Lorena Caridad López del Río

Forecasting companies long-term financial health is provided by Credit Rating Agencies (CRA) such as S&P, Moody’s, Fitch and others. Estimates of rates are based on publicly available data, and on the so-called ‘qualitative information’. Nowadays, it is possible to produce quite precise forecasts for these ratings using economic and financial information that is available in financial databases, utilizing statistical models or, alternatively, Artificial Intelligence techniques. Several approaches, both cross section and dynamic are proposed, using different methods. Artificial Neural Networks (ANN) provide better results than multivariate statistical methods and are used to estimate ratings within all the range provided by the CRAs, obtaining more desegregated results than several proposed models available for intervals of ratings. Two large samples of companies ‘public data’ obtained from Bloomberg are used to obtain forecasts of S&P and Moody’s ratings directly from these data with high level of accuracy. This also permits to check the published rating’s reliability provided by different CRAs.

This study offers in-depth knowledge of the socio-economic characteristics of funded pension projects. It is based on the financial position of pension market actors during the transition of the pension system to a more funded capitalized scheme, mainly through the option benefit model. This is possible due to the fact that the economy is not viewed as a single earning cohort. The study analytically demonstrates a socio-economic anomaly in the funded pension system, which is in favor of high-earning cohorts at the expense of low-earning cohorts. This anomaly is realized due to lack of insurance and exposure to financial and systemic risks. Furthermore, the anomaly might lead to the pension re-reform back to an unfunded scheme, mainly due to political pressure. A minimum pension guarantee was found to be a rebalance mechanism to this anomaly, which increases the probability of a sustainable pension scheme. Specifically, it is argued that implementing a guarantee with an intra-generational, risk-sharing mechanism is the most effective way to reduce the impact of this abnormality. Moreover, the paper shows the convergence process toward implementing a minimum pension guarantee in many countries that have capitalized their pension systems during the last three decades, in particular in Latin America and Central and Eastern Europe.

Using funded and unfunded pillars, the optimal pension structure is estimated using an over-lapping generation model, calibrated to the average OECD countries. While simulating different pillar sizes, a socio-economic characteristic was revealed in which low-earning groups are prone to unexpected market risks than high-earning cohorts and support a larger contribution than better-off individuals. This led to high contribution rates for funded pillars and low contributions rates for social security pillars. This suboptimal allocation leads to inefficient hedging capability for the pension portfolio. An alternative is a minimum pension guarantee as an efficient system stabilizer as it rebalances the economic cost among different earning cohorts. However, the guarantee might be expensive to implement if not capitalized early in the working phases in an era of aging populations, low birth rates, and deep financial crisis.