Undergraduate Programme and Module Handbook 2010-2011 (archived)

Module ECON2061: ECONOMIC DATA ANALYSIS

Department: Economics, Finance and Business (Economics and Finance)

ECON2061: ECONOMIC DATA ANALYSIS

Type	Open	Level	2	Credits	20	Availability	Available in 2010/11	Module Cap	None.	Location	Durham

Prerequisites

Economic Methods (ECON1021) AND Elements of Economics (ECON1011).

Corequisites

Any Level 2 Economics module.

Excluded Combination of Modules

None.

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 Regression, Choice of Regressors, Hypothesis Tests in Regression, Introduction to Multicolinearity, General Testing of Restrictions, Stability, Dummy Variables, Heteroscedasticity, Serial Correlation, Diagnostic Tests.
Examples will include Demand Functions, Government Expenditure, Rational Expectations and Production Functions.

Learning Outcomes

Subject-specific Knowledge:

Understand and perform regression analysis

Subject-specific Skills:

Set in context results from empirical research
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 project, 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, workshops and computer practicals. Learning takes place through attendance at lectures, preparation for and participation in tutorial classes, workshops, computer classes, 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	31	2 per week	1 hour	31
Tutorials	5	1 every 2 weeks	1 hour	5	■
Workshops	3	Terms 1 and 2	1 hour	3	■
Computer Practicals	3	3 in term 2	1 hour	3	■
Preparation and Reading				158
Total				200

Summative Assessment

Component: Examination		Component Weighting: 60%
Element	Length / duration	Element Weighting	Resit Opportunity
One written examination	1 hour 30 mins	100%
Component: Assignment		Component Weighting: 40%
Element	Length / duration	Element Weighting	Resit Opportunity
One written assignment	2500 words max	100%

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