This research proposes a combined model of time series for forecasting housing sales in the city of São Paulo. We used data referring to the time series of sales of residential units provided by SECOVI-SP. The Exponential Softening, Box-Jenkins and Artificial Neural Networks models are individually modelled, later these are combined through five forecast combination techniques.The techniques used are Arithmetic Mean, Geometric Mean, Harmonic Mean, Linear Regression and Principal Component Analysis. The measures of accuracy to measure the results obtained and to select the best model are the RMSE, MAPE and UTheil of forecast. The results showed that Linear Regression with an independent variable, being a combination of the SARIMA model (2,0,0)(2,0,0)12 and MLP/RNA (12,10,1), provided a satisfactory performance, with an RMSE of 368.74, MAPE of 19.2% and UTheil of 0.315.The combination of time series models allowed a significant increase in forecast performance. Finally, the model was validated, using it to predict housing sales. The results show that the model has a good fit, thus demonstrating that using a housing sales forecasting model helps industry professionals minimize error and make sales and launch decisions.

Diferentes países têm adotado políticas para a redução da emissão de CO2, um dos principais fatores no impacto climático e ambiental. Com base nisso, o objetivo desta pesquisa foi investigar a relação entre o PIB, consumo de energia, participação de energias renováveis e as emissões de CO2 per capita das 50 maiores economias do mundo, para o período de 1990 a 2015. Realizou-se a correlação de Pearson entre as variáveis e uma análise de cluster para verificar o perfil dos países que possuem similaridades, ao longo do tempo, na participação de energias renováveis em sua matriz elétrica. Os resultados encontrados sugerem correlação positiva, de moderada a forte, entre crescimento econômico e consumo de energia e correlação negativa, de fraca a moderada, entre participação de energias renováveis na matriz elétrica dos países e emissão de CO2. A análise de cluster separou os países em três grupos, sendo o primeiro deles aquele que mais possui energia renovável em sua matriz elétrica, composto por países como Brasil, Canadá e Noruega.

In order to meet the housing shortage, was created popular housing programs for low-income families. In Brazil, these programs differs from the rest of the world, since here the programs are directed to the acquisition of real estate, unlike the rest of the world where the focus is lower rents for low-income families. In the context, this type of program has also been used as a tool against economic crises. Based on these aspects, this article aims to identify how the FGTS funds are being used regarding the housing finance. To perform this analysis was studied the targeting of FGTS funds for social housing in Brazil, thus demonstrating, a convincing growth in this modality and also an exchange preferably after the year 2009, of used real estates to new ones.