Using manually collected data associated with bribery in China, we find that firms receive higher credit ratings when their travel and entertainment expenses are abnormally high. Higher credit ratings help firms to expand their debt capacity, which incentivizes issuers to bribe rating firms for...

We provide insights into determinants of the rating level of 371 issuers which defaulted in the years 1999 to 2003, and into the leader-follower relationship between Moody's and S&P. The evidence for the rating level suggests that Moody's assigns lower ratings than S&P for all observed periods...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

We estimate the effects of R&D on firms' credit ratings and on financial distress. The main purpose is the comparison of firms in Western Germany and Eastern Germany as a transitional economy. Innovative activity has a positive impact on firm value proxied by ratings in Western Germany, but a...

We consider 1927 borrowers from 54 countries who had a credit rating by both Moody's and S&P as of the end of 1998, and their subsequent default history up to the end of 2002. Viewing bond ratings as predicted probabilities of default, we show that it is unlikely that both agencies are well...