ECO-20042 - Introduction to Econometrics
Coordinator: Reinhold Heinlein Tel: +44 1782 7 33106
Lecture Time: See Timetable...
Level: Level 5
Credits: 15
Study Hours: 150
School Office: 01782 733094

Programme/Approved Electives for 2019/20

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites




Barred Combinations

None

Description for 2019/20

This module is designed especially to cater for the needs of students taking the Single Honous Principal Economics, Business Economics, Principal Finance, or Accounting and Finance. The module is structured to assist them in understanding the technical and quantitative aspects of the subject.
The module will introduce and develop students' understanding of econometrics and the use of statistical methods to investigate selected economic and financial issues (e.g. consumption functions, household labour supply, CAPM) in order to facilitate the reading of published empirical articles in their other modules.

Aims
The aim of this module is to demonstrate the application of theoretical and empirical quantitative methods to particular issues in economics and finance. The unit describes how to formulate an economic model, estimate the model, interpret and evaluate the results. Students will learn these concepts through practical classes, which will lead them to develop investigative/research skills.

Intended Learning Outcomes

Apply the elements of statistical inference in a variety of different contexts
: 1,2,3
Evaluate the adequacy of a given model using a battery of diagnostic tests: 1,2,3
Formulate data analysis problems in a statistical framework, choose appropriate models for situations involving uncertainty, and understand their key elements and properties: 1,2,3
Apply statistical models and methods to solve practical problems; evaluate statistical evidence; interpret the results of statistical analyses; comment critically on econometric modelling approaches.
: 1,2,3
Use industry standard software for statistical analysis: 1,2,3
Use the methodologies for data analysis, such as: analysis of variance and simple and multiple regression
: 1,2,3

Study hours

24 hours lectures
10 hours tutorials/lab classes
20 hours preparation for classes
20 hours assignment preparation
76 hours independent study

School Rules

ECO-20049 Statistics with Bloomberg

Description of Module Assessment

1: Portfolio weighted 20%
Portfolio consisting of 4 online exercises set during the semester.
Exercises will be marked when submitted at different points during the semester. Best 3 marks will contribute to overall assessment.

2: Exam weighted 60%
Two-hour end of semester unseen examination
Two-hour, closed book examination

3: Report weighted 20%
Short report based on lab class exercise
800-word report on STAT output analysing a data set used during the computer lab classes.