Applying XBRL to US State and Local Government Audited Financial Reports

Marc D. Joffe, Jacqueline L. Reck
{"title":"Applying XBRL to US State and Local Government Audited Financial Reports","authors":"Marc D. Joffe, Jacqueline L. Reck","doi":"10.2139/ssrn.3311695","DOIUrl":null,"url":null,"abstract":"Ten years after the Securities and Exchange Commission mandated the conversion of corporate financial statements to machine-readable formats, there is still no analogous mandate for state and local government Comprehensive Annual Financial Reports (CAFRs). We explore the challenges and benefits of migrating from PDF CAFRs to machine-readable filings using eXtensible Business Reporting Language (XBRL). After explaining the benefits of machine-readable audited municipal financial data, we consider the challenges of creating and implementing an XBRL taxonomy for this sector and the impact a filing mandate would have on state and local governments. To better assess the challenges, we update a CAFR taxonomy previously published by Neal M. Snow and Jacqueline L. Reck and apply it to a city in Florida. While corporate XBRL filers generally use third-party filing firms, they can also use open-source software, low-cost licensed software, or both to produce the filings. Providing a variety of low-cost alternatives to state and local governments helps mitigate the challenge of providing affordable filings.","PeriodicalId":385898,"journal":{"name":"PSN: Local Politics & Policy (Topic)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PSN: Local Politics & Policy (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3311695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Ten years after the Securities and Exchange Commission mandated the conversion of corporate financial statements to machine-readable formats, there is still no analogous mandate for state and local government Comprehensive Annual Financial Reports (CAFRs). We explore the challenges and benefits of migrating from PDF CAFRs to machine-readable filings using eXtensible Business Reporting Language (XBRL). After explaining the benefits of machine-readable audited municipal financial data, we consider the challenges of creating and implementing an XBRL taxonomy for this sector and the impact a filing mandate would have on state and local governments. To better assess the challenges, we update a CAFR taxonomy previously published by Neal M. Snow and Jacqueline L. Reck and apply it to a city in Florida. While corporate XBRL filers generally use third-party filing firms, they can also use open-source software, low-cost licensed software, or both to produce the filings. Providing a variety of low-cost alternatives to state and local governments helps mitigate the challenge of providing affordable filings.
在美国州和地方政府审计财务报告中应用XBRL
在美国证券交易委员会(Securities and Exchange Commission)强制要求将公司财务报表转换为机器可读格式十年之后,对州和地方政府的综合年度财务报告(cafr)仍然没有类似的强制要求。我们将探讨使用可扩展业务报告语言(XBRL)从PDF cafr迁移到机器可读文件的挑战和好处。在解释了机器可读的经审计的市政财务数据的好处之后,我们将考虑为该部门创建和实现XBRL分类法的挑战,以及归档命令对州和地方政府的影响。为了更好地评估这些挑战,我们更新了Neal M. Snow和Jacqueline L. Reck先前发布的CAFR分类法,并将其应用于佛罗里达州的一个城市。虽然企业XBRL申报者通常使用第三方申报公司,但他们也可以使用开源软件、低成本许可软件,或者两者兼而有之。为州和地方政府提供各种低成本的替代方案,有助于缓解提供负担得起的申报文件的挑战。
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
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