25 resultados para Panel Data Model
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
Resumo:
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.
Resumo:
A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
Resumo:
Double Degree. A Work Project presented as part of the requirements for the Award of a Masters in Management from Nova School of Business and Economics and Maastricht University.
Resumo:
The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.
Resumo:
The main purpose of the present dissertation is the simulation of the response of fibre grout strengthened RC panels when subjected to blast effects using the Applied Element Method, in order to validate and verify its applicability. Therefore, four experimental models, three of which were strengthened with a cement-based grout, each reinforced by one type of steel reinforcement, were tested against blast effects. After the calibration of the experimental set-up, it was possible to obtain and compare the response to the blast effects of the model without strengthening (reference model), and a fibre grout strengthened RC panel (strengthened model). Afterwards, a numerical model of the reference model was created in the commercial software Extreme Loading for Structures, which is based on the Applied Element Method, and calibrated to the obtained experimental results, namely to the residual displacement obtained by the experimental monitoring system. With the calibration verified, it is possible to assume that the numerical model correctly predicts the response of fibre grout RC panels when subjected to blast effects. In order to verify this assumption, the strengthened model was modelled and subjected to the blast effects of the corresponding experimental set-up. The comparison between the residual and maximum displacements and the bottom surface’s cracking obtained in the experimental and the numerical tests yields a difference of 4 % for the maximum displacements of the reference model, and a difference of 4 and 10 % for the residual and maximum displacements of the strengthened model, respectively. Additionally, the cracking on the bottom surface of the models was similar in both methods. Therefore, one can conclude that the Applied ElementMethod can correctly predict and simulate the response of fibre grout strengthened RC panels when subjected to blast effects.
Resumo:
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
Resumo:
Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia
Resumo:
This article develops a latent class model for estimating willingness-to-pay for public goods using simultaneously contingent valuation (CV) and attitudinal data capturing protest attitudes related to the lack of trust in public institutions providing those goods. A measure of the social cost associated with protest responses and the consequent loss in potential contributions for providing the public good is proposed. The presence of potential justification biases is further considered, that is, the possibility that for psychological reasons the response to the CV question affects the answers to the attitudinal questions. The results from our empirical application suggest that psychological factors should not be ignored in CV estimation for policy purposes, allowing for a correct identification of protest responses.