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Research School of Economics · ANU College of Business and Economics
This course will provide a solid grounding in programming and computational methods for quantitative economic modeling. Students will learn how to use existing numerical algorithms routinely used in economic modeling, such as optimization, linear algebra and basic simulation, as well as how to design, plan and implement specific algorithms for quantitative economic analysis (e.g., dynamic programming, competitive equilibria, solving games). Students will also learn to obtain and manipulate economic and financial data (e.g., use existing data APIs or web scraping) and implement statistical routines such as regression and classification, or new tools from data science. The course will include a project component.
Individual test-assignment with feedback (by week 4)
Mid-term Report
Individual Analytical Project
2 hour lecture + 2 hour tutorial in computer lab
- Jérôme Adda, Russell W. Cooper “Dynamic Economics: Quantitative Methods andApplications”, MIT Press, 2003 - Quantitative Economics online resource Preliminary Reading - Ken Wolpin “The Limits of Inference without Theory”, MIT Press, 2013 - Rust, John (2014): "The Limits of Inference with Theory: A Review of Wolpin (2013)."Journal of Economic Literature, 52(3): 820-50.