Postgraduate Course: Econometrics 1 (ECNM11043)
Course Outline
| School | School of Economics |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Together with the Econometrics 2 courses, this module provides a thorough training in basic econometric methods to enable you to critically assess applied work as well as to undertake your own using appropriate econometric techniques. You will acquire the background required for research at the PhD level or in employment as a professional applied economist. |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Mathematics, Statistics and Econometrics (ECNM11002)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Students should be enrolled on MSc Economics, MSc Economics (Econometrics), MSc Economics (Finance) or MSc Mathematical Economics and Econometrics.
Any other students must email sgpe@ed.ac.uk in advance to request permission.
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Information for Visiting Students
| Pre-requisites | Students should be enrolled on MSc Economics, MSc Economics (Econometrics), MSc Economics (Finance) or MSc Mathematical Economics and Econometrics.
Any other students must email sgpe@ed.ac.uk in advance to request permission.
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| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2024/25, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 36,
Seminar/Tutorial Hours 15,
Supervised Practical/Workshop/Studio Hours 18,
Feedback/Feedforward Hours 14,
Formative Assessment Hours 3,
Summative Assessment Hours 3,
Revision Session Hours 5,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
102 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
The tutorials focus on solving homework questions and dealing with any issues which individual students might have.
Labs teach how to use statistical software for both practical empirical applications and for exploring theoretical properties of econometric estimators and procedures.
There is a single class exam at the end of the course. The exam covers both theoretical concepts and tools and empirical applications.
Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
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| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S1 (December) | Econometrics 1 December Exam 2024 | 3:180 | |
Learning Outcomes
| You will be able to critically assess applied work as well as to undertake your own using appropriate econometric techniques. You will acquire the background required for research at the PhD level or in employment as a professional applied economist.
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Reading List
The main textbook is Fumio Hayashi (2000), Econometrics, Princeton University Press.
Supplementary textbook: Bruce Hansen (2022), Econometrics, Princeton University Press.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
This module consists of approximately 38 hours of lectures which are supported by approximately weekly lab/tutorial sessions (2 hours per week) and a help-desk.
Part A (Robin Alpine) 3 weeks - An introduction to classical econometrics
In this part we will cover the fundamentals of the general linear model: OLS; Gauss-Markov Theorem; inference; dummy variables; and other techniques.
Part B (Mark Schaffer) 6 weeks - Core econometrics
The motivating framework for much of the second part of the course is GMM (the Generalized Method of Moments). Topics covered will include: OLS, IV and other GMM estimators; large sample theory; GLS; maximum likelihood (ML); robust covariance estimation; system estimation; basic panel data.
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| Keywords | Not entered |
Contacts
| Course organiser | Prof Mark Schaffer
Tel:
Email: m.e.schaffer@hw.ac.uk |
Course secretary | Ms Sam Stewart
Tel:
Email: v1sstew7@ed.ac.uk |
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