TIME SERIES ECONOMETRICS - 2020/1
Module code: ECO3003
In light of the Covid-19 pandemic, and in a departure from previous academic years and previously published information, the University has had to change the delivery (and in some cases the content) of its programmes, together with certain University services and facilities for the academic year 2020/21.
These changes include the implementation of a hybrid teaching approach during 2020/21. Detailed information on all changes is available at: https://www.surrey.ac.uk/coronavirus/course-changes. This webpage sets out information relating to general University changes, and will also direct you to consider additional specific information relating to your chosen programme.
Prior to registering online, you must read this general information and all relevant additional programme specific information. By completing online registration, you acknowledge that you have read such content, and accept all such changes.
By the end of the module students will have learnt how to carry out empirical analyses using appropriate econometric software to study economic and financial time series data; how to interpret the results of such analyses; and will have acquired an ability to critically assess empirical papers.
VOLPICELLA Alessio (Economics)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
JACs code: L140
Module cap (Maximum number of students): N/A
Prerequisites / Co-requisites
Indicative content includes:
- The classical linear regression model: review of underlying statistical theory. Properties of estimators and test statistics.
- Stationary Time Series Models.
- Dynamic models: Distributed lags and models of expectations, error correction models.
- Econometric modelling methodology - General to specific modelling strategy for econometric time series models.
- VAR models
- Random walks, tests for unit roots. Cointegration.
- Modeling Volatility in Financial Time Series.
|Assessment type||Unit of assessment||Weighting|
|School-timetabled exam/test||1 hour computer-based test||30|
|Examination||2 HOUR EXAMINATION||70|
The assessment strategy is designed to provide students with the opportunity to demonstrate:
Their understanding of econometric methods that are commonly used in analysing time series data, and the ability to use relevant computer packages to investigate real world economic problems.
Thus, the summative assessment for this module consists of:
Mid-term computer-based class test in week 8, to be worth 30% of the final mark.
Final written exam containing questions covering all 11 weeks. Worth 70% of the final mark.
Formative assessment and feedback
Students receive verbal feedback during lectures through direct questioning (in which multiple questions and real-world examples of the use of economics are discussed). There are also homework assignments throughout the course, where feedback is provided for all individual questions.In addition to this, they receive guidance and illustrations to the use of Eviews and other relevant econometric packages.
- Provide the student with the theoretical and practical skills necessary to construct state of the art, single and multi-equation econometric models. The module will equip the student with the ability to undertake, understand, and critically assess empirical work in economics, with a view to enabling the student to use econometrics to catalogue and describe empirical regularities and test various propositions.
|1||Understand the underlying statistical foundations of econometrics||KCT|
|2||Critically assess published econometric results;||KCP|
|3||Formulate, estimate and interpret an econometric time series model;||KCPT|
|4||Write up the results of a study of an economic problem that includes econometric analysis;||KCPT|
|5||Proficiently use the time series testing and estimation capabilities of a range of packages (e.g. EViews, Oxmetrics or R)||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Overall student workload
Independent Study Hours: 128
Lecture Hours: 22
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
- give students the theoretical tools they need to go out and analyse real world situations;
- encourage rigour in their approach to problems;
- encourage hands-on study of empirical problems
The learning and teaching methods include:
- 2 hour lecture per week x 11 week
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Reading list for TIME SERIES ECONOMETRICS : http://aspire.surrey.ac.uk/modules/eco3003
Programmes this module appears in
|Economics BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Business Economics BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Finance BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Mathematics BSc (Hons)||1||Optional||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2020/1 academic year.