Prof. Marco Costa
University of Aveiro, Aveiro, Portugal
University of Aveiro, Portugal
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Academic Career Length
19Years (2008-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications26 February 2016 in Studies in Higher Education
Journal Article
PSPatrícia Silva Silva
Patrícia Silva SilvaBLBetina Lopes
Betina LopesMarco CostaAMAna I. Melo
Ana I. MeloGDGonçalo Dias
Gonçalo DiasDSDina Seabra
Dina Seabra +1
Higher education institutions are increasingly concerned with the professional insertion of graduates in the labour market and with the design of institutional mechanisms to facilitate students’ transition from higher education to work, particularly given the context of scarcity of financial resources and the rise of graduate unemployment. This issue has been addressed, inter alia, through the creation of study programmes with internships. Despite the public discourse encouraging the use of such strategies, there is a general consensus regarding the absence of empirical studies on the professional value of these strategies. This article aims to assess two interrelated questions: the extent to which measures of graduate unemployment rate tend to decrease after the introduction of internships in Portuguese study programmes; and the extent to which this effect applies to the different institutions that comprise the Portuguese tertiary education landscape. It also seeks to contribute to the debate on the relevance of the structure and nature of internships, which are factors frequently neglected in the literature.
31 May 2015 in Higher Education
Journal Article
PSPatrícia Silva Silva
Patrícia Silva SilvaBLBetina Lopes
Betina LopesMarco CostaDSDina Seabra
Dina SeabraAMAna I. Melo
Ana I. MeloGDGonçalo Dias
Gonçalo Dias +1
10 December 2019 in AIP Conference Proceedings
Conference Paper
This study deals with forecasting economic time series that have strong trends and seasonal patterns. How to best model and forecast these patterns has been a long-standing issue of time series analysis. In this work, we propose a Holt-Winters Exponential Smoothing approach to time series forecasting in order to increase the chance of capturing different patterns in the data and thus improve forecasting performance. Therefore, the main propose of this study is to compare the accuracy of Holt-Winters models (additive and multiplicative) for forecasting and to bring new insights about the methods used via this approach. These methods are chosen because of their ability to model trend and seasonal fluctuations present in economic data. The models are fitted to time series of e-commerce retail sales in Portugal. Finally, a comparison is made and discussed.
1 December 2016 in Polymer Testing
Journal Article
Nuno GamaRSRui Silva
Rui Silva
Marco Costa
Ana Barros timmons
Artur FerreiraJournal Article
Magda Sofia Valério MonteiroMarco CostaThe monitoring and prediction of water quality parameters are important tasks in the management of water resources. In this work, the performances of time series statistical models were evaluated to predict and forecast the dissolved oxygen (DO) concentration in several monitoring sites located along the main river Vouga, in Portugal, during the period from January 2002 to May 2015. The models being compared are a regression model with correlated errors and a state-space model, which can be seen as a calibration model. Both models allow the incorporation of water quality variables, such as time correlation or seasonality. Results show that, for the DO variable, the calibration model outperforms the regression model for sample modeling, that is, for a short-term forecast, while the regression model with correlated errors has a better performance for the forecasting h-steps ahead framework. So, the calibration model is more useful for water monitoring using an online or real-time procedure, while the regression model with correlated errors can be applied in order to forecast over a longer period of time.
1 July 2010 in Journal of Statistical Planning and Inference
Journal Article
Marco CostaTATeresa Alpuim
Teresa AlpuimAbout Me
Marco Costa holds a PhD in Statistics and Operational Research, in the specialty of Probability and Statistics, from the University of Lisbon, a master's degree in Probability and Statistics from the same university and a degree in Applied Mathematics and Computing from the University of Aveiro (UA).
He is currently an Associate Professor at the Águeda School of Technology and Management from the University of Aveiro (ESTGA-UA), where he has taught since 1999 and he is a researcher at the Center for Research and Development in Mathematics and Applications (CIDMA) at the same university. He has taught courses in Mathematics and Statistics and he has collaborated in the supervision of postgraduate students.
He has published several scientific articles in indexed international journals, five chapters of scientific books of international circulation and over two dozen scientific papers published in national and international conferences.
He has participated in university management at the level of the unit as in the organs of the University. He was Head of ESTGA between 2018 and 2023. He was, among other positions, Secretary of the General Council of the University of Aveiro, vice-director of ESTGA and member of the Council of ESTGA, elected member of the Scientific Council of the UA, member of the Executive Committee of ESTGA.
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