Module Information

Module Identifier
Module Title
Academic Year
Semester 1

Course Delivery

Delivery Type Delivery length / details
Lecture 12 one hour lectures
Seminars / Tutorials 6 one hour tutorials
Practical 6 one hour computer practicals
Workload Breakdown 24 contact hours 100 hours of study and review relating to lectures, tutorials, and computer practicals 30 hours preparing coursework 46 hours of revision for the examination


Assessment Type Assessment length / details Proportion
Semester Exam 2 Hours   Written examination  60%
Semester Assessment Coursework  Based on an assignment which entails the preparation of a report based on computer practical work  40%
Supplementary Exam 2 Hours   Repeat failed element  60%
Supplementary Assessment Repeat failed element  40%

Learning Outcomes

On successful completion of this module students should be able to:

* Demonstrate an extensive knowledge of the models of time-series analysis, and be able to;

* Discuss and make use of appropriate econometric techniques, estimate, evaluate and interpret regression results and trst various hypotheses;

* Carry out advanced diagnostic tasks and develop parimonious models using a systematic modelling strategy;

* Regognize the circumstances when simultaneous equation analysis is appropriate;

* Apply appropriate econometric techniques to study various phenomena in economics, finance, and related subject areas;

* Complete small scale empirical projects independently, using dedicated econometrics software such as Microfit.


This is a highly specialised module which provides students with an opportunity to study more advanced quantitative tools and topics in econometrics widely used in applied research in economics, finance and related subject areas.

Brief description

Building on EC30920 Introduction to Econometrics the module aims to introduce students to, and encourage critical engagement with, more advanced topics in econometrics. Particular emphasis will be on the application of empirical methods in time series analysis widely used in applied economics, finance, and related subject areas.


  • Brief Overview of the Classical Linear Regression Model
  • Dynamic Models
  • Non-Stationarity and Unit Root Problem
  • Univariate Time Series Modelling
  • Cointegration
  • Multivariate Time Series Modelling

Module Skills

Skills Type Skills details
Application of Number The module involves estimation of various dynamic time-series models and as such requires students to be able to estimate and interpret results of various regression models. In addition, students will be able to carry out advanced diagnostic checks on models. They also will be able to test various hypotheses using advanced statistical techniques.
Communication Discussion-based lectures and seminars facilitate independent and critical thinking skills about key issues in econometrics. Independent work on assessed coursework helps to develop analytical skills as well as writing skills which will be of great use when carrying out various empirical studies.
Improving own Learning and Performance Students will improve their learning by undertaking directed but independent study and work. Time management will be crucial in preparation for the assessments.
Information Technology Students will be working on a dedicated econometrics package called Microfit. Students are required to use electronic databases and statistical packages in their courseworks. The use of electronic journals is also highly relevant for the successful preparation of their coursework.
Personal Development and Career planning The module provides content which may prove highly valuable for many students in their future career. Ability to conduct empirical studies, as well as research skills developed in connection with the preparation of assessed individual coursework, contribute to transferable skills.
Problem solving By facilitating creative thinking approaches to problem solving, the module enables students to critically evaluate potentiol solutions to complex and challenging problems in applied economics and empirical finance.
Research skills By introducing variety of advanced statistical techniques and quantitative methods, the module enables students to investigate empirically various relationships among economic and financial variables. The module also introduces students to a range of empirical research methods, which will facilitate development of appropriate research skills necessary to produce high quality analytical and empirical research studies.
Subject Specific Skills Students develop advanced analytical and research skills necessary to analyse various contemporary issues in economics, finance and other related subject areas.
Team work Although team work ethics are encouraged in seminar discussions, computer practicals, and preparing individual essays, there is no specific assessment requirement involving team work.

Reading List

Recommended Text
Brooks, Chris (2008.) Introductory econometrics for finance /Chris Brooks. 2nd ed. Cambridge University Press Primo search Enders, Walter (c2004.) Applied econometric time series /Walter Enders. 2nd ed. J. Wiley Primo search Gujarati, Damodar N. (2003.) Basic econometrics /Damodar N. Gujarati. 4th ed. McGraw-Hill Primo search Verbeek, Marno. (c2008.) A guide to modern econometrics /Marno Verbeek. 3rd ed. John Wiley & Sons Primo search


This module is at CQFW Level 6