.png){kind=icon}
.png){kind=icon}
Return
A random effects ordered probit model for rating migrations
.png){kind=icon}
PRE
AI
DOI：10.1016/j.frl.2010.02.004.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Employing a random effects ordered probit model, this paper examines the sources of heterogeneity in sovereign credit ratings in emerging economies. The analysis uses data from six rating agencies for 90 countries. The model highlights the importance of considering the cross-section error, which captures country-specific heterogeneity, in modelling rating upgrades. Watchlist status is a powerful tool in predicting future rating upgrades/downgrades, and dominates rating momentum in some cases. Rating duration and existing rating are important determinants of rating migrations. Evidence of inter-agency differences and dissimilar behaviour of upgrades and downgrades is presented. (C) 2010 Elsevier Inc. All rights reserved.
Keywords:
Random effects ordered probit model
Emerging sovereign ratings
Rating momentum
Rating Watchlist
Rating duration
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.