Teaching simulation methods in economics

Michael Reiter

No 37, Computing in Economics and Finance 2006 from Society for Computational Economics

Abstract: I will discuss my experiences with the course "Simulation methods", given several times in the graduate program of the University Pompeu Fabra, Barcelona. The main topics of the course are 1) Basic techniques of numerical analysis: nonlinear unconstrained and constrained optimization, nonlinear systems of equations, function interpolation, etc. 2) Numerical dynamic programming 3) Solution of linear(ized) rational expectations models 4) Projection methods. The course is for 2nd year PhD students. Most students have a specialization in macroeconomics, but some come from microeconomics or finance. Therefore, applications include business cycle models, models of optimal fiscal and monetary policy, optimal portfolio choice and option pricing. For more detailed information on the course, see the syllabus at http://www.econ.upf.es/eng/graduates/gpem/pdf/courses/05-06/simulmeth.pdf The course homepage is http://www.econ.upf.es/~reiter/sim.html. All the programming is done in Matlab. I will talk about the experience with this, and about ways of overcoming some shortcomings of Matlab programming.

Keywords: computational economics; teaching (search for similar items in EconPapers)
Date: 2006-07-04
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:37

Access Statistics for this paper

More papers in Computing in Economics and Finance 2006 from Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().