ULMS Electronic Module Catalogue |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | ECONOMETRICS 2 | ||
Code | ECON213 | ||
Coordinator |
Dr GD Liu-Evans Economics Gareth.Liu-Evans@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2019-20 | Level 5 FHEQ | Second Semester | 15 |
Pre-requisites before taking this module (other modules and/or general educational/academic requirements): |
ECON121 PRINCIPLES OF MICROECONOMICS; ECON123 PRINCIPLES OF MACROECONOMICS; ECON212 ECONOMETRICS 1 |
Modules for which this module is a pre-requisite: |
Programme(s) (including Year of Study) to which this module is available on a required basis: |
Programme(s) (including Year of Study) to which this module is available on an optional basis: |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
24 |
5 |
.5 |
29.5 | |||
Timetable (if known) | |||||||
Private Study | 120.5 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Assessment 2: Timed Online MCQ Test Duration: maximum 1.5 hours Weighting: 10% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes Assessm | maximum time of 1.5 | 10 | ||||
Assessment 3: Unseen Examination Duration: 2 hours Weighting: 50% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes Final Assessment: Yes | 2 hours | 50 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Assessment 1: Group coursework project Size: 2500 words Weighting: 40% Reassessment Opportunity: Yes Penalty for Late Submission: Standard Anonymous Assessment: Yes Assessment Notes: | -2500 words | 40 |
Aims |
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The aims of this module are to build on ECON212 by extending the treatment of regression to the multiple regression model and to develop practical research skills which would be expected from a graduate in Economics either as a foundation for postgraduate study or for work as a professional economist recruited at graduate level. |
Learning Outcomes |
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(LO1) Students will be able to explain the assumptions required for OLS multiple regression to be Best Linear Unbiased |
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(LO2) Students will be able to explain the problem of multicollinearity, how it is detected and how it can be resolved |
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(LO3) Students will be able to conduct single and joint hypothesis tests |
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(LO4) Students will be able to test restrictions on coefficients |
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(LO5) Students will be able to construct and interpret confidence intervals around estimates and forecasts |
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(LO6) Students will be able to propose and implement model building strategies and criteria for evaluating model adequacy |
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(LO7) Students will be able to explain, use and interpret dummy variables |
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(LO8) Students will be able to explain and implement the generalised method of moments using instrumental variables |
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(LO9) Students will be able to conduct independent econometric research and present the results in a professional manner |
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(LO10) Students will be able to develop a knowledge of the appropriate quantitative tools used inaddressing real world economic issues. |
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(S1) Problem solving skills |
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(S2) Numeracy |
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(S3) Teamwork |
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(S4) Organisational skills |
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(S5) Communication skills |
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(S6) IT skills |
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(S7) Lifelong learning skills |
Teaching and Learning Strategies |
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Teaching Method: Lecture Teaching Method: Laboratory Work Teaching Method: Group Project Self-Directed Learning Hours: 120.5 Costs Information: There are the following non-modular requirements: This module is a pre-requisite for the following modules: Skills/Other Attributes Mapping Skills / attributes: Lifelong learning skills Skills / attributes: IT skills Skills / attributes: Communication skills Skills / attributes: Organisational skills Skills / attributes: Teamwork Skills / attributes: Numeracy Skills / attributes: Problem solving skills |
Syllabus |
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Multiple Regression |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |