Gibrat's Law for (All) Cities: Comment
By Moshe Levy. 2009
178 citations recorded by the source corpus.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/baba80374175703880599d641bc868c3815415c3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Rafael González‐Val
- F. Sanz-Gracia
- Adam Okulicz-Kozaryn
- María Vera-Cabello
- Marco Bee
- Massimo Riccaboni
- Jens Südekum
- Arturo Ramos
Citations in the corpus
- The Area and Population of Cities: New Insights from a Different Perspective on Cities (2010, unknown): “The analysis of 25,359 places in the USA has suggested that Zipf’s law holds in the upper tail (Levy 2009) but fails in the bulk of the distribution, as legally defined cities follow a log-normal distribution rather than a powerlaw (Eeckhout 2004, 2009).”
- Gibrat's Law for (All) Cities: Reply (2009, unknown): “Since for large R the scale "glues" the data to the predicted distribution as well as the bands, Levy (2009) concludes that the "lognormal fits extremely well."”
- The city size distribution debate: Resolution for US urban regions and megalopolitan areas (2012, methodology): “…(Córdoba, 2008b; Cuberes, 2009, 2011; Eeckhout, 2004, 2009; González-Val et al., 2010; Ioannides and Overman, 2004; Ioannides and Skouras, 2009; Levy, 2009); whether Zipf’s rule is best captured by a Pareto or a lognormal distribution, and the proper testing procedure for distinguishing them…”
- The size distribution of US cities: Not Pareto, even in the tail (2013, methodology): “This prediction finds empirical support both in Gabaix (1999) and more recently in Rozenfeld et al. (2011); on the other hand, Eeckhout (2004) finds that the value of the shape parameter changes significantly at different cutoffs, inferring from this that the distribution cannot be truly a power-law”
- Size distributions for all cities: Which one is best? (2013, background): “2 In an important paper regarding city size distributions, Eeckhout (2004) essentially proposes three ideas: (1) that when all cities are taken, without any size restriction, Pareto’s distribution breaks down and the best representation of the data is a lognormal function; (2) as a theoretical resul”
- Urbanization and Structural Transformation (2008, unknown): “Neither paper examines the relationship between structural transformation and urbanization an analysis for which our newly-constructed 10See also Eeckhout (2008) and Levy (2008).”
- City Age and City Size (2014, background): “The debate between Levy (2009) and Eeckhout (2009) may thus also be settled by our finding that the sizes of Census places are better approximated by a DPLN distribution.”