Modeling country risk ratings using partial orders

In order to evaluate the creditworthiness of various countries, a learning model is induced from the 1998 S&P country risk ratings, using the 1998 values of nine economic and three political indicators. This learning model allows the construction of a partially ordered set describing the relative superiority of countries on the basis of their creditworthiness, and it is shown that the Condorcet linear extensions of this poset match closely the S&P ratings. Moreover, the ratings derived from the model correlate highly with those of other rating agencies. The model is shown to provide excellent ratings even when applied to the following years’ data or to the ratings of previously unrated countries. Rating changes implemented by S&P in subsequent years resolved most of the (few) discrepancies between the constructed poset and S&P’s initial ratings. Acknowledgments: The authors gratefully acknowledge the partial support of the National Science Foundation (Grant: NSF-IIS-0312953), as well as the valuable computational advice and support of Dr. Sorin Alexe.