{"title":"Good for the goose, bad for the gander? Corruption and income inequality","authors":"Jamie Bologna Pavlik, Justin T. Callais","doi":"10.1002/soej.12733","DOIUrl":null,"url":null,"abstract":"We examine the relationship between corruption and income inequality across countries. While previous studies have explored this association at both an international and within‐country level, we expand on this literature in two distinct ways. First, along with the most commonly utilized measure of inequality (Gini coefficients), we also examine income per‐capita at each decile, along with top 1% and 5%, and the associated income shares. Second, we employ an empirical strategy that differs from the existing literature. Our primary results are estimated using matching methods, but we also supplement these results with a “doubly robust” difference‐in‐difference design. We find that a reduction in corruption increases incomes of the top 80% but does not significantly impact incomes of the bottom 20%, or the top 1% and 5%. We find some evidence of income growth amongst the top 1% and 5% following increases in corruption, but these results are inconsistent across estimations. Our results also suggest that accounting for the size of the informal sector matters a great deal in understanding the relationship between corruption and the distribution of income.","PeriodicalId":47946,"journal":{"name":"Southern Economic Journal","volume":"14 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Southern Economic Journal","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1002/soej.12733","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
We examine the relationship between corruption and income inequality across countries. While previous studies have explored this association at both an international and within‐country level, we expand on this literature in two distinct ways. First, along with the most commonly utilized measure of inequality (Gini coefficients), we also examine income per‐capita at each decile, along with top 1% and 5%, and the associated income shares. Second, we employ an empirical strategy that differs from the existing literature. Our primary results are estimated using matching methods, but we also supplement these results with a “doubly robust” difference‐in‐difference design. We find that a reduction in corruption increases incomes of the top 80% but does not significantly impact incomes of the bottom 20%, or the top 1% and 5%. We find some evidence of income growth amongst the top 1% and 5% following increases in corruption, but these results are inconsistent across estimations. Our results also suggest that accounting for the size of the informal sector matters a great deal in understanding the relationship between corruption and the distribution of income.