Search results

The purpose of this paper is to analyze which key financial factors are appropriate for measuring a credit rating score for family firms. In the recent literature, there exists a vast number of studies which evaluates performance differences between family and non-family firms (NFF). However an analysis with regards to a distinction between credit rating scores of family-orientated businesses compared to their counterparts in Austria has not been examined so far.

In order to bridge this research gap, an empirical model based on Moody’s credit rating methodology is used to address these issues. Therefore, the relevant data were taken from the 600 largest, both listed and non-listed, companies of Austria. The statistical measurements refer to a comparison of the means resulting from quantitative rating categories (profitability, leverage structure, liquidity development and firm size).

The results of this empirical research show that family firms achieve better values in profitability, leverage structure and liquidity development based on credit rating scores. Only firm size represents no significant differences between family and NFF.

This study will contribute to the existing literature in the academic area of family business research and offers a framework for future empirical analysis in this field. Furthermore, this paper provides important information that will help both family and NFF accomplish their financial strategies related to credit rating transitions.

This paper aims to analyse the similarities and differences in the methodologies adopted by corporate social responsibility (CSR) rating agencies.

The authors gather secondary and primary evidences of practices from selected agencies on the methodologies and criteria they rely upon to assess a firm’s CSR performance.

The authors find not only evidence of similarities in the methodologies adopted by the CSR rating agencies (e.g. the use of environment, social and governance themes, exclusion criteria, adoption of positive criteria, client/“customised” input, quantification) but also several elements of differences, namely, in terms of the thresholds for exclusion, transparent vs confidential approach, industry-specific ratings and weights for each dimension. Drawing from Sandberg et al.’s (2009) conceptualisations, the authors tentatively argue that this mixed picture may reflect competing organisational pressures to adopt a differentiation approach at the strategic and practical levels whilst recognising, and incorporating, the “globalising” tendencies of the CSR business at the terminological levels.

Although these data are based on a relatively small number of agencies, the findings and analysis convey some implications for users of CSR ratings and policymakers, particularly in light of the recent Paris 2016 Agreement on Climate Change and the increased emphasis on the monitoring of social, environmental and governance performance.

The authors contribute to the literature by highlighting how key intermediate rating organisations operationalise notions of CSR.

The purpose of this paper is to investigate the role and responsibility of credit rating agencies in promoting soundness and integrity, especially in the course of their business activities.

The paper describes, and uses, the framework for the activities of credit rating agencies introduced by the International Organization of Securities Commissions (IOSCO), in order to give effect to this investigation.

Credit rating agencies have implemented the provisions of the Code of Conduct Fundamentals for Credit Rating Agencies of the IOSCO on the quality and integrity of the rating process, to the extent of the resources available to them.

The main source of data is the information collected by the IOSCO from nine credit rating agencies, including the main three, on the quality and integrity of their rating processes. The absence of triangulation of research methods limits the robustness of the findings.

The paper addresses a specific aspect of the credit ratings story since the financial crisis on which there is currently little in the literature. It also focuses upon the actions of credit rating agencies, rather than on how these organisations are, or should be, regulated.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

The purpose of this paper is to present a methodology for assessing, in quantifiable terms, the reduction in environmental impacts achieved by applying different credits of sustainability rating systems in building construction projects.

Sustainability rating systems are developed in various regions to evaluate construction projects with respect to their environmental performance. Although implementation of rating systems had a recognized effect on reducing environmental impact of construction projects, there is no objective and quantifiable evidence that the approaches recommended by these rating systems to achieve the required certification lead to optimum environmental results. This paper presents a methodology that utilizes life cycle analysis (LCA) as a powerful and objective tool to validate the way rating systems evaluate project performance. The Qatar Sustainability Assessment System (QSAS), recently developed in the State of Qatar by Gulf Organization for Research and Development (GORD), is chosen as a case study to illustrate application of the developed methodology. Environmental impacts due to implementation of QSAS credits are calculated for one project in Qatar, which is currently under construction.

Results reveal possible use of LCA as a tool for evaluating the effectiveness of rating systems. For the QSAS case study, findings reveal indications of over and, in some instances, under estimation of the weights assigned to some credits and the difficulty in the quantification of the impacts of other credits, which indicates the need for reconsideration of these weights to improve effectiveness of the implementation of these credits.

The proposed methodology stands as a step toward the enhancement and rationalization of the currently used building sustainability ratings system.

The purpose of this paper is to test the hypothesis that major credit rating agencies (CRAs) have been inconsistent in assessing the implications of monetary union membership for sovereign risks. It is frequently argued that CRAs have acted procyclically in their rating of sovereign debt in the European Monetary Union (EMU), underestimating sovereign risk in the early years and over-rating the lack of national monetary sovereignty since the onset of the Eurozone debt crisis. Yet, there is little direct evidence for this so far. While CRAs are quite explicit about their risk assessments concerning public debt that is denominated in foreign currency, the same cannot be said about their treatment of sovereign debt issued in the currency of a monetary union.

While CRAs are quite explicit about their risk assessments concerning public debt that is denominated in foreign currency, the same cannot be said about their treatment of sovereign debt issued in the currency of a monetary union. This paper examines the major CRAs’ methodologies for rating sovereign debt and test their sovereign credit ratings for a monetary union bonus in good times and a malus, akin to the “original sin” problem of emerging market countries, in bad times.

Using a newly compiled dataset of quarterly sovereign bond ratings from 1990 until 2012, the panel regression estimation results find strong evidence that EMU countries received a rating bonus on euro-denominated debt before the European debt crisis and a large penalty after 2010.

The crisis has brought to light that EMU countries’ euro-denominated debt may not be considered as local currency debt from a rating perspective after all.

In addition to quantifying the local currency bonus and malus, this paper shows the fundamental problem of rating sovereign debt of monetary union members and provide approaches to estimating it over time.

There is growing recognition that numerous business drivers contribute to financial performance and investment returns but they are not included in a company's profit and loss statements. In the investment industry, these wider sets of value drivers are known as environment-social- governance (ESG) factors. A small number of specialized ESG rating agencies provide information to investors about the extent to which firms' behaviors are socially responsible. However, a major criticism of these rating agencies is the lack of transparency in their methods. This paper aims to examine the issues of subjectivity, transparency and uniformity of ESG ratings by exploring the methods used to assess ethics performance by an Australian rating agency.

A case study was conducted on an Australian ESG rating provider, Regnan. The data for the analysis were sourced from internal Regnan documents.

The paper found that a level of subjectivity is inevitable in ESG ratings and the call for uniformity may inhibit innovation, but these issues can be addressed by increased transparency of the rating methods.

Further research is required to understand what level and, combination of, uniformity and transparency is sufficient to satisfy stakeholder requirements for ESG information.

The discussion of the factors underlying the ethics performance rating may prompt more open and transparent debate on how to assess ethical performance of companies, and increase investor confidence in ESG ratings. It may also provide more direction to companies on how to strengthen their ethical performance.

There is growing recognition that numerous business drivers contribute to financial performance and investment returns but they are not included in a company's profit and loss statements. These “ESG” factors can account for up to 66 percent of the market value of globally listed companies. In response to calls for more transparency on how ESG factors are assessed, and how ethical performance is appraised, this paper attempts to lift the veil on ESG rating methods.

This study aims to identify the determinants of Malaysian corporate Sukuk rating and attempts to find out which determinant has the most significant impact.

The framework tries to establish a relationship between firm’s size, profitability, Sukuk guarantee status and types of Sukuk with Sukuk rating from the perspective of Agency Theory and Information Asymmetry Theory. The data consist of 43 Sukuk issuances from 2006 to 2015. Multinomial Logistic Regression Model is then used to find out the significant determinants of Sukuk rating.

The study found that only three variables significantly impact Sukuk rating. The results show that a guaranteed Sukuk Ijarah or a guaranteed Sukuk Musyarakah that is issued by a highly profitable firm has a higher likelihood of getting rating AAA or rating AA as compared to getting rating A. A type of Sukuk, particularly Sukuk Murabahah, is the most significant variable influencing Sukuk rating. However, firm size is not a significant determinant of Sukuk rating in the context of this study.

The first limitation of the study is the relatively small sample size. Second, the study only tested four independent variables.

Several implications are derived from the results of the study. First, new firms that are planning to issue Sukuk should consistently maintain a high level of profit and consider issuing debt-based Sukuk to ensure that the issued Sukuk have higher rating. To increase the likelihood of getting higher rating, they should also consider providing a third-party guarantor. As for existing Sukuk issuers that are in lower rating category, they should increase their profitability to be upgraded to higher rating category. Second, risk-adverse investors should invest in highly profitable, guaranteed and debt-based Sukuk, as these Sukuk are likely to be in higher rating category and provide guarantee in terms of capital payments during liquidation or bankruptcy. Third, to reduce information asymmetry, policymakers should make it compulsory for all Sukuk issuers to have their Sukuk rated annually and make it mandatory for all rating agencies in Malaysia to publish their Sukuk rating methodologies.

This paper helps to expand the limited existing literature about the determinants of Sukuk rating, particularly for the Malaysian corporate Sukuk.

This paper aims to study the determinants of the sovereign debt ratings provided by the 3 main rating agencies for 32 European countries. It verifies the clusters of countries existing for each of the agencies, considering regional bias, and then analyzes whether the determinants were different before and after the global financial crisis. It also aims to explain how the determinants are taken into account for rich and developing countries, using a sample for the period between 2001 and 2008 and the period between 2009 and 2016.

To this purpose, this paper performs panel data estimation using an ordered Probit approach.

This method shows that for developing countries after the crisis, the relevant explanatory variables are the unemployment rate and the presence in the Eurozone. For rich countries, the inflation rate is pivotal after the crisis period.

This paper is the first to use a clustering methodology within sovereign debt rating literature, grouping the countries into cohesive clusters according to their sovereign debt ratings along with the proposed time frame. Moreover, it explains, which countries belong to strong or weak groups, according to the rating agencies under discussion; and, in these groups, it identifies the sovereign rating determinants.