A multi-country study of factors and threshold values affecting sovereign debt-taking behavior

IF 1.8 Q2 BUSINESS, FINANCE International Journal of Managerial Finance Pub Date : 2022-07-13 DOI:10.1108/ijmf-06-2021-0291
Reza Tahmoorespour, M. Ariff, K. Lee, Sharon Dharsini Anthony, Yaasmin Farzana Abdul Karim
{"title":"A multi-country study of factors and threshold values affecting sovereign debt-taking behavior","authors":"Reza Tahmoorespour, M. Ariff, K. Lee, Sharon Dharsini Anthony, Yaasmin Farzana Abdul Karim","doi":"10.1108/ijmf-06-2021-0291","DOIUrl":null,"url":null,"abstract":"PurposeThis manuscript reports evidence on how debt-taking decisions of top management in a multi-country setting do affect credit rating scores assigned by credit rating agencies (CRAs) as global monitors of creditworthiness of borrowers. This aspect has been long ignored by researchers in the literature. The purpose of this paper is twofold. A test model is specified first using theories to connect debt-taking behavior to credit rating scores. Once that model helps to identify a number of statistically significant factors, the next step helps to identify threshold values at which the variables driving debt-taking behavior would worsen the credit rating scores as turning points of the thresholds.Design/methodology/approachThe study identifies factors driving creditworthiness scores due to debt-taking behavior of countries and develops a correct research design to identify a model that explains (1) credit rating scores and the factors driving the scores and runs (2) panel-type regressions to test model fit. Having found factors driving debt-taking behavior by observed units, the next step identifies threshold values of factors at which point further debt-taking is likely to worsen credit rating risk of the observed units. This is a robustness test of the methodology used. The observed units are 20 countries with data series across 14 years.FindingsFirst, new findings suggest there are about six major factors associated with debt-taking behavior and credit rating changes. Second, the model developed in this study is able to account for substantial variability while the identified factors are statistically significant within the normal p-values for acceptance of hypotheses. Finally, the threshold values of factors identified are likely to be useful for managerial decisions to judge the levels at which further debt-taking would worsen the credit rating scores of the observed units.Research limitations/implicationsThe observed units are from 20 countries over 14 years of annual data available on credit rating scores (privately obtained from Standard and Poor [S&P]). The sample represents major economies but did not include emerging countries. In that regard, it will be worthwhile to explore the debt-taking behavior of emerging economies in a future study using the methodology verified in this study.Practical implicationsThe findings help add few useful guidelines for top management decisions. (1) There are actually factors that are associated with debt-taking behavior, so the authors now know these factors as guides for managerial actions. (2) The authors are free to state that the credit rating changes occur on objective changes in the factors found as significantly related to the debt-taking behavior. (3) The threshold values of key factors are known, so top management could use these threshold values of named factors to monitor if a debt-taking decision is going to push the credit rating to a worse score.Social implicationsThere are society-wide implications. Knowing that the world's debt level is high at US$2.2 for each gross domestic product (GDP) dollar across almost 200 countries, any knowledge on what factors help drive creditworthiness scores, thus credit riskiness, is revealed in this paper. Knowing those factors and also knowing the turning points of the factors – the threshold values – likely to worsen creditworthiness scores is a powerful tool for controlling excessive debt-taking by an observation unit included in this study (The dataset in this research can also be used to see inter-temporal movement on debt-taking in a future study).Originality/valueIn the authors' view, there are many studies on debt-taking behavior. But none has connected debt-taking on how (1) named factors are observable to management that affect credit rating changes and (2) if a factor affects creditworthiness, at which point of the factor value, the creditworthiness will flip to worsen the score. These aspects are seldom found in the literature. Hence, the paper is original with practical value at the global level.","PeriodicalId":51698,"journal":{"name":"International Journal of Managerial Finance","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Managerial Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijmf-06-2021-0291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1

Abstract

PurposeThis manuscript reports evidence on how debt-taking decisions of top management in a multi-country setting do affect credit rating scores assigned by credit rating agencies (CRAs) as global monitors of creditworthiness of borrowers. This aspect has been long ignored by researchers in the literature. The purpose of this paper is twofold. A test model is specified first using theories to connect debt-taking behavior to credit rating scores. Once that model helps to identify a number of statistically significant factors, the next step helps to identify threshold values at which the variables driving debt-taking behavior would worsen the credit rating scores as turning points of the thresholds.Design/methodology/approachThe study identifies factors driving creditworthiness scores due to debt-taking behavior of countries and develops a correct research design to identify a model that explains (1) credit rating scores and the factors driving the scores and runs (2) panel-type regressions to test model fit. Having found factors driving debt-taking behavior by observed units, the next step identifies threshold values of factors at which point further debt-taking is likely to worsen credit rating risk of the observed units. This is a robustness test of the methodology used. The observed units are 20 countries with data series across 14 years.FindingsFirst, new findings suggest there are about six major factors associated with debt-taking behavior and credit rating changes. Second, the model developed in this study is able to account for substantial variability while the identified factors are statistically significant within the normal p-values for acceptance of hypotheses. Finally, the threshold values of factors identified are likely to be useful for managerial decisions to judge the levels at which further debt-taking would worsen the credit rating scores of the observed units.Research limitations/implicationsThe observed units are from 20 countries over 14 years of annual data available on credit rating scores (privately obtained from Standard and Poor [S&P]). The sample represents major economies but did not include emerging countries. In that regard, it will be worthwhile to explore the debt-taking behavior of emerging economies in a future study using the methodology verified in this study.Practical implicationsThe findings help add few useful guidelines for top management decisions. (1) There are actually factors that are associated with debt-taking behavior, so the authors now know these factors as guides for managerial actions. (2) The authors are free to state that the credit rating changes occur on objective changes in the factors found as significantly related to the debt-taking behavior. (3) The threshold values of key factors are known, so top management could use these threshold values of named factors to monitor if a debt-taking decision is going to push the credit rating to a worse score.Social implicationsThere are society-wide implications. Knowing that the world's debt level is high at US$2.2 for each gross domestic product (GDP) dollar across almost 200 countries, any knowledge on what factors help drive creditworthiness scores, thus credit riskiness, is revealed in this paper. Knowing those factors and also knowing the turning points of the factors – the threshold values – likely to worsen creditworthiness scores is a powerful tool for controlling excessive debt-taking by an observation unit included in this study (The dataset in this research can also be used to see inter-temporal movement on debt-taking in a future study).Originality/valueIn the authors' view, there are many studies on debt-taking behavior. But none has connected debt-taking on how (1) named factors are observable to management that affect credit rating changes and (2) if a factor affects creditworthiness, at which point of the factor value, the creditworthiness will flip to worsen the score. These aspects are seldom found in the literature. Hence, the paper is original with practical value at the global level.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
影响主权债务承担行为的因素和阈值的多国研究
目的这份手稿报告了在多国环境中,最高管理层的债务决策如何影响信用评级机构(CRA)作为借款人信用度的全球监测机构所分配的信用评级分数的证据。这一方面长期以来一直被文献中的研究者所忽视。本文的目的是双重的。首先使用理论将债务承担行为与信用评级分数联系起来,指定了一个测试模型。一旦该模型有助于识别一些具有统计意义的因素,下一步就有助于确定阈值,在该阈值下,驱动债务承担行为的变量会使信用评级得分恶化,成为阈值的转折点。设计/方法论/方法该研究确定了由于国家的债务承担行为而导致的信用评分的驱动因素,并制定了正确的研究设计,以确定一个模型,该模型解释(1)信用评级评分和驱动评分的因素,并运行(2)面板型回归来测试模型拟合度。在发现了驱动被观察单位承担债务行为的因素后,下一步确定了进一步承担债务可能恶化被观察单位信用评级风险的因素阈值。这是对所用方法的稳健性测试。观察到的单位是20个国家,数据系列跨越14年。首先,新的发现表明,大约有六个主要因素与债务承担行为和信用评级变化有关。其次,本研究中开发的模型能够解释显著的可变性,而所确定的因素在接受假设的正常p值内具有统计学意义。最后,所确定的因素的阈值可能有助于管理层做出决定,以判断进一步举债将使被观察单位的信用评级得分恶化的程度。研究局限性/含义观察到的单位来自20个国家,超过14年的信用评级得分年度数据(私下从标准普尔获得)。样本代表主要经济体,但不包括新兴国家。在这方面,有必要在未来的研究中使用本研究中验证的方法来探索新兴经济体的债务承担行为。实际含义这些发现有助于为高层管理决策增加一些有用的指导方针。(1) 实际上,有一些因素与负债行为有关,所以作者现在知道这些因素是管理行动的指南。(2) 作者可以自由地声明,信用评级的变化是由于与债务承担行为显著相关的因素的客观变化而发生的。(3) 关键因素的阈值是已知的,因此最高管理层可以使用这些命名因素的阈值来监控债务承担决定是否会将信用评级推至更差的分数。社会影响有全社会的影响。鉴于全球近200个国家的债务水平高达每国内生产总值2.2美元,本文揭示了哪些因素有助于提高信用评分,从而提高信用风险。了解这些因素,并了解可能使信用评分恶化的因素的转折点——阈值——是本研究中观察单位控制过度举债的有力工具(本研究中的数据集也可用于在未来的研究中观察举债的时间间变化),关于债务承担行为的研究很多。但没有人将债务承担与以下因素联系起来:(1)管理层可以观察到影响信用评级变化的命名因素;(2)如果某个因素影响了信用度,在该因素值的哪个点,信用度将翻转,使得分恶化。这些方面在文献中很少见到。因此,该论文具有原创性,在全球范围内具有实用价值。
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 去求助
来源期刊
CiteScore
4.10
自引率
0.00%
发文量
47
期刊介绍: Treasury and Financial Risk Management ■Redefining, measuring and identifying new methods to manage risk for financing decisions ■The role, costs and benefits of insurance and hedging financing decisions ■The role of rating agencies in managerial decisions Investment and Financing Decision Making ■The uses and applications of forecasting to examine financing decisions measurement and comparisons of various financing options ■The public versus private financing decision ■The decision of where to be publicly traded - including comparisons of market structures and exchanges ■Short term versus long term portfolio management - choice of securities (debt vs equity, convertible vs non-convertible)
期刊最新文献
Examining the Indonesian dual banking system: an exploration of market discipline indicators CEO compensation and bank’s performance following bank-rescue Does corporate sustainability performance matter for cash holdings? International evidence Nonfinancial 8-K disclosures and individual investors' trading during earnings announcement window Corporate governance and capital structure dynamics: evidence from an emerging market
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1