Undergraduate Programme and Module Handbook 2021-2022 (archived)

Module ECON2061: ECONOMIC DATA ANALYSIS

Department: Economics and Finance

ECON2061: ECONOMIC DATA ANALYSIS

Type	Open	Level	2	Credits	20	Availability	Available in 2021/22	Module Cap		Location	Durham

Prerequisites

Principles of Economics (ECON1011) AND EITHER Economic Methods (ECON1021) OR (MATH1061) Calculus I AND (MATH1597) Probability I AND (MATH1071) Linear Algebra I OR (MATH1617) Statistics I AND (MATH1561) Single Maths A OR (MATH1551) Maths for Engineers and Scientists AND (MATH1617) Statistics I 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

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 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, seminars and computer practicals. Learning takes place through attendance at lectures, preparation for and participation in seminar classes, computer practicals, and private study. Formative assessment is continuous in the form of quizzes. 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
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	■
Drop-In Sessions	18	1 per week	1 hour	18
Preparation and Reading				130
Total				200

Summative Assessment

Component: Examination		Component Weighting: 80%
Element	Length / duration	Element Weighting	Resit Opportunity
One 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 test and continuous assessment in the form of quizzes.

■ 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