Francisco José dos Santos Alves

Transparência no setor público: uma análise dos relatórios de gestão anuais de entidades públicas federais no ano de 2010

The present study analyzes the level of public transparency in the annual reports of federal public bodies and the incentives (political, institutional, governmental, social and financial) which can affect the disclosure of public information. It approached the Agency Theory and the need for public accountability in the disclosure of information, since government managers may provide incomplete information (agency conflict). Accordingly a greater transparency of public information may serve as a way of approaching the principal (citizens) and the agent (public officer). We carried out an empirical research, quantitative, which analyze the level of transparency presented in the 2010´s annual reports of 115 federal public entities. For this purpose, an index of federal public transparency was constructed, based on international studies, in order to verify the level of disclosure presented on the annual reports and the incentives that affect disclosure. The results indicate a moderate level of public transparency (48%), deficiency of compliance with mandatory disclosure (80%) and low adherence to voluntary disclosure practices (19%). Regarding incentives to disclosure, a positive relationship of the entity type, accessibility and personnel demographic with the public transparency index was observed, while public bureaucracy showed a significant relationship, but negative. Meanwhile the size, size of core management, budgetary revenues and federal dependency does not influence the disclosure of public information in the annual reports.

Seleção de atributos na previsão de insolvência: aplicação e avaliação usando dados brasileiros recentes

ABSTRACT Bankruptcy prediction may have great utility to financial and nonfinancial institu-tions with regard to take in advance the best possible decisions regarding loans or investments. In specific literature, many bankruptcy prediction models have made use of data mining . The preprocessing step is important to select good qual-ity data for use in mining operations. Still, although the selection of attributes can be very beneficial to pre-select representative data to improve the forecast perfor-mance end, it is not known which method is the best selection. This work has as main objective to compare two approaches for evalua ting subsets of attributes: Filter and Wrapper. Despite being based on data mining techniques and widely used in the step of feature selection in bankruptcy prediction models, these tech-niques are rarely used to treat data from financial statements of Brazilian com-panies. Therefore the empirical basis of this study consists of a sample of Brazi-lian industrial and commercial enterprises, collecting data for the period 2004 to 2011. The results indicated that, in this sample, the filter approach was more effi-cient, providing better classification results both for logistic regression (91,80%) and for neural networks (93,98%). It was shown also the importance of making explicit the evaluation stage of the selection of attributes for achieving better re-sults in applications of data mining techniques to predict insolvency. A specific conclusion about the advantages of the filter approach shows that it may be pre-ferred to assess the attributes that will make predictive models.

Disclosure in public sector: an analysis of the level of disclosure in the annual reports of Brazilian federal government bodies in the year 2010

The present study analyzes the level of public transparency in the annual reports of federal public bodies and the incentives (political, institutional, governmental, social and financial) which can affect the disclosure of public information. It approached the Agency Theory and the need for public accountability in the disclosure of information, since government managers may provide incomplete information (agency conflict). Accordingly a greater transparency of public information may serve as a way of approaching the principal (citizens) and the agent (public officer). We carried out an empirical research, quantitative, which analyze the level of transparency presented in the 2010´s annual reports of 115 federal public entities. For this purpose, an index of federal public transparency was constructed, based on international studies, in order to verify the level of disclosure presented on the annual reports and the incentives that affect disclosure. The results indicate a moderate level of public transparency (48%), deficiency of compliance with mandatory disclosure (80%) and low adherence to voluntary disclosure practices (19%). Regarding incentives to disclosure, a positive relationship of the entity type, accessibility and personnel demographic with the public transparency index was observed, while public bureaucracy showed a significant relationship, but negative. Meanwhile the size, size of core management, budgetary revenues and federal dependency does not influence the disclosure of public information in the annual reports.

A EMENDA CONSTITUCIONAL 95 E SEUS EFEITOS

O conturbado cenario politico-economico impulsionou o Estado a instituir Emenda Constitucional 95, originada do projeto de emenda constitucional (PEC) 55/2016, limitando gastos publicos. Tal medida dividiu opinioes entre os favoraveis e contrarios. O objetivo desta pesquisa e avaliar os impactos da emenda e identificar, sob o prisma das Teorias da Agencia e Regulacao, a quem tal medida beneficia. Os metodos utilizados no estudo foram: descritivos, bibliograficos, documentais e de abordagem quantitativa. Simulou-se o cenario de sua adocao em 2010 afim de determinar seus possiveis efeitos em 2015 e, como resultado, observou-se que as despesas primarias crescem acima da inflacao. Verificou-se que ocorre uma tentativa de regulacao do Estado para controlar o endividamento publico por meio de uma reducao das despesas primarias, de forma indiferente entre as diversas funcoes de governo. Entretanto, o impacto de sua adocao afeta de maneira distinta as diversas areas de acao governamentais, prejudicando algumas mais do que outras. Concluiu-se que atraves da Emenda foi atendido o grupo que e favoravel a reducao do endividamento publico e ao estimulo dos negocios privados, ainda que isto represente uma diminuicao na atuacao do Estado e, consequentemente, uma limitacao no atendimento as necessidades da populacao.

Testando o Triângulo de Cressey no contexto da convergência às normas internacionais de contabilidade: um estudo empírico sobre comportamento ético de profissionais de contabilidade

The aim of this study was to verify how the accounting professional is positioned in relation to moral dilemmas involving torts and Triangle Cressey in the exercise of their professional activity in the convergence to international standards of accounting environment. We sought to identify which components of the triangle and which individual characteristics influence the intention of this act professional. We also assessed whether there was flexibility in the choice of accounting practices brought about by the convergence of international accounting standards. The results corroborate the model shown in Cressey in that it suggested that the proposed scenarios accounting professionals would take advantage of a moment of exchanging the firm to make adjustments that will benefit the Companys results (Opportunity), trying to justify this procedure because it is a common practice in the market (Rationalization), trying to turn something into something unethical acceptable. It was verified that the variables act of judgment and severity of the act were also statistically significant in relation to the intention to act the accounting professional. Have the flexibility not statistically significant.

Transparencia en el sector público: un análisis del nivel de transparencia de los reportes anuales de las entidades públicas federales en el año de 2010

The present study analyzes the level of public transparency in the annual reports of federal public bodies and the incentives (political, institutional, governmental, social and financial) which can affect the disclosure of public information. It approached the Agency Theory and the need for public accountability in the disclosure of information, since government managers may provide incomplete information (agency conflict). Accordingly a greater transparency of public information may serve as a way of approaching the principal (citizens) and the agent (public officer). We carried out an empirical research, quantitative, which analyze the level of transparency presented in the 2010´s annual reports of 115 federal public entities. For this purpose, an index of federal public transparency was constructed, based on international studies, in order to verify the level of disclosure presented on the annual reports and the incentives that affect disclosure. The results indicate a moderate level of public transparency (48%), deficiency of compliance with mandatory disclosure (80%) and low adherence to voluntary disclosure practices (19%). Regarding incentives to disclosure, a positive relationship of the entity type, accessibility and personnel demographic with the public transparency index was observed, while public bureaucracy showed a significant relationship, but negative. Meanwhile the size, size of core management, budgetary revenues and federal dependency does not influence the disclosure of public information in the annual reports.

Selección de atributos en previsión de insolvencia: aplicación y evaluación utilizando datos recientes de Brasil

ABSTRACT Bankruptcy prediction may have great utility to financial and nonfinancial institu-tions with regard to take in advance the best possible decisions regarding loans or investments. In specific literature, many bankruptcy prediction models have made use of data mining . The preprocessing step is important to select good qual-ity data for use in mining operations. Still, although the selection of attributes can be very beneficial to pre-select representative data to improve the forecast perfor-mance end, it is not known which method is the best selection. This work has as main objective to compare two approaches for evalua ting subsets of attributes: Filter and Wrapper. Despite being based on data mining techniques and widely used in the step of feature selection in bankruptcy prediction models, these tech-niques are rarely used to treat data from financial statements of Brazilian com-panies. Therefore the empirical basis of this study consists of a sample of Brazi-lian industrial and commercial enterprises, collecting data for the period 2004 to 2011. The results indicated that, in this sample, the filter approach was more effi-cient, providing better classification results both for logistic regression (91,80%) and for neural networks (93,98%). It was shown also the importance of making explicit the evaluation stage of the selection of attributes for achieving better re-sults in applications of data mining techniques to predict insolvency. A specific conclusion about the advantages of the filter approach shows that it may be pre-ferred to assess the attributes that will make predictive models.

Attribute selection in bankruptcy prediction: application and evaluation using recent brazilian data

ABSTRACT Bankruptcy prediction may have great utility to financial and nonfinancial institu-tions with regard to take in advance the best possible decisions regarding loans or investments. In specific literature, many bankruptcy prediction models have made use of data mining . The preprocessing step is important to select good qual-ity data for use in mining operations. Still, although the selection of attributes can be very beneficial to pre-select representative data to improve the forecast perfor-mance end, it is not known which method is the best selection. This work has as main objective to compare two approaches for evalua ting subsets of attributes: Filter and Wrapper. Despite being based on data mining techniques and widely used in the step of feature selection in bankruptcy prediction models, these tech-niques are rarely used to treat data from financial statements of Brazilian com-panies. Therefore the empirical basis of this study consists of a sample of Brazi-lian industrial and commercial enterprises, collecting data for the period 2004 to 2011. The results indicated that, in this sample, the filter approach was more effi-cient, providing better classification results both for logistic regression (91,80%) and for neural networks (93,98%). It was shown also the importance of making explicit the evaluation stage of the selection of attributes for achieving better re-sults in applications of data mining techniques to predict insolvency. A specific conclusion about the advantages of the filter approach shows that it may be pre-ferred to assess the attributes that will make predictive models.