SUMMARY
To minimize the consequences of asymmetric information, the sovereign risk ratings are instruments that constitute a key piece in the determination of credit market conditions, essential to the growth of developing countries like Brazil. In the present work we studied based on macroeconomics foundations, a classi?cation to sovereign risk ratings realized by the ratings agencies ?nding the classi?cation using Arti?cial Neural Networks. We observed homogeneity degree between the attributions of agencies and macroeconomics foundations in the countries of sample which four of foundations seem to be more directly connected with these attributions. After, in a comparative static exercise, we use the model to make simulations of sceneries of the credit external conditions for the Brazilian economy, changing the macroeconomics foundations which we noted that agencies expected for more per capita income increasing and decrease of public debt.