Estimation of misreporting probability in corporate credit rating: A nonparametric approach

IF 0.5 4区 经济学 Q4 ECONOMICS
Ruichang Lu, Yao Luo, Ruli Xiao
{"title":"Estimation of misreporting probability in corporate credit rating: A nonparametric approach","authors":"Ruichang Lu,&nbsp;Yao Luo,&nbsp;Ruli Xiao","doi":"10.1002/ise3.51","DOIUrl":null,"url":null,"abstract":"<p>There has been heated debate regarding credit-rating agencies' (CRAs') reporting accuracy of corporate credit ratings, which is essential for investors because they rely on those crediting ratings to make investment decisions. We estimate the reporting accuracy using the data on corporate ratings from Standard &amp; Poor from January 1986 to December 2011. First, there is a U-shape in the overall misreporting pattern: the left-hand side (the high-rating groups) has a lower misreporting probability (3%), the middle has no misreporting, and the right-hand side has a high misreporting probability (6%). Second, we find that there is a significant difference across the industries. The financial sector has the highest misreporting probability (35% in the lowest rating group) and misreporting magnitude (rating rank jump between true rating and reported rating), and the energy industry has the lowest misreporting probability. Last, when the economic condition is good, CRAs are likelier to inflate the rating.</p>","PeriodicalId":29662,"journal":{"name":"International Studies of Economics","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ise3.51","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Studies of Economics","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ise3.51","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

There has been heated debate regarding credit-rating agencies' (CRAs') reporting accuracy of corporate credit ratings, which is essential for investors because they rely on those crediting ratings to make investment decisions. We estimate the reporting accuracy using the data on corporate ratings from Standard & Poor from January 1986 to December 2011. First, there is a U-shape in the overall misreporting pattern: the left-hand side (the high-rating groups) has a lower misreporting probability (3%), the middle has no misreporting, and the right-hand side has a high misreporting probability (6%). Second, we find that there is a significant difference across the industries. The financial sector has the highest misreporting probability (35% in the lowest rating group) and misreporting magnitude (rating rank jump between true rating and reported rating), and the energy industry has the lowest misreporting probability. Last, when the economic condition is good, CRAs are likelier to inflate the rating.

企业信用评级误报概率的非参数估计
关于信用评级机构(CRA)报告企业信用评级的准确性,一直存在激烈的争论,这对投资者来说至关重要,因为他们依赖这些信用评级来做出投资决策。我们使用Standard&;1986年1月至2011年12月期间表现不佳。首先,总体误报模式呈U型:左侧(高评级组)误报概率较低(3%),中间没有误报,右侧误报概率较高(6%)。其次,我们发现不同行业之间存在显著差异。金融业的误报概率最高(最低评级组为35%),误报幅度最高(真实评级和报告评级之间的评级排名跳跃),能源行业的误报概率最低。最后,当经济状况良好时,CRA更有可能提高评级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
1.00
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信