Academic Handbook Course Descriptors and Programme Specifications
LECON5213 Econometrics and Programming Course Descriptor
Last modified on May 24th, 2024 at 1:22 pm
Course code | LECON5213 | Discipline | Economics |
UK credit | 15 | US credit | 4 |
FHEQ level | 5 | Date approved | November 2022 |
Core attributes | |||
Pre-requisites | LMATH4213 Mathematics
AND LMATH4216 Statistics |
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Co-requisites | N/A |
Course Overview
This course looks at statistical techniques in cross-sectional, panel and time-series analysis with particular focus on programming applications in the widely used software package R. Students learn how to carry out regression analysis in R and critique the results. The course covers key ideas in econometric theory to empirically evaluate a range of economic concepts and policy suggestions, using cases from around the world.
Learning Outcomes
On successful completion of the course, students will be able to:
Knowledge and Understanding
K1b | Use the key concepts of econometrics to explain how econometric methods enhance the practice of economics as a field of research.. |
K2b | Explain the underlying assumptions that justify the econometric techniques taught in the course, and deploy this knowledge in economic analysis. |
K3b | Explain the uses of the least squares estimator, and evaluate the suitability of an econometric technique for a given dataset. |
Subject Specific Skills
S1b | Use econometric models and methods to analyse real data in economics, and critically interpret the results. |
S3b | Evaluate and discriminate between alternative econometric models that can be used within a given context. |
S2b, | Draw balanced conclusions from econometric analysis when given data and an empirical question. |
Transferable and Employability Skills
T1b | Make appropriate academic use of economic reports and/or journal articles that make use of the concepts and methods introduced in the course, and produce clear, concise, and informative writing using the conventions of Economics. |
T3b | Demonstrate a sound technical proficiency in written English and skill in selecting vocabulary so as to communicate effectively to specialist and non-specialist audiences. |
Teaching and Learning
This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students in their studies.
The scheduled teaching and learning activities for this course are:
Lectures/seminars
40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours.
Version 1:all sessions in the same sized group
OR
Version 2: most of the sessions in larger groups; some of the sessions in smaller groups
Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.
Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.
Dedicated mathematics support will be available to all students during teaching weeks.
Indicative total learning hours for this course: 150
Assessment
Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.
Summative Assessments
AE: | Assessment Activity | Weighting (%) | Duration | Length |
1 | Written Assignment | 40% | 1,000 words | |
2 | Examination | 60% | 105 minutes |
The course is assessed first by a written assignment, in which students will carry out an in-depth written analysis and use learnt econometric theory to empirically evaluate a meaningful causal relationship of the student’s choice. The examination will require students to demonstrate their command of writing for both Economics specialists and non-specialists. and test students’ understanding of key concepts taught during the course and their ability to solve theoretical problems Further information about the assessments can be found in the Course Syllabus
Feedback
Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).
Indicative Reading
Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.
- Theory: Woolridge, J. (2009) Introductory Econometrics.
- Programming (optional): Gujarati, D. (2014), Econometrics by Example, Basingstoke: Palgrave Macmillan.
Indicative Topics
Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below is used as a general guide and part of the approval/modification process only.
- Linear Regression
- Sources of Endogeneity
- Panel Data Analysis
- Time series Analysis
Title: LECON5213 Econometrics and Programming Course Descriptor
Approved by: Academic Board Location: academic-handbook/programme-specifications-and-handbooks/undergraduate-programmes |
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Version number | Date approved | Date published | Owner | Proposed next review date | Modification (As per AQF4) & category number |
1.0 | November 2022 | January 2023 | Dr Marianna Koli | November 2027 |