Neural Networks, Ordered Probit Models and Multiple Discriminants. Evaluating Risk Rating Forecasts of Local Governments in Mexico
AbstractCredit risk ratings have become an important input in the process of improving transparency of public finances in local governments and also in the evaluation of credit quality of state and municipal governments in Mexico. Although rating agencies have recently been subjected to heavy criticism, credit ratings are indicators still widely used as a benchmark by analysts, regulators and banks monitoring financial performance of local governments in stable and volatile periods. In this work we compare and evaluate the performance of three forecasting methods frequently used in the literature estimating credit ratings: Artificial Neural Networks (ANN), Ordered Probit models (OP) and Multiple Discriminant Analysis (MDA). We have also compared the performance of the three methods with two models, the first one being an extended model of 34 financial predictors and a second model restricted to only six factors, accounting for more than 80% of the data variability. Although ANN provides better performance within the training sample, OP and MDA are better choices for classifications in the testing sample respectively.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Centro de Investigación e Inteligencia Económica (CIIE), Departamento de Ciencias Sociales - UPAEP in its series Working Papers with number 1.
Date of creation: 28 Jun 2011
Date of revision:
Credit Risk Ratings; Ordered Probit Models; Artificial Neural Networks; Discriminant Analysis; Principal Components; Local Governments; Public Finance; Emerging Markets;
Find related papers by JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- H79 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Other
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Mendoza-Velázquez, Alfonso, 2009. "The Information Content and Redistribution Effects of State and Municipal Rating Changes in Mexico," Economics Discussion Papers 2009-17, Kiel Institute for the World Economy.
- Mendoza-Velázquez, Alfonso, 2009. "The information content and redistribution effects of state and municipal rating changes in Mexico," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 3(38), pages 1-21.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alfonso Mendoza Velázquez).
If references are entirely missing, you can add them using this form.