Thiago Trafane Oliveira SantosCentral Bank of Brazil, Brasília, Brazil. Department of %Economics, University of Brasilia, Brazil, Daniel Oliveira CajueiroDepartment of Economics, University of Brasilia, Brazil. National Institute of Science and Technology for Complex Systems
{"title":"巴西企业规模分布中的齐普夫定律","authors":"Thiago Trafane Oliveira SantosCentral Bank of Brazil, Brasília, Brazil. Department of %Economics, University of Brasilia, Brazil, Daniel Oliveira CajueiroDepartment of Economics, University of Brasilia, Brazil. National Institute of Science and Technology for Complex Systems","doi":"arxiv-2409.09470","DOIUrl":null,"url":null,"abstract":"Zipf's law states that the probability of a variable being larger than $s$ is\nroughly inversely proportional to $s$. In this paper, we evaluate Zipf's law\nfor the distribution of firm size by the number of employees in Brazil. We use\npublicly available binned annual data from the Central Register of Enterprises\n(CEMPRE), which is held by the Brazilian Institute of Geography and Statistics\n(IBGE) and covers all formal organizations. Remarkably, we find that Zipf's law\nprovides a very good, although not perfect, approximation to data for each year\nbetween 1996 and 2020 at the economy-wide level and also for agriculture,\nindustry, and services alone. However, a lognormal distribution also performs\nwell and even outperforms Zipf's law in certain cases.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":"85 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Zipf's law in the distribution of Brazilian firm size\",\"authors\":\"Thiago Trafane Oliveira SantosCentral Bank of Brazil, Brasília, Brazil. Department of %Economics, University of Brasilia, Brazil, Daniel Oliveira CajueiroDepartment of Economics, University of Brasilia, Brazil. National Institute of Science and Technology for Complex Systems\",\"doi\":\"arxiv-2409.09470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Zipf's law states that the probability of a variable being larger than $s$ is\\nroughly inversely proportional to $s$. In this paper, we evaluate Zipf's law\\nfor the distribution of firm size by the number of employees in Brazil. We use\\npublicly available binned annual data from the Central Register of Enterprises\\n(CEMPRE), which is held by the Brazilian Institute of Geography and Statistics\\n(IBGE) and covers all formal organizations. Remarkably, we find that Zipf's law\\nprovides a very good, although not perfect, approximation to data for each year\\nbetween 1996 and 2020 at the economy-wide level and also for agriculture,\\nindustry, and services alone. However, a lognormal distribution also performs\\nwell and even outperforms Zipf's law in certain cases.\",\"PeriodicalId\":501172,\"journal\":{\"name\":\"arXiv - STAT - Applications\",\"volume\":\"85 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - STAT - Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.09470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.09470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Zipf's law in the distribution of Brazilian firm size
Zipf's law states that the probability of a variable being larger than $s$ is
roughly inversely proportional to $s$. In this paper, we evaluate Zipf's law
for the distribution of firm size by the number of employees in Brazil. We use
publicly available binned annual data from the Central Register of Enterprises
(CEMPRE), which is held by the Brazilian Institute of Geography and Statistics
(IBGE) and covers all formal organizations. Remarkably, we find that Zipf's law
provides a very good, although not perfect, approximation to data for each year
between 1996 and 2020 at the economy-wide level and also for agriculture,
industry, and services alone. However, a lognormal distribution also performs
well and even outperforms Zipf's law in certain cases.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
