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Credit rating agencies (CRAs) are perceived as highly influential in the financial system since their announcements can affect several players in the financial markets, from big private financial and non-financial companies and their financial markets experts to sovereign states. In this sense, this study investigates whether sovereign credit news issued by CRAs (measured by comprehensive credit rating (CCR) variables) affect the uncertainties about the exchange rate in the future (captured by the disagreement about exchange rate expectations). The study is relevant once there is evidence indicating that CRAs' assessments are responsible for affecting international capital flows and, thus, sovereign rating changes can affect the expectations formation process regarding the exchange rate. In addition, there is evidence indicating that the disagreement about exchange rate expectations affects the disagreement about inflation expectations, which brings consequences to policymakers.

The dependent variables are the disagreement in expectations about the Brazilian exchange rate for different forecast horizons, 12, 24 and 36 months ahead and the first principal component of theses series. On the other hand, the CCR variables are built upon the long-term foreign-currency Brazilian bonds ratings, outlooks and credit watches provided by the main CRAs. Estimates are obtained using ordinary least squares (OLS) and generalized method of moments (GMM); a dynamic analysis is performed using vector-autoregressive (VAR) through impulse-response functions.

Negative (positive) sovereign credit news, given by a rating downgrade (upgrade) and/or a negative (positive) outlook/watch status, increase (decrease) the disagreement about exchange rate expectations. This result holds for all disagreement and CCR variables.

The study brings practical implications to both private agents (mainly financial market experts) and policymakers. An important practical implication of the study concerns the ability of CRAs to affect the expectations formation process of financial market experts regarding the future behavior of the exchange rate. When a CRA issues a signal of improvement in a country's sovereign rating, this signal reflects the perception of improvement in macroeconomic fundamentals and reduction of uncertainties about the country's ability to honor its financial obligations, which therefore, facilitates the expectations formation process, causing a reduction in the disagreement about the exchange rate expectations. With respect to the consequences for policymakers, they will have more difficulty in guiding expectations in a country with a worse sovereign risk rating, where agents have difficulties in forming expectations and the disagreement in expectations is greater.

The study is the first to analyze the impact of CRAs' announcements on the disagreement about exchange rate expectations. Moreover, it connects the literature that investigates the effects of sovereign credit news on the economy with the literature that examines the main determinants of disagreement in expectations about macroeconomic variables.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.

We present a critical literature review debating Brazilian research on social and environmental accounting (SEA). The aim of this study is to understand the role of politics in the construction of hegemonies in SEA research in Brazil. In particular, we examine the role of hegemony in relation to the co-option of SEA literature and sustainability in the Brazilian context by the logic of development for economic growth in emerging economies. The methodological approach adopts a post-structural perspective that reflects Laclau and Mouffe’s discourse theory. The study employs a hermeneutical, rhetorical approach to understand and classify 352 Brazilian research articles on SEA. We employ Brown and Fraser’s (2006) categorizations of SEA literature to help in our analysis: the business case, the stakeholder–accountability approach, and the critical case. We argue that the business case is prominent in Brazilian studies. Second-stage analysis suggests that the major themes under discussion include measurement, consulting, and descriptive approach. We argue that these themes illustrate the degree of influence of the hegemonic politics relevant to emerging economics, as these themes predominantly concern economic growth and a capitalist context. This paper discusses trends and practices in the Brazilian literature on SEA and argues that the focus means that SEA avoids critical debates of the role of capitalist logics in an emerging economy concerning sustainability. We urge the Brazilian academy to understand the implications of its reifying agenda and engage, counter-hegemonically, in a social and political agenda beyond the hegemonic support of a particular set of capitalist interests.

This paper aims to investigate Lean Six Sigma (LSS) in the Brazilian context, seeking to identify its main characteristics and opportunities for future research.

This study focuses on a literature review in the area of production engineering and operations management, where 104 relevant scientific publications were identified.

The results show that the most important critical success factor for integrating LSS in Brazil is top management support and commitment. LSS integration occurs predominantly in large industrial companies, being incipient in small and medium-sized enterprises. In general, there is no structured way of applying LSS. A standard framework for LSS is still lacking.

This study is limited to a sample that only comprises Brazilian scientific studies.

Professionals and practitioners can understand the evolution of LSS through practical applications and the main LSS tools used in both the industrial and services sectors. It also points out the critical success factor for the implementation of LSS. The study highlights several roadmaps for LSS implementation adopted by large and modern Brazilian automotive industries based on a robust technological base. This study also contributes to expanding the evidence base of LSS application, both in Brazil and in other countries.

Some suggestions are proposed to clarify the structure and complexity of integrated implementation of LP and SS as well as expand the LSS application in small and medium-sized enterprises. This study is the first to discuss the current situation of LSS in Brazil and provide suggestions to expand LSS in the country. Comparisons of Brazilian LSS literature review with researches of others countries are also presented.