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Project Citation: 

Levy, Moshe. Replication data for: Gibrat’s Law for (All) Cities: Comment. Nashville, TN: American Economic Association [publisher], 2009. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E113328V1

Project Description

Summary:  View help for Summary Jan Eeckhout (2004) reports that the empirical city size distribution is lognormal, consistent with Gibrat's Law. We show that for the top 0.6 percent of the largest cities, the empirical distribution is dramatically different from the lognormal, and follows a power law. This top part is extremely important as it accounts for more than 23 percent of the population. The empirical hybrid lognormal-power-law distribution revealed may be characteristic of other key distributions, such as the wealth distribution and the income distribution. This distribution is not consistent with a simple Gibrat proportionate effect process, and its origin presents a puzzle yet to be answered. (JEL R11, R12, R23)

Scope of Project

Subject Terms:  View help for Subject Terms city size
JEL Classification:  View help for JEL Classification
      R11 Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
      R12 Size and Spatial Distributions of Regional Economic Activity
      R23 Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
Geographic Coverage:  View help for Geographic Coverage United States
Time Period(s):  View help for Time Period(s) 2000 – 2000 (census data)
Universe:  View help for Universe all US cities
Data Type(s):  View help for Data Type(s) survey data; administrative records data; observational data

Methodology

Data Source:  View help for Data Source U.S. 2000 Census
Unit(s) of Observation:  View help for Unit(s) of Observation population,

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