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Strategic Project - UI 731 - 2011-2012

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Publications

Probabilistic clustering of interval data
Publication . Brito, Paula; Silva, A. Pedro Duarte; Dias, José G.
In this paper we address the problem of clustering interval data, adopting a model-based approach. To this purpose, parametric models for interval-valued variables are used which consider configurations for the variance-covariance matrix that take the nature of the interval data directly into account. Results, both on synthetic and empirical data, clearly show the well-founding of the proposed approach. The method succeeds in finding parsimonious heterocedastic models which is a critical feature in many applications. Furthermore, the analysis of the different data sets made clear the need to explicitly consider the intrinsic variability present in interval data.
Reference pricing with elastic demand for pharmaceuticals
Publication . Gonçalves, Ricardo; Rodrigues, Vasco
In this paper, we re‐examine the properties of two commonly adopted government reimbursement schemes for pharmaceuticals: reference pricing and fixed percentage reimbursement. We depart from the previous literature by assuming that the individual demand is price‐sensitive and depends on the copayment rate (i.e., the part paid by each consumer). We obtain two novel results under reference pricing: first, as the copayment rate increases, so do pharmaceutical prices; second, this increase in pharmaceutical prices reduces social welfare. Whilst reference pricing does emerge as a preferable reimbursement scheme, demand elasticities and the copayment rate interact in complex ways. This leads (unexpectedly) to the possibility that a higher copayment rate (lower reimbursement rate) results in higher government expenditure.
Sobre a reforma política e administrativa do estado português
Publication . Costa, Leonardo; Osório, Paulo
O Governo português tem em curso uma reforma do Estado. Neste artigo analisamos o impacto de três alternativas de reforma: cenário da reforma em curso (CREC), cenário baseado em territórios supramunicipais do tipo NUTS 3 (CNUTS) e cenário baseado na regionalização (CR). A análise de impacto contempla várias dimensões: coerência organizativa de conjunto (poder central e local), racionalização territorial das políticas públicas, vulnerabilidade aos lóbis, qualidade dos quadros dos partidos políticos, competitividade da economia, coesão social e territorial, qualidade da democracia, custos operacionais. Os resultados mostram que o CREC é mais do mesmo e por isso não é promissor, em particular, no controlo da despesa pública. O CR é o cenário mais interessante mas de difícil aplicação no imediato. O CNUTS é o cenário mais promissor, podendo evoluir para o CR, se a sociedade portuguesa assim o desejar.
Identifying Special Structures in Interval-Data via Model-Base Clustering
Publication . Brito, Paula; Duarte Silva, A. P.; Dias, José G.
In this paper we present a model-based approach to the clustering of interval data building on recently proposed parametric models. These methods consider configurations for the variance-covariance matrix that take the nature of the interval data directly into account. The proposed framework relies on parametrizations considering the inherent variability of the relevant data units and the relation that may exist between this variability and the corresponding value levels. Using both synthetic and real data sets the pertinence of the proposed methodology is shown, as the method effectively selects heterocedastic models with restricted covariance structures when they are the most suitable, even in situations with limited information. Moreover, considering special configurations of the variance-covariance matrix, adapted to nature of interval data, proves to be the adequate approach. The presented study also makes clear the need to consider both the information about position (conveyed by the MidPoints) and intrinsic variability (conveyed by the Log-Ranges) when analysing interval data.

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Funding agency

Fundação para a Ciência e a Tecnologia

Funding programme

6817 - DCRRNI ID

Funding Award Number

PEst-OE/EGE/UI0731/2011

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