Sovereign Credit Ratings

I argue that when two or more credit rating agencies rate a product, they have the incentive to put a weight on the competitors' rating. This piggybacking allows an agency to increase the precision of its own rating while doing less monitoring. Although it is privately effcient, it implies that having more rating agencies does not necessarily increase the overall monitoring. Using annual data on sovereign debt ratings I show that the probability of a rating change depends on the rating differential towards its competitors, even when accounting for a common information set, which is consistent with the hypothesis.

JEL Classification: G15, G24

Keywords: sovereign debt ratings, credit rating agencies, rating transitions.


Working paper, 2013


"Sovereign credit ratings, market volatility, and financial gains",

Computational Statistics & Data Analysis

With António Afonso and Abderrahim Taamouti

The reaction of EU bond and equity market volatilities to sovereign rating announcements (Standard & Poor's, Moody's, and Fitch) is investigated using a panel of daily stock market and sovereign bond returns. The parametric volatilities are filtered using EGARCH specifications. The estimation results show that upgrades do not have significant effects on volatility, but downgrades increase stock and bond market volatility. Contagion is present, with sovereign rating announcements creating interdependence among European financial markets with upgrades (downgrades) in one country leading to a decrease (increase) in volatility in other countries. The empirical results show also a financial gain and risk (value-at-risk) reduction for portfolio returns when taking into account sovereign credit ratings’ information for volatility modelling, with financial gains decreasing with higher risk aversion.

Keywords: Sovereign ratings; yields; stock market returns; volatility; EGARCH; optimal portfolio; financial gain; risk management; value-at-risk..

With António Afonso and Davide Furceri

We use EU sovereign bond yield and CDS spreads daily data to carry out an event study analysis on the reaction of government yield spreads before and after announcements from rating agencies (Standard & Poor's, Moody's, Fitch). Our results show significant responses of government bond yield spreads to changes in rating notations and outlook, particularly in the case of negative announcements. Announcements are not anticipated at 1-2 months horizon but there is bi-directional causality between ratings and spreads within 1-2 weeks; spillover effects especially among EMU countries and from lower rated countries to higher rated countries; and persistence effects for recently downgraded countries.

JEL CODEL: C23; E44; G15.

Keywords: credit ratings; sovereign yields; rating agencies.

With António Afonso

We use sovereign debt rating estimations from Afonso, Gomes and Rother (2009, 2011) for Fitch, Moody's, and Standard & Poor's, to assess to what extent the recent fiscal imbalances are being reflected on the sovereign debt notations. With macro and fiscal data up to 2010, and macro and fiscal projections, we obtain the expected rating for several OECD countries. The answer to the title question is yes, but in a diverse way for each country. Our average model predictions point to a heterogeneous behaviour of rating agencies across countries.

JEL CODEL: C23; E44; G15.

Keywords: credit ratings; rating agencies.

Published, 2011


"What are the Short and Long-run Determinants of Sovereign Debt Ratings",

International Journal of Finance and Economics

With António Afonso and Philipp Rother

We study the determinants of sovereign debt ratings from the three main international rating agencies, for the period 1995-2005. Using linear and ordered response models we employ a specification that allows us to distinguish between short and long-run effects, on a country's rating, of macroeconomic and fiscal variables. Changes in GDP per capita, GDP growth, government debt, and government balance have a short-run impact on a country's credit rating, while government effectiveness, external debt, foreign reserves and default history are important long-run determinants.

JEL Codes: C23; C25; E44; F30; G15

Keywords: Credit ratings; sovereign debt; rating agencies; random effects ordered probit

Published, 2011

Data Used

With António Afonso and Philipp Rother

Using ordered logit and probit plus random effects ordered probit approaches we study the determinants of sovereign ratings. The last procedure should be more appropriate for panel data as it considers the existence of an additional normally distributed cross-section error.

JEL Codes: C23; C25; E44; F30; F34; G15; H63

Keywords: Credit ratings; sovereign debt; rating agencies; panel data; random effects ordered probit

Published 2009


With António Afonso and Philipp Rother

In this paper we study the determinants of sovereign debt credit ratings using rating notations from the three main international rating agencies, for the period 1995-2005. We employ panel estimation and random effects ordered probit approaches to assess the explanatory power of several macroeconomic and public governance variables. Our results point to a good performance of the estimated models, across agencies and across the time dimension, as well as a good overall prediction power. Relevant explanatory variables for a country's credit rating are: GDP per capita, GDP growth, government debt, government effectiveness indicators, external debt, external reserves, and default history.

JEL Codes: C23; C25; E44; F30; F34; G15; H63

Keywords: Credit ratings; sovereign debt; rating agencies; panel data; random effects ordered probit

Book chapter, 2008

Working Paper