In my Bachelor thesis I analyze the determinants of rating changes and the variables'marginal effects on rating change probabilities. Based on my results, I present transition matrices by computing transition probabilities. Furthermore, I analyze subsamples of my data set, conditional on the business cycle and the economic strength of a country, by using interaction effects. I thereby verify whether or how the transition matrices change by including interaction effects.
I apply a latent variable approach, using an ordered probit model, to calculate the effects of different variables on the probabilities of rating changes.
Table of Contents
1 Introduction
2 Previous Literature
3 Agencies’ rating assessment
3.1 Rating Definitions and Methodology
3.2 Rating Transition Matrices
4 Ordered Probit Model
4.1 Mathematical Framework
4.2 Model parameters
4.3 Marginal effects
5 Data
5.1 Data summary
5.2 Independent Variables and direction of change
5.3 Choice of Variables
6 Estimation
6.1 Simple Ordered Probit Model
6.2 Random Effects Ordered Probit Model
6.3 Marginal Effects
7 Predicted Probabilities and Transition matrices
7.1 Predicted Probabilities
7.2 Unconditional Transition Matrices
7.3 Conditional Transition Matrices
8 Conclusion
Research Objectives and Key Themes
This thesis investigates the determinants of sovereign rating changes and analyzes the marginal effects of various variables on rating change probabilities. By applying a latent variable approach with an ordered probit model, the study aims to estimate transition probabilities and evaluate how these differ across subsamples, specifically focusing on non-developing countries and different stages of the business cycle.
- Determinants of sovereign credit rating transitions.
- Application of the ordered probit model in a sovereign rating context.
- Computation and analysis of conditional and unconditional transition matrices.
- Evaluation of macroeconomic and governmental variables as drivers of rating migration.
Excerpt from the Book
3.1 Rating Definitions and Methodology
"Sovereign debt ratings are forward-looking qualitative measures of the probability of default, given in the form of a code" (Afonso et al., 2009). There are both short- and long-term ratings. In this Bachelor thesis I will discuss only long-term ratings because they are better known and because they allow a broader ranking of letter rating categories. There are 9 coarse rating categories and 21 fine rating categories for long-term ratings, whereas there are only four short term ratings which are P-1, P-2, P-3 and not prime.
Table 1 in the Appendix shows the order of Moody’s ratings with the respective evaluation of a corresponding country’s credit standing (Moody’s, 2012a). Next to Moody’s credit codes, I also added the codes that I use for my analysis, in order to be able to calculate with them.
Moody’s have a three-stage process to determine a sovereign rating (Moody’s, 2008). In the first step, they assess the country’s economic resiliency. In the second step, they assess the government’s financial robustness. Finally, in the third step they determine the rating within the fine rating category.
Summary of Chapters
1 Introduction: This chapter highlights the significance of sovereign ratings and their impact on capital costs, while outlining the research goal to analyze determinants of rating changes and transition probabilities.
2 Previous Literature: This section provides an overview of existing research on sovereign and corporate rating determinants, emphasizing findings related to macroeconomic variables and previous methodological approaches.
3 Agencies’ rating assessment: This chapter details the rating categories, definitions, and the multi-stage process Moody’s uses to assign sovereign ratings.
4 Ordered Probit Model: This section introduces the theoretical latent variable approach, the mathematical framework, and the method for calculating marginal effects used throughout the analysis.
5 Data: This chapter summarizes the dataset, covering 113 countries from 1990 to 2011, and discusses the selection and interpretation of independent variables.
6 Estimation: This chapter presents the regression results from simple and random effects ordered probit models, evaluating the influence of various determinants on rating changes.
7 Predicted Probabilities and Transition matrices: This chapter computes and contrasts predicted probabilities and transition matrices for different groups and business cycle conditions.
8 Conclusion: This final chapter synthesizes the findings, discusses the validity of the applied models, and offers suggestions for future research regarding correlation and spillover effects.
Keywords
Sovereign Ratings, Rating Changes, Ordered Probit Model, Transition Matrices, Macroeconomic Variables, Credit Risk, Moody's, Marginal Effects, Business Cycle, Non-developing Countries, Default History, Inflation, GDP Growth, Debt, Financial Robustness
Frequently Asked Questions
What is the primary focus of this thesis?
The thesis focuses on analyzing the determinants of sovereign rating changes and computing transition probabilities using an ordered probit model.
What are the central themes addressed in the work?
The work covers sovereign rating methodologies, the impact of macroeconomic and government indicators on rating transitions, and the construction of transition matrices for various country subsamples.
What is the main research objective?
The goal is to determine which variables drive sovereign rating changes and to analyze the marginal effects of these variables on rating transition probabilities.
Which methodology is applied?
The author employs a latent variable approach using an ordered probit model to estimate the probabilities of rating migrations.
What is covered in the main body?
The main body covers the review of literature, the explanation of rating agencies' assessment processes, the mathematical framework of the probit model, data analysis, and the presentation of estimation results and transition matrices.
Which keywords characterize the research?
Key terms include Sovereign Ratings, Ordered Probit Model, Transition Matrices, Credit Risk, and Macroeconomic Determinants.
How does the author define "non-developing" versus "developing" countries?
The author classifies countries based on a GNI per capita threshold of 4,036 US$ to separate non-developing from developing nations, accounting for heterogeneity within the middle-income group.
Why did the author use long-term ratings exclusively?
Long-term ratings were selected because they are more widely recognized and provide a broader, more granular ranking of rating categories compared to short-term ratings.
- Arbeit zitieren
- Alex Bergen (Autor:in), 2012, Rating change probabilities: An empirical analysis of sovereign ratings, München, GRIN Verlag, https://www.grin.com/document/231459
