Undergraduate Course: Programming and Numerical Methods for Economics (ECNM10115)
Course Outline
| School | School of Economics |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Programming for Economics is designed to teach the essential skills for computational work in economics. Many economic models cannot be solved analytically but are easy to solve and simulate on a computer. Students who take this course will learn the basics of how to program, how to clean data and calculate basic statistics, and the numerical methods necessary to solve economic models, and estimate them from the data (including, but not limited to, approximating and simulating Markov chains, root finding, constrained optimization, and interpolation, and value function iteration). |
| Course description |
By the end of the course, the students should feel comfortable with programming basics, data management and analysis, and numerical solution methods to many common economic models. Students will also learn how to estimate the parameters of these models using real world data. Programming for Economics will include weekly lab sessions and tutorials to reinforce lectures, and weekly problem sets to give students concrete experience (as well as a portfolio of code they can show to potential employers).
A student who takes this course will learn new programming tools and language, perform data analysis, solve economic models numerically, and estimate economic models. The student will also gain competencies such as programming skills, critical mathematical and computational thinking, and work collaboratively in code projects. At the end of the course, the student should be well prepared for future work on a computational undergraduate dissertation, have the computational knowledge for future employment in private companies and research centers, or for further graduate study.
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2023/24, Available to all students (SV1)
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Quota: 100 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 8,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
168 )
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| Assessment (Further Info) |
Written Exam
60 %,
Coursework
40 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Group-based problem sets with weekly submissions: 40%
Individual take-home exam: 60% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate a knowledge and understanding of key concepts, methods, issues and approaches in computational economics.
- Demonstrate research and investigative skills such as problem framing and solving and the ability to assemble and evaluate complex evidence and arguments.
- Demonstrate communication skills in order to critique, create and communicate understanding and to collaborate with and relate to others.
- Demonstrate personal effectiveness through task-management, time-management, teamwork and group interaction, dealing with uncertainty and adapting to new situations, personal and intellectual autonomy through independent learning.
- Demonstrate practical/technical skills such as, modelling skills (abstraction, logic, succinctness), qualitative and quantitative analysis and general IT literacy.
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Reading List
The nature of this material is that there are very few formal treatments in textbooks, and the textbooks that do exist tend to be geared towards engineers, rather than economists. In general, it is rather difficult to translate between the two approaches. Below, we have collected several approaches that are suitable for the undergraduate level, and which can serve as informal references for the course. Most of the formal course materials will be slides and other lecture notes, which will be posted on the course website.
- Numerical Methods in Economics, by Kenneth L. Judd, 1998
- Quantitative Economics founded by T. Sargent and J. Stachurski |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | programming,numerical methods |
Contacts
| Course organiser | Dr Jacob Adenbaum
Tel:
Email: Jacob.Adenbaum@ed.ac.uk |
Course secretary | Mr Luke Scott
Tel: (01316) 515305
Email: lscott11@ed.ac.uk |
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