EconPapers    
Economics at your fingertips  
 

On the parametric description of log-growth rates of cities’ sizes of four European countries and the USA

Till Massing, Miguel Puente-Ajovin () and Arturo Ramos

Physica A: Statistical Mechanics and its Applications, 2020, vol. 551, issue C

Abstract: We have studied the parametric description of the distribution of the log-growth rates of the sizes of cities of France, Germany, Italy, Spain and the USA. We have considered several parametric distributions well known in the literature as well as some others recently introduced. There are some models that provide similar excellent performance, for all studied samples. The normal distribution is not the one observed empirically.

Keywords: Urban log-growth rate distribution; Exponential distribution; Exponential generalized beta 2 distribution; Student’s t distribution; Mixture distributions (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437120302818
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:551:y:2020:i:c:s0378437120302818

DOI: 10.1016/j.physa.2020.124587

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2021-10-06
Handle: RePEc:eee:phsmap:v:551:y:2020:i:c:s0378437120302818