Abstract
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.
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References
Ahluwalia, P.: Discriminating contagion: an alternative explanation of contagious currency crises in emerging markets. IMF Working Paper WP/00/14. http://http://www.worldcat.org/title/discriminating-contagion-an-alternative-explanation-of-contagious-currency-crises-in-emerging-markets/oclc/43515556 (2000). Accessed 15 May 2012
Bayoumi, T., Fazio, G., Kumar, M., MacDonald, R.: Fatal attraction: using distance to measure contagion in good times as well as bad. Rev. Financ. Econ. 16, 259–273 (2007)
Brauer, F., Castillo-Chávez, C.: Mathematical Models in Population Biology and Epidemiology. Springer, New York (2001)
http://www.euromoney.com/poll/10683/PollsAndAwards/Country-Risk.html. Accessed 15 May 2012
Dornbusch, R., Park, Y.C., Claessens, S.: Contagion: understanding how it spreads. World Bank Res. Obs. 15(2), 177–197 (2000)
Dungey, M., Fry, R., González-Hermosillo, B., Martin, V.L.: Empirical modelling of contagion: a review of methodologies. Quant. Finance 5(1), 9–24 (2005)
Edwards, S., Susmel, R.: Interest rate volatility and contagion in emerging markets: evidence from the 1990. NBER working paper series 7813. http://www.nber.org/papers/w7813 (2000). Accessed 15 May 2012
Edwards, S., Susmel, R.: Volatility dependence and contagion in emerging equity markets. NBER working paper series 8506. http://www.nber.org/papers/w8506 (2001). Accessed 15 May 2012
Eichengreen, B., Rose, A., Wyplosz, C.: Contagious currency crises. NBER working paper series W5681. http://www.nber.org/papers/w5681 (1996). Accessed 15 May 2012
Fernández-Arias, E., Montiel, P.J.: The surge of capital inflows to developing countries: an analytical overview. World Bank Econ. Rev. 10(1), 51–77 (1996)
Forbes, K., Rigobon, R.: Measuring contagion: conceptual and empirical issues. In: Claessens, S., Forbes, K.J. (eds.) International Financial Crises, pp. 43–66. Kluwer, Boston (2001)
Frambach, R.T.: An integrated model of organizational adoption and diffusion of innovations. Eur. J. Mark. 27, 22–41 (1993)
Hamerly, G., Elkan, C.: Alternatives to the \(k\)-means algorithm that find better clusterings. In: Proceedings of the 11th ACM International Conference on Information and Knowledge Management, pp. 600–607 (2002)
Hoti, S., McAleer, M.: An empirical assessment of country risk rating and associated models. J. Econ. Surv. 18(4), 540–588 (2004)
Kodres, L., Pritsker, M.: A rational expectations model of financial contagion. J. Finance 57(2), 769–799 (2002)
MacKay, D.: Information Theory, Inference and Learning Algorithms, pp. 284–292. Cambridge University Press, Cambridge (2003)
Mahajan, V., Muller, E., Bass, F.M.: New product diffusion models in marketing: a review and directions for research. J. Mark. 54, 1–26 (1990)
Masson, P.R.: Contagion: monsoonal effects, spillovers and jumps between multiple equilibria. In: Agenor, P., Miller, M., Vines, D. (eds.) The Asian Crises: Causes, Contagion and Consequences, pp. 265–283. Cambridge University Press, Cambridge (1999)
Mathematica. http://www.wolfram.com/products/mathematica
Nelder, J.A., Mead, R.: A simplex method for function minimization. Comput. J. 7, 308–313 (1964)
Sachs, J., Tornell, A., Velasco, A.: Financial crises in emerging markets: the lessons from 1995. NBER working paper series 5576. http://www.nber.org/papers/w5576 (1996). Accessed 15 May 2012
Taylor, M.P., Sarno, L.: Capital flows to developing countries: long-and short-term determinants. World Bank Econ. Rev. 11(3), 451–470 (1997)
Zhang, D., Ntoko A.: Mathematical model of technology diffusion in developing countries. In: Computational Methods in Decision-Making, Economics and Finance, pp. 526–539. Kluwer Academic Publisher, Boston (2002)
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Cervelló-Royo, R., Cortés, J.C., Sánchez-Sánchez, A., Santonja, F.J., Shoucri, R., Villanueva, R.J. (2014). Probabilistic European Country Risk Score Forecasting Using a Diffusion Model. In: Mago, V., Dabbaghian, V. (eds) Computational Models of Complex Systems. Intelligent Systems Reference Library, vol 53. Springer, Cham. https://doi.org/10.1007/978-3-319-01285-8_4
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DOI: https://doi.org/10.1007/978-3-319-01285-8_4
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