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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Economics : Economics

Postgraduate Course: Advanced Time Series Econometrics (ECNM11049)

Course Outline
SchoolSchool of Economics CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis 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.
Course description Not entered
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Econometrics 1 (ECNM11043) AND ( Econometrics 2 - Time Series (ECNM11089) OR Econometrics 2 - Applied Microeconometrics (ECNM11090))
Co-requisites
Prohibited Combinations Other requirements Students may take either of the Econometrics 2 courses as a pre-requisite for this course, but are strongly advised to take Econometrics 2 - Time Series (ECNM11089).
Information for Visiting Students
Pre-requisitesStudents 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
Academic year 2022/23, Available to all students (SV1) 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 )
Assessment (Further Info) Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
Additional Information (Assessment) Final Assessment: A two hour written exam and provides 100% of your final mark in this class.
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
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.
Reading List
None
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.
KeywordsNot entered
Contacts
Course organiserDr Tatiana Kornienko
Tel: 0131 650 8338
Email: Tatiana.Kornienko@ed.ac.uk
Course secretaryMs Grace Oliver
Tel:
Email: grace.oliver@ed.ac.uk
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