5 resultados para C33 - Models with Panel Data

em RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal


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This paper demonstrates the significance of culture in examining the relationshipbetween democratic capital and environmental performance.The aim is to examine the relationship among scores on the Environmental Performance Index and the two dimensions of cross cultural variation suggested by Ronald Inglehart and Christian Welzel. Significantional interrelationships among democracy, cultural and environmental sustaintability measures could be found, following the regression results. Firstly, higher levels of democratic capital stock are associated with better environmental performance. Secondly importance to distinguish between cultural groups could be confirmed.

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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics

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This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

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RESUMO - Introdução: A despesa em saúde aumentou consideravelmente nas últimas décadas na maioria dos países industrializados. Por outro lado, os indicadores de saúde melhoraram. A evidência empírica sobre a relação entre as despesas em saúde e a saúde das populações tem sido inconclusiva. Este estudo aborda a relação entre as despesas em saúde e a saúde das populações através de dados agregados para 34 países para o período 1980-2010. Metodologia: Utilizou-se o coeficiente de correlação de Pearson para avaliar a correlação entre as variáveis explicativas e os indicadores de saúde. Procedeuse ainda à realização de uma regressão multivariada com dados em painel para cada indicador de saúde utilizado como variável dependente: esperança de vida à nascença e aos 65 anos para mulheres e homens, anos de vida potencialmente perdidos para mulheres e homens e mortalidade infantil. A principal variável explicativa utilizada foi a despesa em saúde, mas consideraram-se também vários fatores de confundimento, nomeadamente a riqueza, fatores estilo de vida, e oferta de cuidados. Resultados: A despesa per capita tem impacto nos indicadores de saúde mas ao adicionarmos a variável PIB per capita deixa de ser estatisticamente significativa. Outros fatores têm um impacto significativo para quase todos os indicadores de saúde utilizados: consumo de álcool e tabaco, gordura, o número de médicos e a imunização, confirmando vários resultados da literatura. Conclusão: Os resultados vão ao encontro de alguns estudos que afirmam o impacto marginal das despesas em saúde e do progresso da medicina nos resultados em saúde desde os anos 80 nos países industrializados.

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In the last few years, we have observed an exponential increasing of the information systems, and parking information is one more example of them. The needs of obtaining reliable and updated information of parking slots availability are very important in the goal of traffic reduction. Also parking slot prediction is a new topic that has already started to be applied. San Francisco in America and Santander in Spain are examples of such projects carried out to obtain this kind of information. The aim of this thesis is the study and evaluation of methodologies for parking slot prediction and the integration in a web application, where all kind of users will be able to know the current parking status and also future status according to parking model predictions. The source of the data is ancillary in this work but it needs to be understood anyway to understand the parking behaviour. Actually, there are many modelling techniques used for this purpose such as time series analysis, decision trees, neural networks and clustering. In this work, the author explains the best techniques at this work, analyzes the result and points out the advantages and disadvantages of each one. The model will learn the periodic and seasonal patterns of the parking status behaviour, and with this knowledge it can predict future status values given a date. The data used comes from the Smart Park Ontinyent and it is about parking occupancy status together with timestamps and it is stored in a database. After data acquisition, data analysis and pre-processing was needed for model implementations. The first test done was with the boosting ensemble classifier, employed over a set of decision trees, created with C5.0 algorithm from a set of training samples, to assign a prediction value to each object. In addition to the predictions, this work has got measurements error that indicates the reliability of the outcome predictions being correct. The second test was done using the function fitting seasonal exponential smoothing tbats model. Finally as the last test, it has been tried a model that is actually a combination of the previous two models, just to see the result of this combination. The results were quite good for all of them, having error averages of 6.2, 6.6 and 5.4 in vacancies predictions for the three models respectively. This means from a parking of 47 places a 10% average error in parking slot predictions. This result could be even better with longer data available. In order to make this kind of information visible and reachable from everyone having a device with internet connection, a web application was made for this purpose. Beside the data displaying, this application also offers different functions to improve the task of searching for parking. The new functions, apart from parking prediction, were: - Park distances from user location. It provides all the distances to user current location to the different parks in the city. - Geocoding. The service for matching a literal description or an address to a concrete location. - Geolocation. The service for positioning the user. - Parking list panel. This is not a service neither a function, is just a better visualization and better handling of the information.