Undergraduate Programme and Module Handbook 2019-2020 (archived)
Module ECON2061: ECONOMIC DATA ANALYSIS
Department: Economics and Finance
ECON2061: ECONOMIC DATA ANALYSIS
| Type | Open | Level | 2 | Credits | 20 | Availability | Available in 2019/20 | Module Cap | Location | Durham |
|---|
Prerequisites
- Principles of Economics (ECON1011) AND EITHER Economic Methods (ECON1021) OR (MATH1061) Calculus and Probability I AND (MATH1071) Linear Algebra I OR (MATH1541) Statistics AND (MATH1561) Single Maths A OR (MATH1551) Maths for Engineers and Scientists AND (MATH1541) Statistics OR successful completion of Phase 1 of the Economics programme at Shandong University, China
Corequisites
- Any Level 2 Economics module.
Excluded Combination of Modules
- Any Level 2 statistics module in the Mathematics department.
Aims
- To enable students to read and understand the typical empirical analysis as utilised in much of the economic literature.
- To enable students to write a report based on econometric analysis.
- To build on the material of Economic Methods
- To provide relevant material to be utilised in other core and optional modules.
Content
- Ordinary Least Squares Estimation;
- Choice of Regressors;
- Hypothesis Tests in Regression;
- Multicolinearity;
- General Testing of Restrictions;
- Stability;
- Dummy Variables;
- Heteroscedasticity;
- Serial Correlation;
- Endogeneity;
- Panel Data Estimators.
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 and tie the results to relevant literature
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
- Initiative: students, whilst undertaking the assignment, must carry out resource investigation by accessing a range of hard copy and electronic resources, establishing the relevance of the documents for the problem in hand.
- 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 requested 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, tutorials and computer practicals. Learning takes place through attendance at lectures, preparation for and participation in tutorial classes, computer practicals, and private study. Formative assessment is by means of one exercise per student. Summative assessment is by means of a written examination and a written assignment.
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 | |
| Tutorials | 7 | 4 in Term 1, 3 in Term 2 | 1 hour | 7 | ■ |
| Computer Practicals | 2 | 2 in Term 2 | 1 hour | 2 | ■ |
| Preparation and Reading | 147 | ||||
| Total | 200 |
Summative Assessment
| Component: Examination | Component Weighting: 60% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| One written examination | 1 hour 30 mins | 100% | same |
| Component: Assignment | Component Weighting: 40% | ||
| Element | Length / duration | Element Weighting | Resit Opportunity |
| One written assignment | 2500 words max | 100% | same |
Formative Assessment:
One exercise per student
■ 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