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Quantitative Methods II

Course Code:
15PECC045

This module builds on the basic foundations provided by QMI, focusing principally on time series econometrics, although simultaneous equation models are also discussed. The lectures consist of an introduction to the econometric methods and the coursework is strongly orientated towards the use of econometric methods in the estimation and testing of economic relationships. Data from developing countries are used where possible. The use of formal arguments is kept to a minimum and students are not normally required to prove theorems.

This module enables students to gain practical experience, and aims to create competence in critically evaluating research results, and carrying out good quality empirical work.

Topics covered include: 

  • Introduction to time-series data, 
    • autocorrelation, 
    • ARCH processes, 
    • distributed lag and autoregressive models,
  • Stationarity and nonstationarity, 
    • unit root tests, 
    • spurious regression and cointegration,
  • Simultaneous equation models, 
    • identification, 
    • applications. 
    • Panel Data Models.

Objectives and learning outcomes of the course

On successful completion of the course, you should be able to;

  • explain the nature of economic time series
  • demonstrate understanding of disturbance processes and autocorrelation: its causes, consequences, tests of it and how to make progress in its presence
  • explain the nature of finite and infinite distributed lag models
  • demonstrate understanding of autoregressive models, the partial adjustment and adaptive expectations hypotheses and the Koyck transformation
  • explain and use tests of causality and Ramsey's RESET
  • use information criteria
  • explain stationary and nonstationary time series, including the distinction between stochastic and deterministic nonstationarity
  • explain and implement tests of the order of integration of time series
  • discuss what is meant by 'spurious regression' and be able to identify it
  • demonstrate understanding of cointegration: how to test for it and its relationship with spurious regression
  • explain and interpret error-correction models and show their relationship to autoregressive distributed lag models
  • use error-correction models to model relationships involving cointegrated time series
  • demonstrate understanding of the nature of the identification problem and use the rank and order conditions for identification
  • explain and use OLS, indirect least squares (ILS) and two-stage least squares (2SLS) in simultaneous systems
  • demonstrate understanding of panel data models, panel unit root tests and panel cointegration
  • use the course software to implement the econometric methods discussed in the course
  • exercise judgement in the face of apparently conflicting evidence when carrying out empirical work

Method of assessment

Assessment weighting: Exam 70% / Coursework 30% (computer based). Coursework not resubmittable.

Required reading

Background reading:
  • Asteriou, D and S G Hall (2007) Applied Econometrics A Modern Approach, Revised edition, Palgrave Macmillan, ISBN 978-0-230-50640-4
  • Brooks, C (2008) Introductory Econometrics for Finance, 2nd edition, Cambridge University Press.
  • Gujarati D N and Porter D C (2009) Basic Econometrics, 5th edition, McGraw-Hill, International Edition. ISBN 978-007-127652-2