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

被引:0
|
作者
Lu, Ruichang [1 ]
Luo, Yao [2 ]
Xiao, Ruli [3 ]
机构
[1] Peking Univ, Guanghua Sch Management, Beijing, Peoples R China
[2] Univ Toronto, Dept Econ, Toronto, ON, Canada
[3] Indiana Univ, Dept Econ, 100 S Woodlawn Ave, Bloomington, IN 47405 USA
关键词
business cycle; credit rating; inflation; misreporting;
D O I
10.1002/ise3.51
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:260 / 276
页数:17
相关论文
共 50 条
  • [1] Probability of default estimation in credit risk using a nonparametric approach
    Rebeca Peláez Suárez
    Ricardo Cao Abad
    Juan M. Vilar Fernández
    TEST, 2021, 30 : 383 - 405
  • [2] Cost uniqueness and corporate credit rating
    Zahid, S. M.
    Islam, Mohammad Nazrul
    Zhou, Ling
    FINANCE RESEARCH LETTERS, 2025, 76
  • [3] Impact of Corporate Governance on Credit Rating
    Tarigan, Christi Karolina
    Fitriany, Fitriany
    PROCEEDINGS OF THE 6TH INTERNATIONAL ACCOUNTING CONFERENCE (IAC 2017), 2017, 55 : 248 - 253
  • [4] The credit rating process and estimation of transition probabilities: A Bayesian approach
    Stefanescu, Catalina
    Tunaru, Radu
    Turnbull, Stuart
    JOURNAL OF EMPIRICAL FINANCE, 2009, 16 (02) : 216 - 234
  • [5] Utility indifference valuation of corporate bond with credit rating migration by structure approach
    Liang, Jin
    Zhao, Yuejuan
    Zhang, Xudan
    ECONOMIC MODELLING, 2016, 54 : 339 - 346
  • [6] The New Frontier in Risk Assessment: Estimation of Corporate Credit Rating Quality in Emerging Markets
    Smith, Dylan A.
    Fryer, David
    AFRICAN REVIEW OF ECONOMICS AND FINANCE-AREF, 2012, 4 (01): : 89 - 109
  • [7] Feature selection in corporate credit rating prediction
    Hajek, Petr
    Michalak, Krzysztof
    KNOWLEDGE-BASED SYSTEMS, 2013, 51 : 72 - 84
  • [8] Tax credit rating and corporate innovation decisions
    Yu, Xuehang
    Fang, Junxiong
    CHINA JOURNAL OF ACCOUNTING RESEARCH, 2022, 15 (01)
  • [9] Corporate payments networks and credit risk rating
    Letizia, Elisa
    Lillo, Fabrizio
    EPJ DATA SCIENCE, 2019, 8 (1)
  • [10] A corporate credit rating model with autoregressive errors
    Hirk, Rainer
    Vana, Laura
    Hornik, Kurt
    JOURNAL OF EMPIRICAL FINANCE, 2022, 69 : 224 - 240