Module
Econometric Theory II
Module description
This module builds on Econometric Theory I and further develops your knowledge and understanding of econometric and methodological research tools and the application of various econometric methods and techniques to real life problems.
Additional Information:
Internationalisation
The methods covered in this module, such as those used to forecast inflation and GDP, are applicable across countries.
Sustainability
Resources for this module are available on the ELE (Exeter Learning Environment).
Employability
Students gain an understanding of the statistical techniques used to study topics such unemployment and forecasting inflation and economic growth which are all necessary skill for working in central banks. They also develop their numerical and problem-solving skills in learning these mathematical techniques.
Full module specification
Module title: | Econometric Theory II |
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Module code: | BEEM142 |
Module level: | M |
Academic year: | 2023/4 |
Module lecturers: |
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Module credit: | 15 |
ECTS value: | 7.5 |
Pre-requisites: | BEEM139. Only available to students on the MRes Economics and MRES Economics (PHD Pathway) programmes. |
Co-requisites: | None |
Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
This module aims at providing the students with the necessary econometric and methodological research tools to equip them for carrying out empirical research projects as well as understand the contents of other modules.
The module is dedicated to the application of various econometric methods and techniques to real life problems.
ILO: Module-specific skills
- 1. apply modern econometric techniques in the analysis of economic data
ILO: Discipline-specific skills
- 2. formulate hypotheses of interest, derive the necessary tools to test this hypothesis and interpret the results
- 3. show a specialised knowledge of applied aspects of econometrics that will enable him/her to carry out applied research or direct them towards an academic career
ILO: Personal and key skills
- 4. have technical expertise in computing software, particularly econometric software, to tackle empirical problems
- 5. demonstrate confidence in identifying, tackling and solving research problems
Learning activities and teaching methods (given in hours of study time)
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
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32 | 118 |
Details of learning activities and teaching methods
Category | Hours of study time | Description |
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Scheduled Learning and Teaching | 22 | Lectures |
Scheduled Learning and Teaching | 10 | Tutorials |
Independent Study | 118 | Independent study |
Formative assessment
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Weekly exercises | 5-15 questions per week | 1-5 | Oral/Written |
Summative assessment (% of credit)
Coursework | Written exams | Practical exams |
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20 | 80 | 0 |
Details of summative assessment
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Assignment | 20 | 2000 words | 1-5 | Oral/Written |
Final Exam | 80 | 2 hours | 1-5 | Oral/Written |
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Details of re-assessment (where required by referral or deferral)
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
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Assignment | Assignment (20%) | 1-5 | August |
Final exam | Final exam (80%) | 1-5 | August |
Syllabus plan
• Topics:
• Topics in estimation techniques:
1. Maximum Likelihood Estimation
2. Generalized Method of Moments
• Topics in Microeconometrics:
1. Binary choice Models and Limited Dependent Variables
2. Panel Data Models
- Topics in Time Series:
1. Univariate Time Series Models
2. Multivariate Time Series Models
3. Unit Roots and Cointegration
Indicative learning resources - Basic reading
Cameron, C. and P. Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press.
Greene, W. (2008), Econometric Analysis, New Jersey: Prentice Hall, 6th Edition. (main textbook.)
Hamilton, J. D. (1994), Time Series Analysis, Princeton University Press.
Module has an active ELE page?
Yes
Origin date
04/04/2016
Last revision date
11/05/2022