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Bruno Miguel Pinto Damásio
Bruno Miguel Pinto Damásio, Professor Auxiliar Convidado
Doutoramento em Matemática Aplicada
Universidade de Lisboa

Bruno Damásio holds a PhD Applied Mathematics, a Master in Econometrics and a Degree in Economics by the University of Lisbon. His research interests are nonlinear econometrics, multivariate Markov chains, stochastic processes, financial econometrics, nonlinear time-series, applied economics, and the statistical packages R and Stata. His work has been published in several journals, such as Physica A: Statistical Mechanics and its Applications, Statistics and Probability Letters, Applied Economics Letters, Empirica. Additionally, he is a lecturer of statistics and econometrics courses at NOVA IMS (Information Management School, Nova University of Lisbon) and ISEG (Lisbon School of Economics and Management, University of Lisbon). He is serving as statistical consultant and trainer for numerous private and public organisations including OECD, European Comission, European Court of Auditors, Ministries, Central Banks, Bureau of Statistics, Bureau of Economic Analysis, among others.

Unidades Curriculares que leciona na NOVA IMS
- Análise de Dados Discretos
- Análise de Variância
- Econometria I
- Econometria II
- Estatística para a Ciência de Dados
- Metodologias de Investigação
- Métodos de Previsão
- Métodos Econométricos
- Programação para a Gestão
Publicação em Periódicos Científicos
Curado, A., Damásio, B., Encarnação, S., Candia, C., & Pinheiro, F. L. (2021). Scaling behavior of public procurement activity. PLoS ONE, 16(12), 1-19. [e0260806].
Lyra, M. D. S., Curado, A., Damásio, B., Bação, F., & Pinheiro, F. L. (2021). Characterization of the Firm-Firm Public Procurement Co-Bidding Network from the State of Ceará (Brazil) Municipalities. Applied Network Science, 6, 1-10. [77].
Vaz, E., Bação, F., Damásio, B., Haynes, M., & Penfound, E. (2021). Machine learning for analysis of wealth in cities: A spatial-empirical examination of wealth in Toronto. Habitat International, 108, 1-9. [102319].
Vaz, E., Cusimano, M. D., Bação, F., Damásio, B., & Penfound, E. (2021). Open data and injuries in urban areas: A spatial analytical framework of Toronto using machine learning and spatial regressions. PLoS ONE, 16(March), 1-17. [e0248285].
Vaz, E., Damásio, B., Bação, F., Kotha, M., Penfound, E., & Rai, S. K. (2021). Mumbai's business landscape: A spatial analytical approach to urbanisation. Heliyon, 7(7), [e07522].
Damásio, B., & Mendonça, S. (2019). Modelling insurgent-incumbent dynamics: Vector autoregressions, multivariate Markov chains, and the nature of technological competition. Applied Economics Letters, 26(10), 843-849. [Advanced online publication 30 july 2018]. DOI: 10.1080/13504851.2018.1502863
Martins, D., & Damásio, B. (2019). One Troika fits all?: job crash, pro-market structural reform and austerity-driven therapy in Portugal. Empirica. [Advanced online publication on 11 february 2019]. Doi:
Damásio, B.; Louçã, F. & Nicolau, J. (2018). The changing economic regimes and expected time to recover of the peripheral countries under the euro: A nonparametric approach. Physica A: Statistical Mechanics and its Applications, 507, 524-533. doi:
Barros, C., Damásio, B. and Faria, J. (2014). Reverse FDI in Europe: An Analysis of Angola's FDI in Portugal. African Development Review, 26 (1), 160-171.
Damásio, B. and Nicolau, J. (2014). Combining a Regression Model with a Multivariate Markov Chain in a Forecasting Problem.Statistics & Probability Letters, 90 (july), 108-113.