Search

Food production is an increasingly relevant issue in the current framework associated with food and water security and future years projections. In addition, the production of organic food has gained significance in recent years, revealing a growing change in the population's consumption habits. The Communities Supported Agriculture (CSAs) play an important role in enabling productive areas for planting crops in agroecological and biodynamic standards. Given this, this study aimed to investigate the relationship between different CSAs variables located in the Southeastern region of Brazil to validate or not the hypotheses created. Thus, the study was designed as a descriptive research and quantitative approach, using an inductive logic survey. In addition, the methodology was set up with the support of the Structural Equation Modeling technique. The study confirmed the hypothesis (H1) that socioeconomic characteristics positively influence CSAs’ performance. The limitations were associated with the method of data collection and the difficulties imposed by the Covid-19 pandemic.

To achieve Sustainable Development Goal 7 (SDG7) and improve energy management efficiency, it is essential to develop models and methods to forecast and enhance the process accurately. These tools are crucial in shaping the national policymakers’ strategies and planning decisions. This study utilizes data envelopment analysis (DEA) and bootstrap computational methods to evaluate Brazil’s energy efficiency from 2004 to 2023. Additionally, it compares seasonal autoregressive integrated moving average (SARIMA) models and autoregressive integrated moving average (ARIMA) forecasting models to predict the variables’ trends for 2030. One significant contribution of this study is the development of a methodology to assess Brazil’s energy efficiency, considering environmental and economic factors to formulate results. These results can help create policies to make SDG7 a reality and advance Brazil’s energy strategies. According to the study results, the annual energy consumption rate is projected to increase by an average of 2.1% by 2030, which is accompanied by a trend of GDP growth. By utilizing existing technologies in the country, it is possible to reduce electricity consumption costs by an average of 30.58% while still maintaining the same GDP value. This demonstrates that sustainable development and adopting alternatives to minimize the increase in energy consumption can substantially impact Brazil’s energy sector, improving process efficiency and the profitability of the Brazilian industry.

The global transition towards environmentally friendly energy sources plays a major role in addressing both energy security and climate change. Brazil is at the forefront of this transition due to its rich natural resources and increasing investments in biofuels. Therefore, this investigation examines the consumption patterns and interactions between ethanol, primarily sourced from sugarcane, and gasoline within Brazil’s energy framework. Ethanol’s renewability, reduced environmental impact, and superior combustion characteristics position it as a feasible substitute for traditional fossil fuels. Nonetheless, obstacles like competition for land use and inadequate distribution infrastructure impede its widespread acceptance. This study explores the economic interaction between ethanol and gasoline, focusing on pricing dynamics and regional influences. Using consumer preferences and the accessibility of ethanol, this research identifies a range of price ratios within which consumer preferences shift from gasoline to ethanol in various Brazilian regions. The study also classifies Brazilian states into three distinct ranges based on the ethanol-to-gasoline price ratio in 2023 for a granular analysis of the economic dynamics influencing fuel choice. The research identifies states with competitive and dominant ethanol markets by examining the interplay between ethanol market share, fuel prices, and the adoption of flex-fuel vehicles (FFVs) in the country. Lastly, the findings support the importance of regional economic conditions and the influence of price ratios on consumer behavior, highlighting that ethanol’s market share does not always correlate with favorable pricing.

Volatility reflects the degree of variation in a time series, and a measurement of the stock performance in the energy sector can help one understand the pattern of fluctuations within this industry, as well as the factors that influence it. One of these factors could be the COVID-19 pandemic, which led to extreme volatility within the stock market in several economic sectors. It is essential to understand this regime of volatility so that robust financial strategies can be adopted to handle it. This study used stock data from the Yahoo! Finance API and data from the energy-price database from the US Energy Information Administration to conduct a comparative analysis of the volatility in the energy sector in Brazil and in the United States, as well as of the energy prices in California. The volatility in these time series were modeled using GARCH. The stock volatility regimes, both before and after COVID-19, were identified with a Markov switching model; the spillover index between the energy markets in the USA and in Brazil was evaluated with the Diebold–Yilmaz index; and the causality between the energy stock price and the energy prices was measured with the Granger causality test. The findings of this study show that (i) the volatility regime introduced by COVID-19 is still prevalent in Brazil and in the USA, (ii) the changes in the energy market in the US affect the Brazilian market significantly more than the reverse, and (iii) there is a causality relationship between the energy stock markets and the energy prices in California. These results may assist in the achievement of effective regulation and economic planning, while also supporting better market interventions. Also, acknowledging the persistent COVID-19-induced volatility can help with developing strategies for future crisis resilience.

The use of biofuels represents a promising means of achieving a sustainable future and offers considerable economic and environmental benefits. Since they are derived from organic sources, such as vegetable oils and animal fats, biofuels can mitigate the effects of greenhouse gas emissions, improve air quality, support local agriculture, create employment opportunities, and enhance energy security by reducing dependence on fossil fuels. However, introducing these alternative fuels to the aviation sector remains a significant challenge. Thus, it is vital to investigate the potential of sustainable aviation fuel (SAF) and discover how to overcome the technological obstacles to its integration into mainstream aviation to attain broader decarbonization objectives. This article seeks to contribute to a discussion about SAF by examining how it has evolved and its connections to related patents. This article is a comprehensive study of biofuel innovation, highlighting the complex relationships between academia, industry, and other stakeholders. It is hoped that the findings from this study will provide a clearer understanding of the catalysts involved in SAF innovation and provide valuable insights for policymakers, academics, and professionals in the field who are committed to shaping the trajectory of sustainable energy technologies in the future.

This article presents an innovative approach to video steganography called Stego-STFAN, as by using a cheap model process to use the temporal and spatial domains together, they end up presenting fine adjustments in each frame, the Stego-STFAN had a PSNRc metric of 27.03 and PSNRS of 23.09, which is close to the state-of-art. Steganography is the ability to hide a message so that third parties cannot perceive communication between them. Thus, one of the precautions in steganography is the size of the message you want to hide, as the security of the message is inversely proportional to its size. Inspired by this principle, video steganography appears to expand channels further and incorporate data into a message. To improve the construction of better stego-frames and recovered secrets, we propose a new architecture for video steganography derived from the Spatial-Temporal Adaptive Filter Network (STFAN) in conjunction with the Attention mechanism, which together generates filters and maps dynamic frames to increase the efficiency and effectiveness of frame processing, exploiting the redundancy present in the temporal dimension of the video, as well as fine details such as edges, fast-moving pixels and the context of secret and cover frames and by using the DWT method as another feature extraction level, having the same characteristics as when applied to an image file.

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033.

The Internet of Things, Smart Devices, Information Systems, and Cloud Services have led to a digital transformation of companies. Such revolution has been accompanied by a huge amount of data available for companies, posing the growing challenge of data breaches. However, data breaches are not just a concern and complication for security experts; they also affect clients, stakeholders, organizations, and businesses, as stated by the Privacy Rights Clearinghouse. Thus, this study provides insights into data breaches faced by companies listed on the New York Stock Exchange and NASDAQ. The study found that hacking/IT incidents are the forms of attack with greater impact in data breaches, followed by unauthorized internal disclosures. The frequency of data breaches, the magnitude of exposed records, and financial losses due to breached records are increasing rapidly. Data from the companies listed on the stock exchange is regarded as being highly valuable. This has become a significant lure for the misappropriation and pilferage of data. Addressing this anomaly, the paper employs statistical visualizations of the data to shed light on these incidents and assess their consequences on the affected companies and individuals whose data was compromised. This work aims to contribute to a comprehensive understanding of data breaches and empower organizations to safeguard against them proactively by conducting this multifaceted analysis, and also provides a brief qualitative risk assessment regarding the attack vectors.

The purpose of this study is to propose an integrative model for evaluating the effectiveness of performance management system (PMS). This model aims to systematize the dimensions and criteria used in the literature and provide clarity in terms of evaluation possibilities. A comprehensive review of the literature was conducted to identify the dimensions, criteria, and causal relationships used in evaluating PMS effectiveness. A sample of 57 articles was analyzed using content analysis. The study established dimensions and criteria that have been neglected in the literature. The review resulted in the proposal of an integrative model for evaluating PMS effectiveness, which incorporates individual and organizational dimensions and criteria identified in the literature. It sheds light on recurrently adopted dimensions, particularly those related to individual-level phenomena, and seeks to clarify current conceptual ambiguities. This study’s originality lies in its integrative approach, which diverges from the prevailing tendencies in the field. This study provides clarity regarding the conceptual confusion surrounding ambiguous concepts and generically applied measures that hinder the drawing of certain conclusions about the effectiveness of PMS.

A data breach is the unauthorized disclosure of sensitive personal data, and it impacts millions of individuals annually in the United States, as reported by Privacy Rights Clearinghouse. These breaches jeopardize the physical safety of the individuals whose data are exposed and result in substantial economic losses for the affected companies. To diminish the frequency and severity of data breaches in the future, it is imperative to research their causes and explore preventive measures. In pursuit of this goal, this study considers a dataset of data breach incidents affecting companies listed on the New York Stock Exchange and NASDAQ. This dataset has been augmented with additional information regarding the targeted company. This paper employs statistical visualizations of the data to clarify these incidents and assess their consequences on the affected companies and individuals whose data were compromised. We then propose mitigation controls based on established frameworks such as the NIST Cybersecurity Framework. Additionally, this paper reviews the compliance scenario by examining the relevant laws and regulations applicable to each case, including SOX, HIPAA, GLBA, and PCI-DSS, and evaluates the impacts of data breaches on stock market prices. We also review guidelines for appropriately responding to data leaks in the U.S., for compliance achievement and cost reduction. By conducting this analysis, this work aims to contribute to a comprehensive understanding of data breaches and empower organizations to safeguard against them proactively, improving the technical quality of their basic services. To our knowledge, this is the first paper to address compliance with data protection regulations, security controls as countermeasures, financial impacts on stock prices, and incident response strategies. Although the discussion is focused on publicly traded companies in the United States, it may also apply to public and private companies worldwide.

The academic community has witnessed a notable increase in paper publications, whereby the rapid pace at which modern society seeks information underscores the critical need for literature mapping. This study introduces an innovative automatic model for categorizing articles by subject matter using Machine Learning (ML) algorithms for classification and category labeling, alongside a proposed ranking method called SSS (Scientific Significance Score) and using Z-score to select the finest papers. This paper’s use case concerns industry productivity. The key findings include the following: (1) The Decision Tree model demonstrated superior performance with an accuracy rate of 75% in classifying articles within the productivity and industry theme. (2) Through a ranking methodology based on citation count and publication date, it identified the finest papers. (3) Recent publications with higher citation counts achieved better scores. (4) The model’s sensitivity to outliers underscores the importance of addressing database imbalances, necessitating caution during training by excluding biased categories. These findings not only advance the utilization of ML models for paper classification but also lay a foundation for further research into productivity within the industry, exploring themes such as artificial intelligence, efficiency, industry 4.0, innovation, and sustainability.

With the economic growth of the Brazilian agroindustry, it is necessary to evaluate the efficiency of this activity in relation to environmental demands for the country’s economic, social, and sustainable development. Within this perspective, the present research aims to examine the eco-efficiency of agricultural production in Brazilian regions, covering 5563 municipalities in the north, northeast, center-west, southeast, and south regions, using data from 2016–2017. In this sense, this study uses the DEA methods (classical and stochastic) and the computational bootstrap method to remove outliers and measure eco-efficiency. The findings lead to two fundamental conclusions: first, by emulating the benchmarks, it is feasible to increase annual revenue and preserved areas to an aggregated regional level by 20.84% while maintaining the same inputs. Given that no municipality has reached an eco-efficiency value equal to 1, there is room for optimization and improvement of production and greater sustainable development of the municipalities. Secondly, climatic factors notably influence eco-efficiency scores, suggesting that increasing temperatures and decreasing precipitation can positively impact eco-efficiency in the region. These conclusions, dependent on regional characteristics, offer valuable information for policymakers to design strategies that balance economic growth and environmental preservation. Furthermore, adaptive policies and measures can be implemented to increase the resilience of local producers and reduce vulnerability to changing climate conditions.

Data breaches result in data loss, including personal, health, and financial information that are crucial, sensitive, and private. The breach is a security incident in which personal and sensitive data are exposed to unauthorized individuals, with the potential to incur several privacy concerns. As an example, the French newspaper Le Figaro breached approximately 7.4 billion records that included full names, passwords, and e-mail and physical addresses. To reduce the likelihood and impact of such breaches, it is fundamental to strengthen the security efforts against this type of incident and, for that, it is first necessary to identify patterns of its occurrence, primarily related to the number of data records leaked, the affected geographical region, and its regulatory aspects. To advance the discussion in this regard, we study a dataset comprising 428 worldwide data breaches between 2018 and 2019, providing a visualization of the related statistics, such as the most affected countries, the predominant economic sector targeted in different countries, and the median number of records leaked per incident in different countries, regions, and sectors. We then discuss the data protection regulation in effect in each country comprised in the dataset, correlating key elements of the legislation with the statistical findings. As a result, we have identified an extensive disclosure of medical records in India and government data in Brazil in the time range. Based on the analysis and visualization, we find some interesting insights that researchers seldom focus on before, and it is apparent that the real dangers of data leaks are beyond the ordinary imagination. Finally, this paper contributes to the discussion regarding data protection laws and compliance regarding data breaches, supporting, for example, the decision process of data storage location in the cloud.

This study analyzes the municipal agriculture eco-efficiency in the Amazon biome and the influence of exogenous factors. We use a two-stage data envelopment analysis (DEA) method with bootstrap. The results indicate that: (i) the density curve of the corrected eco-efficiency indices is statistically different from the deterministic score curves, suggesting the presence of bias in the latter; (ii) there is evidence of constant returns, demonstrating that small, medium and large municipalities can be equally eco-efficient; (iii) there are relevant eco-inefficient behaviors, showing that it is possible to increase the products (gross revenue and preserved area) and simultaneously reduce environmental damage (impact on biodiversity and greenhouse gas emission indices) with the same inputs, by replicating the best practices; and (iv) eco-efficiency scores are also substantially affected by exogenous factors. Based on the results, strategies can be defined by decision-makers to harmonize economic growth and environmental preservation; in addition, adaptive policies and actions can be adopted to optimize the sustainability of regional agriculture.

O combate à pandemia desencadeou quase que imediatamente reações por parte de governos em todo o mundo. Recursos econômicos foram direcionados para manutenção da economia e auxílio a famílias e empresas, gerando alterações sem precedentes nos orçamentos públicos. Considerando que a corrupção é um mal que aflige todas as sociedades, abriu-se uma janela de oportunidade para desvios de recursos públicos. Nesse contexto, este estudo teve por objetivo analisar os créditos extraordinários abertos no orçamento federal de 2020 destinados ao enfrentamento da pandemia do Covid-19, capturando dados da execução orçamentária e promovendo análises em busca de sinalizações para atos de corrupção nos municípios. Para tanto, foram utilizados métodos quantitativos e qualitativos, suportados pela Análise de Redes Sociais e mineração de grafos. Os resultados indicam o potencial da abordagem com grafos na identificação de localidades mais suscetíveis à existência de atos de corrupção, uma vez que o estudo das relações entre empresas e municípios oferece insights investigativos que provavelmente não seriam alcançados por meio de modelos tradicionais de investigação. Como contribuição, os achados da pesquisa podem ser úteis para pesquisadores e profissionais que buscam métodos para fortalecer as atividades dos órgãos de fiscalização e controle, contribuindo com o aperfeiçoamento da gestão pública.

This research presents an eco-efficiency index for the municipalities of São Paulo, indicating how much it would be possible to maximize economic and environmental objectives, taking into account the best practices for the municipalities of this region. In this vein, we used the Data Envelopment Analysis method with directional distance functions based on the classic variables of multiproduct production function and the internalization of two externalities (one positive and one negative). The study also used the tools of exploratory spatial data analysis to verify the spatial autocorrelation and spatial heterogeneity of the calculated index. The results indicate that, on average, the analyzed municipalities are able to expand the production and forested areas by 59% and also to reduce degraded areas and inputs in the same proportion. Spatial analysis demonstrated the existence of spatial heterogeneity and autocorrelation between municipalities and the formation of large clusters. Based on these results, priorities for environmental intervention in the state are defined.

The work aims to discuss accounting science from the point of view of Kuhnian theory. The study fits as a theoretical essay, in which, based on bibliographic research, to expose ideas and reflect on concepts. To this end, a brief historical context is presented to the reader on the development of accounting knowledge, showing the transformations that this field of study has undergone and its search for maturity as a science, whether normative or positive. The characteristics of the Kuhnian scientific process are also analyzed, addressing the phases of the formation of a science and its paradigms. Thus, a Kuhnian structure for accounting science is proposed, focusing on the 20th and 21st centuries, framing the work A Statement of Basic Accounting Theory (AAA, 1966) as the starting point of the (new) scientific accounting period. Still, aspects related to conceptual frameworks were analyzed, pointing out criticisms to the current framework. Finally, it is maintained that accounting is experiencing a period of crisis as a science, as its paradigm would be in “check” by no longer offering solutions to emerging issues in the field, opening up the opportunity for a new technology-based accounting paradigm. As a suggestion for future research, a multidisciplinary approach to accounting is indicated with the introduction of Big Data techniques in the production of accounting knowledge.

O presente estudo tem por objetivo verificar empiricamente os fatores determinantes da estrutura de capital de empresas brasileiras de capital aberto, com ações negociadas na BM&FBosvepa, no período 2010-2017. Os fatores considerados na análise são aqueles propostos nas principais teorias sobre estrutura de capital: rentabilidade, risco, tamanho, tangibilidade e oportunidades de crescimento. Subsidiariamente a estes fatores, incluiu-se um conjunto de dummies setoriais com o intuito de evidenciar eventual característica específica de dado setor. Para a análise empregou-se o método estatístico de dados em painel e modelos com efeitos fixos e com efeitos variáveis. A amostra foi composta por 186 empresas, dividias em 19 setores econômicos. Os testes estatísticos evidenciaram a não significância dos setores ao apontar pela estimação de um modelo com efeitos fixos. Os resultados indicam que rentabilidade, risco e oportunidades de crescimento induzem menor endividamento, que o tamanho de empresa induz maior endividamento e que a tangibilidade não teve influência sobre o nível de endividamento das empresas da amostra no período estudado. Em que pese apresentarem justificativas teóricas, os resultados obtidos, em conjunto, não permitem confirmar um teoria específica acerca da estrutura de capital de empresas de capital aberto.

Em uma época de retração do crédito e de saldos elevados de parcelamento de tributos, o objetivo neste estudo foi investigar como o parcelamento de tributos federais pode se traduzir como fonte de financiamento indireto das empresas, avaliando-se a vantagem em relação à captação no mercado e o impacto na estrutura de capital. Fez-se uma comparação do custo do parcelamento com o custo de captação de crédito com instituições financeiras, bem como, por meio de estudo de caso, simulou-se o impacto na estrutura de capital. Constatou-se que o custo do parcelamento de tributos é menor do que o de captação. Observou-se vantagem para o parcelamento de tributos em relação à estrutura de capital. Não foi identificada relação entre o custo de financiamento, seja por parcelamento seja por captação, e os saldos de parcelamento e de crédito financeiro. Palavras-chave: Parcelamento tributário. Tributos federais. Financiamento. Custo. Estrutura de capital. Installment plan of federal taxes as a form of indirect financing Abstract In an era of credit crunch and high tax installment balances, the objective of this study was to investigate how the federal tax installment can be useful to indirect financing for companies, evaluating the advantage in relation to banking funding, the impact on the capital structure and the relationship with the economic cycle. A comparison of the cost of installment payment with that of funding with financial institutions was made. By means of a case study it was simulated the impact on the capital structure. It was found that the cost of the tax installment is lower than that of funding. There was an advantage for the tax installment in relation to the capital structure. No relationship was identified between the cost of financing, either by installment or by funding, with installment and financial credit balances. Keywords: Tax installment. Federal taxes. Financing. Cost. Capital structure.

ABSTRACT This article aims to analyze if the issuance of Series E Treasury Bonds (CFT-Es) generates abnormal returns in a higher education stock portfolio and verify if the Brazilian higher education market is efficient in its semi-strong form. The main purpose of CFT-Es is to transfer funds to institutions with the aim of providing finance to students enrolled in private universities. These issuances have effects on the capital market, considering that after the program began, the first initial public offering (IPO) of a Brazilian university occurred. Moreover, according to the National Institute for Educational Studies and Research Anísio Teixeira/Ministry of Education and Culture (Inep/MEC), Brazil has the largest market for higher education in Latin America. Several studies have been conducted to analyze the relationship between monetary policy and financial markets, but this has not occurred within the scope of fiscal policy. Such research is appropriate, considering the discussion on the need to contain government spending, but at the same time stimulate the Brazilian economy. The main contribution of the study is it indicates that the higher education market has tended towards the efficiency hypothesis, considering that in the first analysis, H0 was not rejected for 82% of the windows of events, and in the second analysis, H0 was not rejected for any of the windows of events, with there being no evidence of abnormal gains due to funds being released for the Student Finance Fund (Fies). The event study methodology was used to test the hypotheses of abnormal returns obtained due to CFT-Es being issued through the release of ordinances. A portfolio composed of higher education stocks was elaborated, weighted by the quarterly amount receivable from Fies for each institution, and covering 2009 to 2017. The results show that the stocks of institutions benefiting from Fies tend to react efficiently to CFT-E issuances authorized by the National Treasury.

Resumo: A dívida pública é um importante elemento das finanças públicas e sua sustentabilidade é o indicativo da boa gestão da política fiscal de um governo. Este estudo tem o objetivo de verificar a sustentabilidade da dívida estadual, de forma agregada, a partir da análise de cointegração e da reação fiscal entre o resultado primário e a dívida líquida estadual, usando dados mensais de dezembro/2001 a maio/2014. Os resultados apontam a existência de cointegração entre as séries de resultado primário e de dívida líquida estadual e, além disso, revelam que os governos estaduais geraram superávits primários em face do crescimento da dívida. Assim, tem-se a indicação de que existiu sustentabilidade para a dívida dos estados no período estudado. Contudo, desafios recentes como o afrouxamento fiscal e a redução da atividade econômica colocam em dúvida a sustentabilidade futura.

The concept of staff sizing aims to estimate or determine the ideal or optimal number of people needed to perform some organizational activities, which can be considered as a trend. So, models for staff sizing constitute a fundamental part of accurately identifying staff allocation. The objective of this paper is to propose a framework for decision-making based on Data Envelopment Analysis–DEA, to estimate the staff sizing in a Brazilian entity responsible for promoting and supporting the competitiveness and sustainable development of micro and small enterprises. Data collection was carried out in the headquarters of the entity, located in Brasilia. Firstly, interviews were carried with managers in order to assess qualitatively the needs of staff for each service unit. Secondly, the documental analysis of reports from 21 units was analyzed quantitatively in order to determine their efficiency in terms of staff sizing. The results found through DEA show that only three service units can be considered efficient in terms of staff sizing. Thus, there is a need to reduce the number of workers in most of the organization. In this context, the contributions for the entity lie in the discussion on the creation of quantitative indicators and the adoption of an efficiency analysis, which can be used to better estimate or determine the optimal quantity of staff. This paper innovates by proposing a quantitative and systematized approach to estimate the staff sizing, which is the DEA.

Em 1996 a carga tributária das Microempresas (ME) e Empresas de Pequeno Porte (EPP) foi reduzida por meio da criação do Sistema Integrado de Pagamento de Impostos e Contribuições das Microempresas e das Empresas de Pequeno Porte (SIMPLES), que é um regime especial unificado de arrecadação de tributos e contribuições. Essa redução da carga tributária representa uma importante renúncia de receita ao Estado, o que representa um custo para o país e justifica a importância do seu estudo. Assim, o objetivo do presente artigo é fazer uma análise da arrecadação do SIMPLES e do SIMPLES Nacional e da geração de empregos pelas ME, EPP e pelos Microempreendedores Individuais (MEI), para verificar benefícios à sociedade. Como instrumento de pesquisa, utilizou-se revisão bibliográfica, coleta de dados para o período de 2002 a 2013 e análise desses dados por meio de estatística descritiva. Foi verificado que a arrecadação tributária pelo SIMPLES apresentou um crescimento mais de três vezes superior ao crescimento da arrecadação dos outros regimes, no período de 2007 a 2013. Além disso, observa-se que apesar das ME, EPP e MEI possuírem participação expressiva no número de empregos, essa participação reduziu no período estudado. Constatou-se que a partir de 2009, com a influência dos MEI, a arrecadação média por empresa no SIMPLES tem apresentado diminuição.In 1996, Microenterprises' (ME) and Small Enterprises' (EPP) tax burden was reduced by the creation of the Integrated System for Payment of Taxes and Contributions of Micro and Small Enterprises (SIMPLES), which is a special unified regime applied to collect federal taxes and contributions of such companies. This tax reduction is an important waiver of revenue to the state, which represents a cost to the country and justifies the importance of this study. The objective of this paper is to analyze the collection of 'SIMPLES' tax and the consequent generation of jobs by ME, EPP and Individual Micro Entrepreneurs (MEI), in order to verify its benefits to the society. As a research tool, a literature review was made and data was collected from the period 2002-2013 and the analysis of these was made by a descriptive statistics. It was found that tax collections for the SIMPLES showed a growth more than three times higher in relation to the collection of other regimes in the period 2007 to 2013. Moreover, it was observed that despite ME, EPP and MEI have a significant participation in the employment number, this share decreased during the study period. It was found that since 2009, with the influence of MEI, the average revenue per company has decreased in SIMPLES.

In the period between 2006 and 2013 the tax rate on industrialized products for cars was reduced in two stages, with the aim of increasing their demand and stimulate the economy. Thus, the aim of this paper is to verify whether the reduction in the rate of tax on industrialized products caused alterations in auto sales. Through regression analysis, was tested the influence of the reduction in of tax on industrialized products on the cars sale. The results showed that it is not possible to state that the reduction in tax on industrialized products rate was able to change the behavior of car sales. As additional results, can be seen in the period the expansion of credit to the natural person, even in a situation of worker’s real income declining. Another observation was that the price of the economy car had an increase below inflation, indicating a change in relative prices.

En el período entre 2006 y 2013 la alícuota del Impuesto sobre Productos Industrializados para automóviles fue reducida en dos momentos, con el objetivo de aumentar la demanda de estos y estimular la economía. Así, el objetivo de este artículo es verificar si la reducción de la alícuota del IPI causó alteraciones en las ventas de automóviles. Por medio del análisis de regresión, fue probada la influencia de la reducción de la alícuota del IPI sobre la venta de automóvil es. Los resultados obtenidos demostraron que no es posible afirmar que la reducción de la alícuota del IPI fue capaz de modificar el comportamiento de la venta de automóviles. Como resultados adicionales, se observa en el período la expansión del crédito a la persona física, aun en una situación de declive de la renta real del trabajador. Otra observación fue que el precio del automóvil popular tuvo un aumento abajo de la inflación, indicando un cambio de precios relativos.

O exercício do controle social é uma das formas de prática democrática aplicada ao sistema de saúde pública no Brasil. Dentre os mecanismos para o seu exercício, tem-se os relatórios de prestação de contas de natureza econômico-financeira. Tais relatórios são elaborados pelas Secretarias de Saúde e submetidos à deliberação de seus respectivos Conselhos de Saúde, como um dos meios à concretização da transparência dos atos públicos. Este artigo versa sobre uma análise comparada dos relatórios de prestação de contas das Secretarias Estaduais de Saúde, permitindo dessa forma a descrição de possíveis melhorias no processo de divulgação de tais informações. A presente pesquisa se caracteriza pelo tipo documental e natureza qualitativa. Foram analisados os relatórios de prestação de contas dos exercícios de 2008 e 2009 dos seguintes Estados: Paraná, Santa Catarina, Rio Grande do Sul, Espírito Santo e Rio de Janeiro. Os resultados sugerem que, apesar de as Secretarias Estaduais divulgarem a maioria das variáveis avaliadas, os Conselhos de Saúde não materializam a análise da gestão pública em seus pareceres, demonstrando que o processo de avaliação das informações carece de melhorias acerca de sua interpretação e recomendações de melhorias das políticas públicas em saúde. No que tange à prestação de contas, aspectos como: definição de prioridades na destinação de recursos e estabelecimento de metas e objetivos ainda não fazem parte da maioria dos relatórios estaduais. Como sugestão para pesquisas futuras, poder-se-á analisar se a amplitude de participação dos conselhos influencia na melhoria dos relatórios de prestação de contas.