Probabilistic European Country Risk Score Forecasting Using a Diffusion Model

Over the last few years, global crisis has shaken confidence in most European economies. As a consequence, a lack of confidence has spread amongst European countries leading to Europe’s financial instability. Therefore, forecasting the next future of economic situation involves high levels of uncertainty. In this respect, it would be interesting to use tools which allow to predict the trends and evolution of each country’s confidence rating. The Country Risk Score (CRS) represents a good indicator to measure the current situation of a country regarding measures of economic, political and financial Risk in order to determine country Risk ratings. CRS is underscored by Euromoney Agency and is calculated by assigning weights to these measures. In this contribution, we present a diffusion model to study the dynamics of the CRS in 27 European countries which considers both the endogenous effect of each country policies and the contagion effect among them. The model depicts quite well the evolution of the CRS despite jumps and uncertainty in the data within some periods. Furthermore, it should be noted a downward trend in the CRS dynamics for almost all European countries in the next year.

[1]  Roberto Rigobon,et al.  Measuring Contagion: Conceptual and Empirical Issues , 2001 .

[2]  Vance L. Martin,et al.  Empirical modelling of contagion: a review of methodologies , 2005 .

[3]  Greg Hamerly,et al.  Alternatives to the k-means algorithm that find better clusterings , 2002, CIKM '02.

[4]  Paul R. Masson,et al.  Contagion: Monsoonal Effects, Spillovers, and Jumps Between Multiple Equilibria , 1998 .

[5]  Pavan Ahluwalia,et al.  Discriminating Contagion: An Alternative Explanation of Contagious Currency Crises in Emerging Markets , 2000, SSRN Electronic Journal.

[6]  June Dong,et al.  Mathematical Model of Technology Diffusion in Developing Countries , 2002 .

[7]  Vijay Mahajan,et al.  New Product Diffusion Models in Marketing: A Review and Directions for Research: , 1990 .

[8]  Eduardo Fernández-Arias,et al.  The surge in capital inflows to developing countries : an analytical overview , 1996 .

[9]  Giorgio Fazio,et al.  Fatal Attraction , 2003 .

[10]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.

[11]  Stijn Claessens,et al.  Contagion: Understanding How It Spreads , 2000 .

[12]  F. Brauer,et al.  Mathematical Models in Population Biology and Epidemiology , 2001 .

[13]  Sebastian Edwards,et al.  Interest Rate Volatility and Contagion in Emerging Markets: Evidence from the 1990s , 2000 .

[14]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[15]  Michael McAleer,et al.  An Empirical Assessment of Country Risk Ratings and Associated Models , 2004 .

[16]  Matthew Pritsker,et al.  A Rational Expectations Model of Financial Contagion , 1998 .

[17]  Andrés Velasco,et al.  Financial Crises in Emerging Markets: The Lessons from 1995 , 1996 .

[18]  Mark P. Taylor,et al.  Capital Flows to Developing Countries: Long- and Short-Term Determinants , 1997 .

[19]  R. Frambach.  An Integrated Model of Organizational Adoption and Diffusion of Innovations , 1993 .