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2011/2 Provisional Module Catalogue - UNDER CONSTRUCTION & SUBJECT TO CHANGE
 Module Code: ECO3003 Module Title: TIME SERIES ECONOMETRICS
Module Provider: Economics Short Name: EC412
Level: HE3 Module Co-ordinator: GABRIEL V Dr (Economics)
Number of credits: 15 Number of ECTS credits: 7.5
 
Assessment Pattern
Unit(s) of Assessment 

Weighting Towards Module 
Mark (%)

2 hour Examination

50

Coursework 1

20

Coursework 2

30


Qualifying Condition(s)
A weighted aggregated mark of 40% is required to pass the module
Module Overview
By the end of the module students will have learnt how to carry out empirical analyses using economic and financial time series data; how to interpret the results of such analyses; and will ahve acquired an ability to critically assess empirical papers
Prerequisites/Co-requisites

None

Module Aims
The aim of this module is to provide the student with the theoretical and practical skills necessary to construct state of the art, single equation econometric models.The module will equip the student with the ability to undertake, understand, and critically assess empirical work in economics, with a view to enabling the student to use econometrics to catalogue and describe empirical regulatities and test various propositions
Learning Outcomes

By the end of the module students will:-

  1. have thoroughly revised and gained a deep understanding of the underlying statistical foundations of econometrics
  2. be able to critically assess published econometric results
  3. be able to formulate, estimate and interpret an econometric time series model
  4. be able to write up the results of a study of an economc problem that includes econometric analysis
  5. become a proficient user of the time series testing and estimation capabilities of Eviews
Module Content

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

  • The classical linear regression model: review of underlying statistical theory. Properties of estimators and test statistics
  • Stationary time series models
  • Dynamic models: Distributed lags and models of expectations, erro correction models.
  • Econometric modelling methodology - Hendry's General to specific modelling strategy for econometric time series models
  • Random walks, tests for unit roots. Cointegration. Application to macroeconomic time series
  • Modeling Volatility in Financial Time Series
Methods of Teaching/Learning
Lecturers (10), Computing Workshops (3)
Readings using lecturers guidance
Responding to questions in class
Preparing and taking part in the coursework tests
Last Updated

10 March 2011