Postgraduate Course: Advanced Time Series Econometrics (ECNM11049)
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 | 10 |
ECTS Credits | 5 |
| Summary | This module cover topics in time series econometrics beyond those covered in Econometrics 2. Students will be introduced to various tools that are part of the basic econometric training of professional economists. The course is intended for students who want to be professional economists or who want to go on to PhD study. It also is very relevant to those planning to work or research in finance and/or macroeconomics.
The class covers three key classes of model with a practical focus: state space models, nonlinear time series models and factor models. State space models are used for a wide variety of applications in macroeconomics and finance, including trend-cycle decompositions, modelling time-variation in parameters, ARMA modelling and estimating dynamic stochastic general equilibrium (DSGE) models. Non-linear time series models (e.g. Markov switching or threshold autoregressive models) are used to model time-variation or regime change in parameters. Particularly with macroeconomic data, such parameter change is typically found and it is important to account for it when doing empirical work. Factor methods are used to deal with Big Data that researchers in macroeconomics and finance are increasingly using. They reduce the information in large data sets into a small number of factors, allowing for parsimonious econometric analysis.
Taken together, knowledge of these three topics will provide the student with the ability to estimate and forecast with a wide range of important models and deal with empirically important issues that arise in them.
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| Course description |
Not entered
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Information for Visiting Students
| Pre-requisites | Students should be registered for MSc Economics OR MSc Economics (Finance). All other students should have taken and passed a course similar in content to Econometrics 1 ECNM11043 and Econometrics 2 ECNM11089 AND they must email sgpe@ed.ac.uk in advance to request permission. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
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Quota: 0 |
| Course Start |
Block 4 (Sem 2) |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 14,
Supervised Practical/Workshop/Studio Hours 4,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
80 )
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| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Final Assessment: A two hour written exam and provides 100% of your final mark in this class.
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| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S2 (April/May) | | 2:00 | |
Learning Outcomes
| This module explores further topics in time series econometrics, beyond Econometrics 2. Students will be introduced to various tools that are part of the basic econometric training of professional economists. The course is intended for students who want to be professional economists or who want to go on to PhD study. It also is very relevant to those planning to work or research in finance and/or macroeconomics.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Lectures and tutorials will together take up 3 hours per week throughout the six week options block. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Tatiana Kornienko
Tel: 0131 650 8338
Email: |
Course secretary | Ms Grace Oliver
Tel:
Email: |
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