{"title":"The Determinants of Redistribution Around the World","authors":"M. Jäntti, Jukka Pirttilä, Risto Rönkkö","doi":"10.1111/roiw.12406","DOIUrl":null,"url":null,"abstract":"This paper reexamines the determinants of redistribution in light of improved data and methods relative to earlier literature. In particular, we use the latest version of the UNU‐WIDER’s Income Inequality Database to have the best available estimates of both pre‐ and post‐redistribution inequality for the largest set of countries and periods. We tackle head‐on problems related to model specification that risk generating large biases in estimates because of mechanical associations between the dependent and explanatory variables. The results suggest that the bias in the earlier work can be substantial. The descriptive analysis highlights, in addition, how scarce the data are when it comes to information about the extent of redistribution in developing countries.","PeriodicalId":11465,"journal":{"name":"Econometrics: Econometric & Statistical Methods - General eJournal","volume":"47 2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Econometric & Statistical Methods - General eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/roiw.12406","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
This paper reexamines the determinants of redistribution in light of improved data and methods relative to earlier literature. In particular, we use the latest version of the UNU‐WIDER’s Income Inequality Database to have the best available estimates of both pre‐ and post‐redistribution inequality for the largest set of countries and periods. We tackle head‐on problems related to model specification that risk generating large biases in estimates because of mechanical associations between the dependent and explanatory variables. The results suggest that the bias in the earlier work can be substantial. The descriptive analysis highlights, in addition, how scarce the data are when it comes to information about the extent of redistribution in developing countries.
本文在改进的数据和方法相对于早期文献的光重新审视再分配的决定因素。特别是,我们使用最新版本的联合国大学(unu) wider收入不平等数据库(UNU‐WIDER’s Income Inequality Database),以获得对两方面的最佳估计。以及大多数国家和时期的再分配不平等。我们解决与模型规范相关的问题,由于因变量和解释变量之间的机械关联,这些问题可能会在估计中产生很大的偏差。结果表明,早期工作中的偏差可能是实质性的。此外,描述性分析还突出表明,关于发展中国家再分配程度的信息数据是多么匮乏。