The Dimension, Diversity and Complexity of the Macroeconomic Risk
The approach at a macroeconomic level of the challenges in order to foster the competitiveness in certain economic areas implies understanding and assessing the risk as an essential element which can determine in every moment the availability of the mechanisms and the necessary resources for a sustainable future. Even if in a certain measure the risk has to be assumed, the losses caused by undesired events seem to be more ample than the benefits. The most important aspect and part of the risk management is represented by the fact that risk has to be distributed over time, its effects being extended for long periods. While the benefits are hard to distinguish, the efforts seem to be determined at short notice. Any privation of the risk indicators that are correlated with the long-term objectives leads to a barrier when it comes to monitoring the exactitude and performance of the decision-makers. Despite the struggle against the global pressure and the political risk, at a macroeconomic level the uncertainty does not only lingers in association with the external framework, but it also succeeded in reaching extreme levels in comparison with the recent history. The present article aims to observe, categorize and explain the dimension, diversity and complexity of the macroeconomic risk and it will also try to demonstrate that when it comes to composite systems, the risk follows the same path as the environmental context, all because of the diversified overlaps between financial systems and societies, together with their economies and ecosystems.
Keywords: integrated risk management, risk society, uncertainty
 Altman, E. (1968). Financial ratios, discriminant analysis and the predictions of corporate bankruptcy. The Journal of Finance, vol. 23, pp. 589-609.
 Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., Suvas, A. (2016). Financial distress prediction in an international context: A review and empirical analysis of Altman’s Z-Score model. Journal of International Financial Management & Accounting, vol. 28, no. 2, pp. 131-171.
 Bauweraerts,J.(2016).Predictingbankruptcyinprivatefirms:Towardsastepwiseregressionprocedure. International Journal of Financial Research, vol. 7, no. 2, pp. 147-153.
 Bazilevich, V. and Ilin, V. (2010). Metaphizika economiki. Kiev: Znannia.
 Briys,E.,Schlesinger,H.(1990).Riskaversionandthepropensitiesforself-insuranceandself-protection. Southern Economic Journal, vol. 57, pp. 458-467.
 Burn, P., Redwood, V. (2003). Company accounts based modelling of business failures and the implications for financial stability, in Working paper, 210. England: Bank of England.
 Courbage, C., Rey, B. (2012). Optimal prevention and other risks in a two-period model. Mathematical Social Sciences, vol. 63, no. 3, pp. 213-217.
 Cressy, R. (1992). UK small firms bankruptcy predictions: A logit analysis of industry, trend and macro effects. Journal of Small Business Finance, vol. 1, pp. 233-253.
 Dimitras, A., Zanakis, S., Zopounidis, C. (1996). A survey of business failures with an emphasis on prediction methods and industrial applications. European Journal of Operation Research, vol. 90, pp. 487-513.
 Dionne,G.,Eeckhoudt,L.(1985).Self-insurance,self-protectionandincreasedriskaversion.Economics Letters, vol. 17, pp. 39-42.
 Fama, E. (1986). Term premiums and default premiums in money markets. Journal of Financial Economics, vol. 17, pp. 175-196.
 Hernandez-Tinoco, M., Wilson, N. (2013). Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables. International Review of Financial Analysis, vol. 30, pp. 394-419.
 Kumar, M., Rao, V. S. H. (2015). A new methodology for estimating internal credit risk and bankruptcy prediction under Basel II Regime. Computational Economics, vol. 46, no. 1, pp. 83-102.
 Lane,S.,Schary,M.(1989).Themacroeconomiccomponentofbusinessfailure1959–1988,inWorking paper, 89-31. Boston: Boston University.
 Levy, A., Bar-Niv, R. (1987). Macroeconomic aspects of firm bankruptcy analysis. Journal of Macroeconomics, vol. 9, pp. 407-415.
 Melicher, R., Heart, D. (1988). A time series analysis of aggregate business failure: A macroeconomic perspective. Journal of Accounting, Auditing and Finance, vol. 6, pp. 20-31.
 Merton, R. C. (1974). Glossary of Statistical Terms. Available at: https://stats.oecd.org/glossary/detail. asp?ID=6864 (Accessed: 7 October 2019).
 OECD(2005).Onthepricingofcorporatedebt:Theriskstructureofinterestrates. Journal of Finance, vol. 29, pp. 449-470.
 Rose, P., Andrews, W., Giroux, G. (1982). Predicting business failure: A macroeconomic perspective. Journal of Accounting, Auditing and Finance, vol. 6, pp. 20-31.
 Sargent, T. J. (2008). Evolution and intelligent design. American Economic Review, vol. 98, no. 1, pp. 5-37.