Spatio‑Temporal Analysis of the Impact of Credit Rating Agency Announcements on the Government Bond Yield in the World in the Period of 2008–2017

The paper concerns the impact of announcements published by rating agencies on the government bond yield in selected countries of the world. Ratings assigned to debt securities on account of the issuer’s financial standing are an important determinant of their yield. Factors that affect the rate of...

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Bibliographic Details
Main Authors: Elżbieta Szulc, Dagna Wleklińska
Format: Article
Language:English
Published: Lodz University Press 2019-08-01
Series:Acta Universitatis Lodziensis. Folia Oeconomica
Subjects:
Online Access:https://czasopisma.uni.lodz.pl/foe/article/view/3331
Description
Summary:The paper concerns the impact of announcements published by rating agencies on the government bond yield in selected countries of the world. Ratings assigned to debt securities on account of the issuer’s financial standing are an important determinant of their yield. Factors that affect the rate of return of a given traded debt, in addition to idiosyncratic factors, i.e. those related to the issuer’s economy, and global factors, also include the ratings of connected countries. Moreover, empirical studies carried out in this area prove that the relationship is asymmetrical. This allows us to suppose that favourable information concerning the improvement of government bond ratings is not reflected in the decrease in their yield. The aim of the paper is the analysis of interactions between the yields of 10‑year government bonds issued by selected economies. A subject that is of particular interest is the evaluation of the impact of positive and negative changes in credit rating assessments made by international agencies on the yield of bonds issued by other economies than the country concerned in the assessment. The spatial scope of the analysis concerns 10‑year government bonds issued by 40 countries in the period of 2008-2017. In the study, dynamic spatial models for pooled time series and cross‑sectional data and dynamic spatial panel data models were used.
ISSN:0208-6018
2353-7663