Econometric models for forecasting financial ratings

Credit Rating Agencies (CRA) provide ordinal assessments associated with the ability of companies, governments, institutions or financial assets, to meet debt obligations on time. These ratings are generated by CRAs as an 'objective' information about the financial health of their customers (although, in some cases, the CRAs provide ratings for third parties), bonds emissions, companies, institutions, and some other agents or financial products. This information is based on two components: the first is estimated from financial and economic sources, usually public, and the second on so called ‘qualitative’ data, which is part of the proprietary know-how of the agencies. But, how an independent investor or institution could evaluate the financial health of a company or a new issue? How can it be done without having to incur in the costs of arranging a contract for this purpose with a CRA? Some statistical methods have been employed with this aim, but as the emergency of Artificial Intelligence (AI) tools are becoming widespread, it is possible to model the rating of a company using public data. In fact, this is possible using public information, available to investors and to financial institutions. The answer to these questions lies in using statistical multivariate methods and AI models to estimate ratings of companies based on information available about their financial and economic data. Most of the literature about financial rating forecasting focuses on bond-rating prediction, and not in company’s ratings. The specification of econometric models to forecast the credit rating of a company involves using exogenous financial variables that produce a causal effect on their creditworthiness, and on their capacity to fulfill their future obligations. Public data are available for most of the companies that are traded on financial markets. In Bloomberg's database, this information and the ratings obtained from the main CRAs, are available. Long-term rates are divided in two main categories: investment and non-investment grades using a letter scale. Investment grades starts (in Moody’s scale) at ‘Aaa’, wich is related to the highest credit quality, and, consequently, the lowest expectation of default risk; they reflect and exceptionally strong capacity to fulfil their financial commitments, and they are not future events that can alter this situation; the ‘Aa’ rating is linked to very high credit quality, and low default risk. Following it is the ‘A’ level, associated to high credit quality and low possibility of default, but can be influenced by changes in the business environment. Finally, the ‘Baa’ level is associated with medium risk. The junk grade level starts at ‘Ba’ and ‘B’, which is associated to high risk of default, the ‘Caa’ and ‘Ca’ to highest risks, and finally, level ‘C’ is associated to firms in default, that is, with the presence of credit events of failure to pay interest or principal of a loan or security when due, and the debtor is unable to meet the legal obligation to debt repayment. The information provided by these values is ordinal, and not directly associated with probabilities of default. Moreover, more troubling is that the risk increase linked to a notch downgrade is not constant along the scale; more still, these variations are not comparable between them, and still less, they cannot be quantified. Some Multivariate Analysis methods used to estimate rates produce less accurate classifications; for example, Discriminant Analysis reaches only 20.7% of correct forecasted ratings, but only 16.7% when using jackknife methods to exclude one case at the time, as trial set. Multivariate logit (or similar models) are in the same range. While non-linear methods, such as Artificial Neural Networks, provide much better results, if a sufficiently large sample is used to train the model. The first main objective proposed is to elaborate models that can reproduce S&P's and Moody’s long-term ratings using publicity available data. The second main objective is to analyze the phenomenon called 'rate inflation', that is, the attribution of a certain level of rating above the 'objective level' which would be generate by an impartial observer. As Moody's ratings tend to be lower that those obtained by S&P's, these differences are considered as an evidence of rating inflation. This has been studied, also, in different economic sectors. Data employed come from two random samples of over one thousand companies each, for the years 2010 to 2018, and from thirteen economic sector

Structural Models in Corporate Social Responsibility: Attraction of Investment in Tunisia

The attraction of foreign direct investment is a common objective in developing countries, and this broad aim is carried out with different approaches in public policies. Corporate social responsibility is very common in international corporations, and it tends to produce a positive image for investors and in the surrounding society. This study aims to clarify the influence of the enhancement of corporate social responsibility by companies established in Tunisia as a consequence of the host country government general policies on the attraction of direct foreign investment. We propose the testing of a conceptual framework that describes this influence and explains the benefits of the social commitment, especially when it will be encouraged by public policies which can favor the attraction of foreign investments. The paper opted for an exploratory analysis on a sample of foreign companies with subsidiaries in the country. It contains a descriptive analysis, a study of the reliability of the scales of measurement and a principal components analysis. This approach is completed by an analysis of moment structures (AMOS) through a structural equation model linking the interactions of public policies with the development of strategies in social responsibility in companies, and their induced effects on the investment decisions in their subsidiaries. This approach tends to be associated with the sustainability and the commitment in the country, which is especially important in the present moment, with the political changes in the Maghreb region. With the models proposed, it has been shown that public policies, in addition to having a direct impact on investment decisions, can produce positive effects when they are carried out with the aim of promoting sustainable growth, and using indirect tools like the promotion of corporate social strategies in the companies that are already established in the country

Analysis of Wellbeing in Nongovernmental Organizations’ Workplace in a Developed Area Context

An extremely useful theoretical approach to understanding the nature of work, health, and wellbeing is the job demand–control (JDC) model and the job demand–control–support (JDCS) model. In order for professional workers in the nongovernmental organization (NGO) sector to do their job, it is necessary for them to have a feeling of wellbeing. Despite this, in Europe, studies regarding the effects of the JDCS model in relation to workers’ wellbeing have not been carried out. This study is expected to fill this important gap in research by analyzing the relationship of wellbeing with work demands, work control, and social support. In order to corroborate the proposed hypotheses, an analysis of these constructs in employees in European nongovernmental organizations (NGOs) was developed and, using structural equation models, these relationships were tested. The results confirm the main hypothesis of the job demand–control–support (JDCS) model and the causal relationship among physical and psychological demands, work control, and support from supervisors and colleagues with the level of employee wellbeing

Moody’s Ratings Statistical Forecasting for Industrial and Retail Firms

Long-term ratings of companies are obtained from public data plus some additional nondisclosed information. A model based on data from firms’ public accounts is proposed to directly obtain these ratings, showing fairly close similitude with published results from Credit Rating Agencies. The rating models used to assess the creditworthiness of a firm may involve some possible conflicts of interest, as companies pay for most of the rating process and are, thus, clients of the rating firms. Such loss of faith among investors and criticism toward the rating agencies were especially severe during the financial crisis in 2008. To overcome this issue, several alternatives are addressed; in particular, the focus is on elaborating a rating model for Moody’s long-term companies’ ratings for industrial and retailing firms that could be useful as an external check of published rates. Statistical and artificial intelligence methods are used to obtain direct prediction of awarded rates in these sectors, without aggregating adjacent classes, which is usual in previous literature. This approach achieves an easy-to-replicate methodology for real rating forecasts based only on public available data, without incurring the costs associated with the rating process, while achieving a higher accuracy. With additional sampling information, these models can be extended to other sectors

Ten Years of Airbnb Phenomenon Research: A Bibliometric Approach (2010–2019)

The interest in the Airbnb phenomenon is represented in the fast growth of publications indexed in the Web of Science (WoS) since the research inception of this topic in 2010. However, there are no studies that analyze the incidence of this phenomenon from a bibliometric approach using WoS. Therefore, this paper aims to quantify the incidence and composition of the Airbnb phenomenon through bibliometrics taken it as a data source. To achieve this aim, the WoS statistical instruments and the bibliometric tool VOSviewer are used. The results obtained, such as the number of articles and citations per year, the main categories of these articles, the nationalities of the authors, the most productive institutions, the sources and authors in terms of publications, and the H-Core of the most cited articles, are presented. Finally, concept maps are exposed, representing the relatedness of co-authorship and co-citation among authors, as well as the co-occurrence of the keywords in the articles analyzed. Satisfaction, trust, and innovation appear as the main research lines. This paper can be useful for academics and professionals, giving them a holistic overview of the topic, identifying new research areas, or as an objective manner to literary review approaches

Workplace Situation and Well-Being of Ecuadorian Self-Employed

Due to novel coronavirus 2019 (COVID-19), the labor market is going to undergo a profound restructuring. The creation of a new labor paradigm by all stakeholders is essential. This document contributes to the current political and social debates about self-employment, the need for economic growth, and how these labor measures, which are deeply institutionalized, need a change of attitude for an adequate job reconstruction in terms of welfare and sustainability. Currently, policy makers are proposing actions and policies because the new labor paradigm is being designed in the countries of Latin America. This research aims to analyze the JDCS model (Job Demand-Control-Support) and well-being in the self-employed in Ecuador. Unlike previous studies, this research takes a comprehensive approach by considering this theoretical model and the figure of the self-employed in terms of well-being. The logistic model, using cases of more than one thousand workers, generated estimated results that indicate the existence of a significant effect of physical and psychological demands at work on the balance between well-being and the management of angry clients; the speed of execution; and the complexity of the tasks. Regarding labor control, the ability to solve problems and make decisions for the company are detected as influencing factors; finally, social support is another factor influencing global well-being for the self-employed. These results show that with an effective management of the self-employed labor environment, it is possible to achieve an adequate level of workplace satisfaction

Segmentation Based on the Gastronomic Motivations of Tourists: The Case of the Costa Del Sol (Spain)

Tourist destinations increasingly sustain their consolidation, promotion, and development from gastronomy. This research aims to contribute to the scientific literature analyzing the relationship between tourism and gastronomy for the specific case of the Costa del Sol (Spain) from tourists’ experiences of different nationalities who have visited the area. The methodology has been based on questionnaires applied to foreign travellers, after the gastronomic tasting of lunch or dinner in typical beach restaurants, called “chiringuitos”. Results show the existence of different segments of tourists based on their attitude towards local cuisine. Three groups have been identified, with different gastronomic predispositions and knowledge, and it is concluded that there are different levels of satisfaction and motivations in tourists, as they are identified in one segment or the other

New types of accommodation: Tourist apartments and determining factors of the daily rate

El reciente cambio de paradigma en el sector turístico debido al uso generalizado de las tecnologías de la comunicación ha traído consigo un incremento en la facilidad para efectuar reservas por parte del consumidor. Asimismo, antes de la irrupción del COVID-19, se ha asistido a un sostenido incremento en el número de turistas acompañado del aumento en la oferta de distintos tipos de alojamiento turístico, entre los que cabe destacar nuevas modalidades alejadas de los convencionales hoteles, tales como los apartamentos turísticos. El objetivo de este estudio es conocer los determinantes de valoración del precio de la estancia diaria de esta nueva modalidad de alojamiento mediante un modelo econométrico utilizando el método de precios hedónicos y empleando a Booking.com como principal fuente de datos. La ciudad seleccionada para el análisis ha sido Sevilla debido al notable auge de este tipo de alojamiento que ha experimentado en años recientes y por ser la urbe de mayor tamaño del sur de España. Variables referidas a la tipología del inmueble, su ubicación, su tamaño, sus amenidades, así como factores relacionados con la estacionalidad y los eventos especiales de la ciudad aparecen como relevantes en el modelo. El grado de ajuste obtenido en el mismo es alto, así como su poder predictivo, pudiendo ser útil para estimar el precio de la estancia por parte de empresarios, clientes, así como las distintas plataformas online en las que se comercializa esta modalidad de alojamiento, una vez conocidas un conjunto de características internas del inmueble, de su entorno y de estacionalidad.The recent paradigm shift in the tourism sector due to the widespread use of communication technologies has facilitated the booking process for consumers. Similarly, before the outbreak of COVID-19, there was a sustained increase in the number of tourists accompanied by an increase in the offer of different types of tourist accommodation, including new types other than conventional hotels, such as tourist apartments. The aim of this research is to reveal the determinants of the price of the daily rate in this new type of accommodation based on an econometric model using the hedonic price method and using Booking.com as the main source of data. The city selected for the analysis is Seville due to the notable increase in this type of accommodation experienced in the city in recent years and because it is the largest city in Southern Spain. Variables referring to the type of property, its location, its size, its amenities, and factors related to seasonality and special events in the city appear as relevant in the model. The degree of adjustment obtained in the model is high, as is its predictive power and it could be useful for estimating the daily rate for hosts, clients and the different online platforms through which this type of accommodation is marketed, after determining a series of internal characteristics of the property, and those relating to its environment and seasonality