{"title":"所有“城市”的规模分布:一个统一的方法","authors":"Kristian Giesen, Jens Suedekum","doi":"10.2139/ssrn.2004229","DOIUrl":null,"url":null,"abstract":"In this paper we show that the double Pareto lognormal (DPLN)\nparameterization provides an excellent fit to the overall US city size distribution, regardless\nof whether �cities� are administratively defined Census places or economically defined\narea clusters. We then consider an economic model that combines scale-independent urban\ngrowth (Gibrat�s law) with endogenous city creation. City sizes converge to a DPLN\ndistribution in this model, which is much better in line with the data than previous urban\ngrowth frameworks that predict a lognormal or a Pareto city size distribution (Zipf�s law).","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":"{\"title\":\"The Size Distribution Across All \\\"Cities\\\": A Unifying Approach\",\"authors\":\"Kristian Giesen, Jens Suedekum\",\"doi\":\"10.2139/ssrn.2004229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we show that the double Pareto lognormal (DPLN)\\nparameterization provides an excellent fit to the overall US city size distribution, regardless\\nof whether �cities� are administratively defined Census places or economically defined\\narea clusters. We then consider an economic model that combines scale-independent urban\\ngrowth (Gibrat�s law) with endogenous city creation. City sizes converge to a DPLN\\ndistribution in this model, which is much better in line with the data than previous urban\\ngrowth frameworks that predict a lognormal or a Pareto city size distribution (Zipf�s law).\",\"PeriodicalId\":410291,\"journal\":{\"name\":\"ERN: Analytical Models (Topic)\",\"volume\":\"120 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"45\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Analytical Models (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2004229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Analytical Models (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2004229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Size Distribution Across All "Cities": A Unifying Approach
In this paper we show that the double Pareto lognormal (DPLN)
parameterization provides an excellent fit to the overall US city size distribution, regardless
of whether �cities� are administratively defined Census places or economically defined
area clusters. We then consider an economic model that combines scale-independent urban
growth (Gibrat�s law) with endogenous city creation. City sizes converge to a DPLN
distribution in this model, which is much better in line with the data than previous urban
growth frameworks that predict a lognormal or a Pareto city size distribution (Zipf�s law).