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Objetivo Geral:

Bibliografia Básica:

• AFONSO, O. e VASCONCELOS, P. Computational Economics: a Concise Introduction. New York: Taylor & Francis Ltd, 2016.
• ARAÚJO, T. V. Introdução à Economia Computacional. Lisboa: Almedina, 2011.
• BARABÀSI, A. L. (2016). Network Science. Cambridge, UK: Cambridge University Press, 2016.
• CARMO, J.; SERNADAS, A. et al (2014). Introdução à Programação em Mathematica. 3ª ed. Lisboa: Instituto Superior Técnico.
• COMPUTATIONAL ECONOMICS – official journal of Society for Computational Economics. https://link.springer.com/journal/10614 .
• DON, E. (2009). Mathematica. 2nd ed. New York: McGraw-Hill.
• DOWNEY, A. B. (2012). Think Python. 2nd ed. Needham, Massachussets: Green Tea Press/O’Reilly Media Inc. Avaliable at: greenteapress.com/thinkpython/thinkpython.pdf.
• DIEBOLD, F. X. Financial and Macroeconomic Connectedness. http://financialconnectedness.org/research.html (links para vários artigos deste autor).
• FURTADO, B. A; SAKOWSKI, P .A M. e TÓVOLI, M. H. (2015). Modelagem de Sistemas Complexos para Políticas Públicas. Brasília: IPEA.
• GAMA. J.; CARVALHO, A. P. L.; FACELI, K. et al. (2015). Extração de Conhecimento de Dados – Data Mining. 2ª ed. Lisboa: Edições Sílabo.
• JACKSON, M. O. Social and Economic Networks. Princeton, New Jersey: Princeton University Press, 2010.
• JUDD, K. L. (1996). Computational Economics and Economic Theory: Substitutes or Complements? Stanford, California: Stanford University. Available at: https://web.stanford.edu/~judd/papers/scekey.pdf
• KENDRICK, D. A.; MERCADO, P.R. & AMMAN, H. (2005). Computational Economics. Princeton University Press.
• LABORATORY FOR SIMULATION DEVELOPMENT (LSD) – www.labsimdev.org/Joomla_1-3/
• MITCHELL, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web. 2nd ed. Massachussets: O’Reilly Media Inc.
• MIRANDA, M. J. (2002). Applied Computational Economics and Finance. Massachussets: The MIT Press.
• PERKOVIC, L. (2015). Introduction to Computing Using Python. 2nd ed. New Jersey: John Wiley & Sons.
• PERLIN, M. S. (2018). Processamento e Análise de Dados Financeiros com o R. Rio de Janeiro: Agência Brasileira do ISBN.
• REICH, G. P. (2015). Three Essays in Computational Economics. Zurich: University of Zurich Faculty of Economics. Dissertation available at: www.zora.ch/id/eprint/111777/2/DissGregorReich_ohne_CV.pdf
• SARGENT, T. J. and STACHURSKI, J. (2017). Quantitative Economics Lectures – Python 3. New York: Alfred P. Sloan Foundation. Available at: HTTPS://lectures.quantecon.org .
• SCHMEDDERS, K. and JUDD, K. L. (2017). Handbook of Computational Economics. Vol. 3. Amsterdam: New-Holland/Elsevier
• SOCIETY FOR COMPUTATIONAL ECONOMICS – comp-econ.org.
• STINESPRING, J.R. (2002) Mathematica for Microeconomics: Learning by Example. Academic Press/Harcourt Inc.: San Diego, California.
• TESTFATSION, L. and JUDD, K. (2006) Handbook of Computational Economics – Agent Based Computational Economics. Vol. 2. Amsterdam: NewHolland/Elsevier.
• TESTFATSION, L. (2005). Agent-Based Computational Economics: A Constructive Approach to Economic Theory. Ames, Iowa: Iowa State University.
• VARIAN, H. (1996). Computational Economics and Finance: Modelling and Analysis with Mathematica. Vol. 2. Springer.
• WICKHAM, H. e GROLEMUND, G. (2016). R for Data Science: Import, Tidy, Transform, Visualize and Model Data. Massachussets: O’Reilly Media Inc.

Bibliografia Complementar:

• BLACHMAN, N. (1992) Mathematica: a practical approach. Englewood Cliffs, New Jersey: Prentice-Hall.
• CHARVEN, K. (2013). Mastering Gephi Visualization. Birmingham, UK: Packt Publishing.
• GEPHI – THE OPEN GRAPH VIZ PLATFORM – https://gephi.org
• KOKHAR, D. (2015). Gephi Cookbook. Birmingham, UK: Packt Publishing.
• NAGLE, R. K.; SAFF. E.B. e SNIDER, A. D. (2012). Equações Diferenciais. 8ª ed São Paulo: Pearson. (ver os manuais do Matlab e do Mathematica disponíveis no site de apoio ao livro).
• RABUSKE, M. A. (1992). Introdução à Teoria dos Grafos. Florianópolis: Editora da UFSC