Political instability, country risk and probability of default

Balkan, Erol

doi:10.1080/00036849200000077

Cited by 90 publications

(42 citation statements)

References 11 publications

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“…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. He uses a democracy index that measures two components of the political system: participation, which measures the extent to which the executive and legislative branches of government reflect the popular will, and competitiveness, which incorporates the degree of exclusion of political parties from the system and the ability of the largest party to dominate national elections.…”

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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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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“…Bu dönemde borç krizleri ile birlikte, çeşitli ülke riski analizleri yapılmaya başlamıştır. Bu kapsamda Angeloni/Short (1980) ile Feder/Ross (1982) gibi iktisatçılar ülke riskinin faiz oranı farklılıkları ve banka borçları üzerİndeki etkilerini; Edwards (1984); Brewer/Rivoli (1990) ve Balkan (1992) ise borçlarla ülke riski arasındaki ilişkiyi araştırma konusu yapmışlardır.…”

Section: Introductionunclassified

Ülke Riskinin Hisse Senedi Fiyatlarına Etkisi: İMKB 100 Endeksi Üzerine Bir Araştırma

Sevda;GÜNGÖR¹

2007

Ankara Üniversitesi SBF Dergisi

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Bu çalışmanın amacı ekonomik. politik ve finansal tilke risklerinin hisse senedi fiyatlarına etkisini tespit etmektir. Ülke risk primleri, son dönemlerde çalışmalarda oldukça sık kullanılan ve gtivenilirliği kabul edilmiş ICRG (International Country Risk Guide)'den temin edilmiştir. 1986:1-2006:12 dönemini kapsayan bu çalışmada, İMKB 100 endeksi, ekonomik, finansal ve politik risk primi değişkenleri kullanılmıştır. Johansen-Juselius eş-btittinleşme testleri. ekonomik, finansal ve politik risk primleri ile İMKB 100 bileşik endeksi arasında uzun dönemli bir ilişki olduğunu, Granger nedensellik testleri ise ekonomik risk ve politik riskten İMKB 100 endeksine doğru bir nedenselliğin olduğunu göstermektedir. Çalışmada finansal risk ve İMKB 100 bileşik endeksi arasında herhangi bir nedensellik gözlenmemiştir. Yapılan regresyon tahminleri. ekonomik. finansal ve politik risklerin hisse senedi fiyatlarınt olumsuz yönde etkilediiline işaret etmektedir. AnahtarKelimeler: Ekonomik risk, finansal risk. politik risk. hisse senedi fiyatları, Granger nedensellik testleri.

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“…Therefore, indicator systems should be designed to capture target agent features. For country credit, the existing indicator system mainly encompasses a country's economic, financial, social, cultural, geographic, and political fields including its relationship with other countries (Li et al 2012a;Balkan 1992;Block and Vaaler 2004;Beirne and Fratzscher 2013). For example, Balkan Balkan 1992 proposed a model with two political risk variables (level of democracy and political instability) and some economic variables and showed that the novel model including the political variables generated superior results than the model limited to economic variables.…”

Section: Indicator Systemsmentioning

confidence: 99%

“…Moreover, the explanatory variables (or evaluation indexes) play an important role in credit rating prediction and vary across different target agents. For example, country risk includes a country's economic, financial, social, cultural, geographic, and political fields and extends to its relationship with other countries (Li et al 2012a;Balkan 1992;Block and Vaaler 2004;Beirne and Fratzscher 2013). Evaluation indexes for corporate credit can be divided into financial and nonfinancial indicators (Duffee and Zhou 2001;Min and Lee 2008).…”

Section: Introductionmentioning

confidence: 99%

Social credit: a comprehensive literature review

Tang

et al. 2015

Financial Innovation

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To avoid credit fraud, social credit within an economic system has become an increasingly important criterion for the evaluation of economic agent activity and guaranteeing the development of a market economy with minimal supervision costs. This paper provides a comprehensive review of the social credit literature from the perspectives of theoretical foundation, scoring methods, and regulatory mechanisms. The study considers the credit of various economic agents within the social credit system such as countries (or governments), corporations, and individuals and their credit variations in online markets (i.e., network credit). A historical review of the theoretical (or model) development of economic agents is presented together with significant works and future research directions. Some interesting conclusions are summarized from the literature review. (1) Credit theory studies can be categorized into traditional and emerging schools both focusing on the economic explanation of social credit in conjunction with creation and evolution mechanisms. (2) The most popular credit scoring methods include expert systems, econometric models, artificial intelligence (AI) techniques, and their hybrid forms. Evaluation indexes should vary across different target agents. (3) The most pressing task for regulatory mechanisms that supervise social credit to avoid credit fraud is the establishment of shared credit databases with consistent data standards.

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Political instability, country risk and probability of default

Cited by 90 publications

References 11 publications

Sovereign default, interest rates and political uncertainty in emerging markets

Sovereign default, interest rates and political uncertainty in emerging markets

Ülke Riskinin Hisse Senedi Fiyatlarına Etkisi: İMKB 100 Endeksi Üzerine Bir Araştırma

Social credit: a comprehensive literature review

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