Procyclicality and Path Dependence of Sovereign Credit Ratings: The Example of Europe

Freitag, Lennart

doi:10.1111/ecno.12032

Cited by 14 publications

(15 citation statements)

References 30 publications

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“…While some papers use GDP growth rate (Feng et al (2008), Koopman et al (2009), and Alp (2013)), others create their own business cycle indicator (Amato and Furfine (2004) and Freitag (2015)). Hence, it is not certain which business cycle variable should be included in the analysis.…”

Section: Datamentioning

confidence: 99%

Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects

Tuzcuoglu

2019

SSRN Journal

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Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals. To tackle this problem, we use composite likelihoods that involve much lower order of integration. However, parameter identification becomes problematic since the information employed in lower dimensional distributions may not be rich enough for identification. Therefore, we characterize types of composite likelihoods that are valid for this model and study conditions under which the parameters can be identified. Moreover, we provide consistency and asymptotic normality results of the pairwise composite likelihood estimator and conduct Monte Carlo simulations to assess its finite-sample performances. Finally, we apply our method to analyze credit ratings. The results indicate a significant improvement in the estimated transition probabilities between rating classes compared with static models.

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Section: Datamentioning

confidence: 99%

Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects

Tuzcuoglu

2019

SSRN Journal

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“…Kabadayi and Celik (2015) examined the effect of macroeconomic and political variables on sovereign ratings of countries using the panel probit model. The conclusion was that credit rating agencies consider the political and economic framework when rating developing countries (Kabadayi & Celik, 2015 Freitag assessed the capacity to repay debt of European countries based on ratings by credit rating agencies using probit model and concluded that credit rating agencies take macroeconomic factors into consideration, however there is inconsistency with regards to upgrades and downgrades in ratings (Freitag, 2015). Hamdi, Herwany, & Tanzil (2015) intended to see if the macroeconomic variables they selected have any effect on ratings by Moody's and Fitch, to compare the ratings given by CRA, and to find out whether sovereign ratings influence return on stock indices.…”

Section: Literaturementioning

confidence: 99%

Comparison of Country Ratings of Credit Rating Agencies with MOORA Method

Genç¹,

Başar²

2019

berj

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The three main credit rating agencies, Standard and Poor's, Moody's and Fitch, use a combination of economic, social and political factors to determine the capacity and current and future debt obligation of countries. This study contributes to literature in two ways. The first one is comparison of results obtained by rating countries on various macroeconomic variables using credit scores given by the three main credit rating agencies and using the MOORA method. The second one is the determination of how optimistic or pessimistic country-based results the three main credit rating agencies yield according to their estimates by macroeconomic variables. Among the three rating agencies, Moody's make the most optimistic estimates in terms of its rating of countries. Moody's is followed by Standard and Poor's, and the credit rating agencies that make the most pessimistic estimates is observed to be Fitch.

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“…Analiza poziomu konkurencji wskazuje na zbliżone wyniki. Podobne wnioski ze swoich badań otrzymał L. Freitag (2015). Sugeruje on, iż faza cyklu koniunkturalnego nie jest uwzględniana przez agencje podczas prowadzenia analizy ryzyka upadłości emitenta.…”

Section: Przegląd Badań Dotyczących Determinant Credit Ratingów Bankówunclassified

Istotność wskaźników finansowych a credit rating banku w czasie kryzysu

Chodnicka-Jaworska

2018

Folia Oeconomica

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Głównym celem artykułu jest analiza zachowania credit ratingu banku w czasie koniunktury i dekoniunktury gospodarczej, przy uwzględnieniu wskaźników finansowych. Na podstawie przeglądu literaturowego postawiono następujące hipotezy badawcze: „Podczas kryzysu w sektorze bankowym występuje silniejszy wpływ wskaźników adekwatności kapitałowej” oraz „Noty ratingowe banków podczas dekoniunktury są niższe niż w okresie prosperity”. Do badania wykorzystano dane kwartalne z lat 1998–2016 dla europejskich banków. Postawione hipotezy zostały zweryfikowane przy użyciu panelowych uporządkowanych modeli probitowych dla długoterminowych credit ratingów banków. Przeprowadzone badania dowodzą, że w momencie kryzysu rating nadawany przez Fitch i Moody bankom jest niższy niż w okresie koniunktury w sektorze bankowym. Ponadto zauważono, iż noty S&P są niewrażliwe na analizowane zmiany.

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Procyclicality and Path Dependence of Sovereign Credit Ratings: The Example of Europe

Cited by 14 publications

References 30 publications

Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects

Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects

Comparison of Country Ratings of Credit Rating Agencies with MOORA Method

Istotność wskaźników finansowych a credit rating banku w czasie kryzysu

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