1.

Class Title

Applied Econometrics

credit value

12

standard / level

Masters (Diploma stage of Masters Programme)

core / optional

optional

semester

Semester 2 (except when taken by Open Learning)

pre-requisites

31942 Data Handling and Analysis

session

2005-06

2.

Contact details

Lecturer in Charge

Roger Perman

telephone number

0141 548 3845

e-mail address

r.perman@strath.ac.uk

Administrator

Joyce Russell

telephone number

0141 548 3865

e-mail address

j.m.russell@strath.ac.uk

3.

Overview

The class is offered in the belief that an important part of the work of economists comprises the empirical analysis of economic issues. Students will begin this class with some previous econometric background, including that obtained on the DHA core class. At completion of this class, it is expected that each student will have a good knowledge of, and practical experience in, those econometric and statistical techniques that are likely to be used by practising economists.

4.

Syllabus

Lecture topics are given in the following table:

5.

Class Materials

Internet Resources

This module makes use of a number of Internet resources. These resources are an important part of the class documentation. In addition, some of the reading for this module will only be available over the web. The homepage for this class - including an up-to-date week by week timetable, lab exercises and associated data sets, detailed reading recommendations, and lecture notes/presentations - is located at

http://homepages.strath.ac.uk/~hbs96127/mscempaeoutline.htm

Reading

The following text is recommended for purchase:

• Stock, James H. and Watson, Mark W. (2003) Introduction to Econometrics.

This book is excellent on several parts of the syllabus, but does not cover all the course in the way we would like. It will also be necessary to make use of one or more of the other references listed below (but not to buy them). A second useful textbook that we shall be trialing this year is "Introductory Econometrics" by Jeffrey M. Wooldridge. (2nd edition, Thomson). This would be particularly useful for the first three weeks of the class.

We are aware that Stock and Watson is quite expensive (currently only available in paperback at around £43 from Amazon UK ) so you may be unwilling to buy this text. You might consider sharing copies. A small number will be available in the library short-loan collection.

Detailed reading lists will be distributed during the class.  A number of other useful texts is available in the library short loan collection including:

• Thomas R L (1997) Modern Econometrics, Addison-Wesley.
• Enders, W. (1995) "Applied Econometric Time Series", Wiley.
• Kennedy P (1997) A Guide to Econometrics, 4th edition, Blackwell.
• Thomas R L (1993) Introductory Econometrics: Theory and Applications, 2^nd edition.

If you have studied econometrics before and purchased a recommended text, please ask one of the module staff whether the book(s) you used there might be acceptable substitutes for Stock and Watson.

6.

Assessment Structure

General

The class will be assessed by two pieces of computer-based classwork. There is no formal examination for this class.

Module Specific Assessment Criteria

One item of the assessed classwork will require you to construct, discuss and report on a portfolio of your work from the computer lab sessions. You will also be asked to prepare an Executive Summary of your report. In particular, it will involve an extensive piece of empirical analysis, using the techniques learned in the class.

The second item will require that you carry out an investigation, using cointegration analysis, into the possible existence of a long-run relationship between a set of variables. You are required to write up, explain and justify your findings in the report.

Each piece of classwork is required to demonstrate:

• the use of statistical techniques to formulate, estimate and draw inferences from econometric models;
• understanding of the way in which those results can be given economic interpretations;
• ability to communicate with other economists, and with non-specialists, in a comprehensible and effective manner.

7.

Learning Outcomes

Some specific outcomes that we seek, that should reflect skills the student is expected to have learned and mastered, include:

 Knowledge and Understanding

• Building upon previous knowledge in this area, a developed and enhanced understanding of  good-practice econometric and statistical techniques.
  
  
• The ability to apply these techniques in a critical and thoughtful way in the contexts of both cross-section and time-series data sets.
  
  
• Good methodological practice in applied analysis: the ability to specify regression models in a way that is appropriate to the task in hand; the ability to search for valid parsimonious specifications; the ability to assess whether estimated regressions models are statistically sound; and the ability to respond in an appropriate manner to evidence of model misspecification.
  
  
• Understanding of the techniques of prediction and forecasting, in sample and out of sample, with both cross-sectional and time series regression models.
  
  
• Recognition of the non-stationary nature of much economic and financial time series data, and a knowledge of how to conduct estimation and inference where data may be non-stationary.
  
  
• Oral presentation skills: the ability to present findings from empirical analysis to an audience of staff and fellow students, and to justify and defend those findings.

Practical Professional Skills

• Practical experience with the main components of the set of quantitative skills likely to be used by practising economists.
  
  
• The ability to undertake business and economic forecasting using univariate time series (ARMA/ARIMA) techniques and, where appropriate, simple econometric models.
  
  
• Transferability of quantitative skills. It is expected that skills learned in the class will be generic in nature, and that the student is equipped with the ability and skills required for learning and using new software packages as they are developed.
  
  
• The ability to present complex empirical findings in the form of a written report that effectively and simply communicates its main findings, and the ability to present findings from empirica analysis to a business or public sector audience, and to justify and defend those findings.

8.

Elements of Teaching

This module will be taught over the first 8 weeks of Semester 2, using a combination of lectures (16 contact hours) and computer-based laboratory sessions (8 contact hours). Some tutorial sessions will also be arranged to discuss and interpret results of exercises set during the module.

Lectures - There are 16 lecture hours for this module, arranged as 16 sessions of 60 minutes duration. 

Computer Laboratory Sessions - There will be 8 computer laboratory sessions, each of one hour duration. In these, the student will be given instruction and practice in the techniques required to apply data analysis techniques.

Tutorial sessions - It is expected that 6 one-hour tutorial sessions will be arranged, to provide an opportunity to discuss and reflect upon the theoretical material and its applications in the computer laboratory sessions.

9.

Teaching Staff

• Robin Alpine: DUN 6.07, tel 548 3849, e-mail r.l.alpine@strath.ac.uk
• Roger Perman: DUN 6.09, tel 548 3845, e-mail r.perman@strath.ac.uk

10.

Additional Information

None

11.

Complaints Procedure, Equal Opportunities and Disability Service

Information on the University's Complaints Procedure, Policy on Equal Opportunities and Provision for Students with Special Needs is contained in the MSc EMP Handbook 2005-06. This information is also available on the Faculty's Undergraduate Student Handbook and on the University's web pages: http://www.strath.ac.uk

Students with Special Needs should see the Module Administrator, Joyce Russell, as soon as possible.  Students who believe they may need additional support or equipment, but have not spoken to anyone in the University about it yet should also contact the University's Disability Service, Level 4, Graham Hills Building, tel: 0141 548 3402, web: http://www.mis.strath.ac.uk/SSS