O uso da Lei Rouanet como ferramenta produtiva em um plano de comunicação

The Rouanet law is a tax incentive law that allows companies to invest up to 4% of their taxes - based on actual profit - in sponsoring cultural projects previously approved by the Ministry of Culture. By sponsoring these projects, companies can have their name attached to them and, consequently, strengthening their brand and increase its visibility in the market. Whereas this project is aligned to the company vision, its image will be strengthened and the sales will increase. Large companies use the Rouanet Law to sponsor cultural events and have very strong names in the Brazilian market, perhaps worldwide. Examples: Petrobras, Banco do Brasil, Banco Bradesco, BNDES, Usiminas, Vale, among others. The Public Relations professional, who’s responsible for internal and external communication of a company, can use it as a differential of his work, expanding the company's profits with minimum investments, aligning the company's vision to actual practices and using the sponsorship as an agent capable of strengthen its social responsibility and, due to that, to increase the trust of its target audience. This study will address the theoretical and practical aspects of the Rouanet Law and of the public relations professionals, beyond mentioning examples on the subject, with special attention to Petrobras, the largest sponsor of cultural projects in Brazil. The greatest problem of the Rouanet Law is the fact that its sponsored projects are mostly concentrated in the Southeast, specifically in the Rio - São Paulo region. The more popular the Act become, for most places it will spread and Brazil may, after some time, become a world reference in the Cultural point

The Economic Impacts of Tourism in Ouro Preto, MG, Brazil

The tourism spending like other activities has direct and secondary effects on the economy, and presents complex interaction with other activities deserving a special treatment for measuring its contribution to the global result of production and consumption. In this paper, it is used the Money Generation Model to measure the global economic impact of tourism sales in Ouro Preto, this method is not so limited by the data and it is able to produce good approximations to reality. It was not possible to adopt the WTO methodology due to data limitation. The results revealed the real importance of tourism for Ouro Preto, representing up to 10.4% of GDP in 2002, up to 21.8% of tax revenues in 2004, and approximately 11% of the region’s population in 2002 was related to tourism sales. Some actions can be outlined from these results in order to illustrate the current economic reality of the tourism in Ouro Preto. It is also possible to improve the tourist planning accomplished by the local City Hall in a coherent way with the economic results generated by the tourism.

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model