Postgraduate Course: Computational Methods in Economics (ECNM11066)
|School||School of Economics
||College||College of Humanities and Social Science
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||This module, optional for all first year PGR students, is designed to introduce and cover in some depth a range of theoretical issues and techniques so as to broaden student's knowledge of computational methods in economics. The aim is to provide exposure to a wide variety of methods that may be used by graduate research students to simulate and solve economic models.
This module, optional for all first year PGR students, is designed to introduce and cover in some depth a range of theoretical issues and techniques so as to broaden student's knowledge of computational methods in economics. The aim is to provide exposure to a wide variety of methods that may be used by graduate research students to simulate and solve economic models. The course will cover in some depth the specification and solution of dynamic stochastic models and of econometric estimation routines using a single computer package. Currently there are two packages and hence two sets of lectures/labs available to students. The first set covers Z-Tree whilst the other covers Python. After consulting with supervisors and PG Directors, students would choose lectures in the software that is most suited to their intended research. Students would be assessed via an assignment set by and graded by the School of Economics.
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| All first year PhD students in Economics will have the option to sit this course subject to the approval of the supervisor(s).
Course Delivery Information
|Not being delivered|
On completion of this course, the student will be able to:
- Although exact topics covered will vary from year to year it is expected that after taking the course all students will be able to: Use practically all of the capabilities and functions of the relevant computational software being taught (currently Python or Z-Tree).
- Use the relevant software to effect simulation of a nonlinear dynamic stochastic economic model.
- (Students taking Z-Tree) Use the software to run experiments
|This is a hands on computing course and the main texts will be the relevant programme manuals.|
|Graduate Attributes and Skills
||See learning Outcomes
|Course organiser||Prof Andy Snell
Tel: (0131 6)50 3848
|Course secretary||Mrs Fiona Ross
Tel: (0131 6)51 5184