-020-01879-3.pdf (2.35 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02880544 , version 1 (26-06-2020)

Licence

Paternité

Identifiants

Citer

Christian Schluter. On Zipf’s law and the bias of Zipf regressions. Empirical Economics, 2021, 61 (2), pp.529-548. ⟨10.1007/s00181-020-01879-3⟩. ⟨hal-02880544⟩
89 Consultations
181 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More