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2011/2 Provisional Module Catalogue - UNDER CONSTRUCTION & SUBJECT TO CHANGE
 Module Code: ECOM023 Module Title: ECONOMETRICS
Module Provider: Economics Short Name: EC603B
Level: M Module Co-ordinator: PIERSE RG Mr (Economics)
Number of credits: 15 Number of ECTS credits: 7.5
 
Module Availability

Spring

Assessment Pattern
Unit(s) of Assessment

Weighting Towards Module 
Mark (%)

2 hour Examination

75

Coursework

25


Qualifying Condition(s)
A weighted aggregated mark of 50% is required to pass the module
Module Overview

The module builds on the Quantitative Methods in Economics (ECOM022) introducing several new topics and making use of matrix algebra.

Prerequisites/Co-requisites

None

Module Aims

This module builds on the Quantitative Methods in Economics module (ECOM022). Asymptotically valid methods of estimation and hypothesis testing are introduced and we look at models involving several equations. Limited dependent variable and panel data models are also examined. Matrix algebra is used extensively to explore the properties of the models

Learning Outcomes

On successful completion of this module you should:

  • Understand the maximum likelihood principle and its application to different models
  • Be able to derive the asymptotic properties of estimators and tests
  • Appreciate issues of identification and estimation methods in simultaneous systems
  • Be familiar with techniques for estimation in models with limited dependent variables with panel data
Transferable Skills:
  • Ability to estimate and test econometric equations in standard software
  • Preparation for dissertation in using applied economic techniques

     

Transferable Skills:

 

Transferable Skills:

 

Module Content

The following is an indication of the likely topics to be covered 

  • Review of Matrix Algebra
  • OLS estimation using matrix algebra
  • GLS estimation; Seemingly Unrelated Regression (SUR) model
  • Maximum Likelihood estimation; Wald, LR and LM tests
  • Limited dependent variable models: Identifcation, estimation and testing
  • Panel data estimation: Fixed and random effects models
  • Simultaneous equations: Identification, estimation and testing
  • Introduction to VAR (Vector Autoregressive) models; Granger causality
  • Cointegration in VAR models

     

     

     

     

     

     

     

     

     

     

     

     

  • Methods of Teaching/Learning

    Lectures (20 hrs) and Classes (10 hrs)
    Reading using lecturers guidance
    Preparing exercises for discussion in class
    Responding to questions in class
    Preparing and producing an applied econometrics assignment as coursework

    Selected Texts/Journals

    Main Texts: 
    Greene,W.H., Econometric Analysis, Prentice Hall (latest edition) Verbeek,M., A Guide to Modern Econometrics, Wiley (latest edition) Auxiliary texts: 
    Gujarati, Basic Econometrics, 3rd edition, McGraw-Hill, (latest edition) Maddala, GS, Introduction to Economics, Macmillan (latest edition) 
    Thomas, RL, Introductory Econometrics, Longman(latest edition)

    Last Updated

    10 March 2011