Numerical analysis: mathematics of scientific computing
Numerical analysis: mathematics of scientific computing
Iterative solution of nonlinear equations in several variables
Iterative solution of nonlinear equations in several variables
Applied Computational Economics and Finance
Applied Computational Economics and Finance
Numerical Mathematics and Computing
Numerical Mathematics and Computing
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
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Effective teaching of computational methods to economists in an introductory graduate-level course requires difficult choices regarding the material to be covered, the level at which the material will be covered, and the role of assigned exercises, laboratory sessions, and required readings. In this paper, I discuss the goals that I set and the pedagogical choices that I make in teaching computational methods to doctoral students in economics in a quarter-length course. The discussion is based on 15 years of teaching computational methods to students with a broad range of research interests and professional objectives. I also discuss some of the pedagogical obstacles that I often face when teaching the course and how I address them. I hope that the discussion will provide a useful starting point for instructors wishing to develop computational methods courses in other economics graduate programs.