We study US city size distribution using places data from the Census, without size restrictions, for the period 1900-2010, and the recently constructed US City Clustering Algorithm (CCA) data for 1991 and 2000. We compare the lognormal, two distributions named after Ioannides and Skouras (2013)...

The aim of this work is to test empirically the validity of Gibrat's Law in the growth of cities, using data for all the twentieth century of the complete distribution of cities (without any size restrictions) in three countries: the US, Spain and Italy. For this we use different techniques...

This paper analyses in detail the features offered by three distributions used in urban economics to describe city size distributions: lognormal, q-exponential and double Pareto lognormal, and another one of use in other areas of economics: the log-logistic. We use a large database which covers...