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New York University 4 credits Economics GH
Numerical Methods covers basic methods of numerical analysis such as numerical optimization, the solution of linear and nonlinear equation systems, etc. Special attention will be given to numerical methods for dynamic optimization, which are essential for dynamic analysis in all fields of economics. The course will cover in detail the solution of dynamic stochastic equilibrium models, including heterogeneous agent models, as they are used in modern macroeconomics, both in academic work and in central banks. The coursework will be done in Matlab, the language most widely used in economic applications. Introductions will be given to Python, a scripting language used in all fields of computing, and to Julia, a new high-performance computing language. The focus of the course is on the practical implementation of these methods. At the end of the course, participants are supposed to be able to replicate the results of recent papers in quantitative economics. The grade of the course will be based on a series of exercises and a final computational project. Prerequisites: ECON-GH 5600.
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Learn how to write a good research question for a paper. Narrow your topic, identify a research problem, and create a focused question with practical examples.
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