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A Comparative Study of the Estimators for the Demand of Engineering Courses in Portugal

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Recent Studies on Risk Analysis and Statistical Modeling

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

For the purpose of modeling the demand of Engineering Courses in Portugal we analyzed the possible regression models for panel count data models by establishing a comparison between the estimators obtained and then finding the most appropriate ones for our dataset. A precise quantification of the demand for each academic program is facilitated by the rules of access to higher education, in National Contest for Access and Admission to Higher Education, where candidates must list up to six preferences of institution and program. The data used in this paper covers the results of the national contest from 1997 to 2015 provided by the Portuguese Ministry of Education and Science. Multivariate methodologies were performed in order to allow a better understanding of the students’ allocation behavior. The results seem to indicate that the negative binomial estimates fit better the dataset analyzed.

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Acknowledgements

A. Manuela Gonçalves and Raquel Oliveira were supported by the Research Centre of Mathematics of the University of Minho with the Portuguese Funds from the “FCT-Fundação para a Ciência e a Tecnologia,” through the Project PEstOE/MAT/UI0013/2014. Rosa M. Vasconcelos was supported by the Foundation through “FCT - Fundação para a Ciência e Tecnologia,” within the Project UID/MAT/00013/2013, by FEDER funds through the Competitivity Factors Operational Programme—COMPET and by national funds through FCT within the scope of the project POCI-01-0145-FEDER-007136.

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Correspondence to Raquel Oliveira .

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Oliveira, R., Manuela Gonçalves, A., Vasconcelos, R.M. (2018). A Comparative Study of the Estimators for the Demand of Engineering Courses in Portugal. In: Oliveira, T., Kitsos, C., Oliveira, A., Grilo, L. (eds) Recent Studies on Risk Analysis and Statistical Modeling. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-76605-8_26

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