Politics and Perceived Country Creditworthiness in International Banking

Brewer, Thomas L.; Rivoli, Pietra

doi:10.2307/1992565

Cited by 115 publications

(57 citation statements)

References 26 publications

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“…Theoretical research includes the works of Alter (1961), Finch (1951), Mikesell (1962), Gulathi (1967), Bitterman (1973), Van Agtmael (1976), Brackenbridge (1977, Eaton and Gerovitz (1981), and Lee (1993a,b). Empirical research includes the studies of Frank and Cline (1971), Goodman (1977), Puz (1977), Feder and Just (1977), Feder et al, (1981), Feder and Uy (1985), Abdullah (1985), Brewer and Rivoli (1990), Cosset and Roy (1991), and Lee (1993b). Some of the empirical studies used subjective weighting of scores and others used objective statistical analyses.…”

Section: Review Of the Literaturementioning

confidence: 99%

Predicting LDC debt rescheduling: performance evaluation of OLS, logit, and neural network models

Barney

Alse

2001

Journal of Forecasting

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Empirical studies in the area of sovereign debt have used statistical models singularly to predict the probability of debt rescheduling. Unfortunately, researchers have made few efforts to test the reliability of these model predictions or to identify a superior prediction model among competing models. This paper tested neural network, OLS, and logit models' predictive abilities regarding debt rescheduling of less developed countries (LDC). All models predicted well out-of-sample. The results demonstrated a consistent performance of all models, indicating that researchers and practitioners can rely on neural networks or on the traditional statistical models to give useful predictions.

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Section: Review Of the Literaturementioning

confidence: 99%

Predicting LDC debt rescheduling: performance evaluation of OLS, logit, and neural network models

Barney

Alse

2001

Journal of Forecasting

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“…Using a logit model, they find that political instability is a statistically significant determinant of the probability of borrower default. Brewer and Rivoli (1990) include three measures of political instability along with economic variables and find that regime instability, as measured separately by both changes in the head of government and changes in the governing group, are statistically significant variables in explaining the probability of sovereign debt default. Balkan (1992) considers two dimensions of the borrower's political environment, a democracy index and a political instability index, and finds them both statistically significant in explaining default probabilities in a sample of more than 30 countries.…”

Section: Introductionmentioning

confidence: 99%

Sovereign default, interest rates and political uncertainty in emerging markets

Cuadra

Sapriza

2008

Journal of International Economics

202

129

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Emerging economies tend to experience larger political uncertainty and more default episodes than developed countries. This paper studies the effect of political risk on sovereign default and interest rate spreads in emerging markets. The paper develops a quantitative model of sovereign debt and default under political risk in a small open economy that captures some of the main empirical regularities in emerging economies: default occurs in equilibrium and interest rate spreads and default risk are countercyclical.More polarized economies experience higher default rates and larger level and volatility of spreads. Also consistent with empirical evidence, the quantitative analysis shows that higher levels of political uncertainty significantly raise the default frequency and both the level and volatility of spreads.

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“…This question is subject to different analyses. Haque et al (1998) claim that it is sufficient to restrict the scope of analysis to economic factors only, while others (Brewer and Rivoli 1990) claim that both economic and political factors impact country risk ratings. This lack of clarity raised the discontent of Japan's Prime Minister, Junichiro Koizumi, who was "railed at being rated in the same neighborhood as African countries to which Japan is providing assistance".…”

Section: Critiques Of Present Rating Systemsmentioning

confidence: 99%

Reverse-engineering country risk ratings: a combinatorial non-recursive model

2009

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The central objective of this paper is to develop a transparent, consistent, selfcontained, and stable country risk rating model, closely approximating the country risk ratings provided by Standard and Poor's (S&P). The model should be non-recursive, i.e., it should not rely on the previous years' S&P ratings. The set of variables selected here includes not only economic-financial but also political variables. We propose a new model based on the novel combinatorial-logical technique of Logical Analysis of Data (which derives a new rating system only from the qualitative information representing pairwise comparisons of country riskiness). We also develop a method allowing to derive a rating system that has any desired level of granularity. The accuracy of the proposed model's predictions, measured by its correlation coefficients with the S&P ratings, and confirmed by kfolding cross-validation, exceeds 95%. The stability of the constructed non-recursive model is shown in three ways: by the correlation of the predictions with those of other agencies (Moody's and The Institutional Investor), by predicting 1999 ratings using the non-recursive model derived from the 1998 dataset applied to the 1999 data, and by successfully predicting the ratings of several previously non-rated countries. This study provides new insights on the importance of variables by supporting the necessity of including in the analysis, in addition to economic variables, also political variables (in particular "political stability"), and Peter L. Hammer tragically died in a car accident on December 27, 2006, after this manuscript was essentially completed. The authors express their appreciation to Dr. Sorin Alexe for his invaluable help in the execution of computational experiments with LAD.

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Politics and Perceived Country Creditworthiness in International Banking

Cited by 115 publications

References 26 publications

Predicting LDC debt rescheduling: performance evaluation of OLS, logit, and neural network models

Predicting LDC debt rescheduling: performance evaluation of OLS, logit, and neural network models

Sovereign default, interest rates and political uncertainty in emerging markets

Reverse-engineering country risk ratings: a combinatorial non-recursive model

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