Undergraduate Programme and Module Handbook 2024-2025
Module ECON2061: ECONOMETRICS
Department: Economics
ECON2061: ECONOMETRICS
| Type | Tied | Level | 2 | Credits | 20 | Availability | Available in 2024/2025 | Module Cap | Location | Durham |
|---|
| Tied to | L100 |
|---|---|
| Tied to | L106 |
| Tied to | L109 |
| Tied to | L103 |
| Tied to | L104 |
| Tied to | L105 |
| Tied to | LL12 |
| Tied to | LL02 |
| Tied to | LL01 |
| Tied to | VL52 |
| Tied to | VLL6 |
| Tied to | VLLA |
| Tied to | CFG0 |
| Tied to | CFC0 |
| Tied to | FGC0 |
| Tied to | LMVA |
| Tied to | LMV0 |
Prerequisites
- Principles of Economics (ECON1011) AND EITHER Economic Methods (ECON1021) OR Calculus I (MATH1061) AND Linear Algebra I (MATH1071) AND Probability I (MATH1597) AND Statistics I (MATH1617)
Corequisites
- None.
Excluded Combination of Modules
- None.
Aims
- To enable students to identify and apply appropriate econometric methods to answer economic questions.
- To enable students to interpret the results of econometric analyses.
- To enable students to understand and critically evaluate econometric analyses from the economics literature.
- To build on the material of Economic Methods.
Content
- Topics covered likely to include:
- Linear Regression
- Hypothesis Tests on Regression Coefficients
- Nonlinear Regression Functions
- Assessing Validity of Regression Analyses
- Regression with Panel Data
- Regression with Binary Variables
- Instrumental Variables Regression
- Introduction to Regression with Time Series Data
Learning Outcomes
Subject-specific Knowledge:
- Understand and perform regression analysis
Subject-specific Skills:
- ability to set in context results from empirical research
- ability to conduct and manage a small-scale empirical project using econometric analysis
Key Skills:
- Written Communication: the summative assessment includes both a written report and a written examination.
- Problem Solving: the exercises will require students to use the basic material to solve problems tested in the summative assessment
- Numeracy: students are expected to perform econometric tests and interpret empirical work to the level of their knowledge.
- Computer Literacy: the project will be word-processed and the analysis assignment will require the use of an econometric package.
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- Teaching is by lectures, seminars and computer practicals. Learning takes place through attendance at lectures, preparation for and participation in seminars, computer practicals, and private study. Summative assessment is by means of an in-person examination and assignment. Formative assessment is by means of a piece of written work to prepare for the exam.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | |
|---|---|---|---|---|---|
| Lectures | 20 | 1 per week | 2 hours | 40 | |
| Revision Lectures | 2 | 1 per week in Term 3 | 2 hours | 4 | |
| Seminars | 6 | 3 in Term 1, 3 in Term 2 | 1 hour | 6 | ■ |
| Computer Practicals | 2 | 1 in Term 1, 1 in Term 2 | 1 hour | 2 | ■ |
| Preparation and Reading | 148 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 80% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| One in-person written examination | 2 hours | 100% | Same |
| Component: Assignment | Component Weighting: 20% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| One written assignment | 1500 words max | 100% | Same |
Formative Assessment:
One written piece of work to prepare students for the summative exam.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University