Subject details

  • Topics
    • LINEAR REGRESSION
    • INTERVAL ESTIMATION AND HYPOTHESIS TESTING
    • PREDICTION, GOODNESS OF FIT AND MODELING ISSUES
    • THE MULTIPLE REGRESSION MODEL
    • FURTHER INFERENCE IN THE MULTIPLE REGRESSION MODEL
    • NONLINEAR RELATIONSHIPS
    • HETEROSKEDASTICITY
    • DYNAMIC MODELS, AUTOCORRELATION AND FORECASTING
    • NON-STATIONARY TIME SERIES DATA AND COINTEGRATION
    • QUALITATIVE AND LIMITED DEPENDENT VARIABLE MODELS

Students who successfully complete this subject will be able to:

  1. Demonstrate an understanding of important econometric methods and interpret estimation results
  2. Analyse the concepts of model specification and diagnostic testing procedure in time series and cross sectional econometrics
  3. Solve problems using econometric computer software and commercial databases
  4. Work in groups to solve econometric problems and clearly communicate their results and interpretations.
  • Assignment 1 - Individual (25-40%) (0%)
  • Assignment 2 - Group (10-25%) (0%)
  • Assignment 3 - Group (10-15%) (0%)
  • Assignment 4 - Individual (40-55%) (0%)

Textbooks are subject to change within the academic year. Students are advised to purchase their books no earlier than one to two months before the start of a subject

Entry Requirements

You must have successfully completed the following subject(s) before starting this subject:

Special requirements

No special requirements

This subject is designed so that students learn fundamental techniques of data analysis, basic econometric methods and learn to use data to solve real-world problems by estimating relevant parameters (such as elasticities, marginal values etc). Students acquire expertise in applying data analysis and econometric methods, including regression analysis and its extensions, to various types of data. Students also learn how to use econometrics to test theory, analyse economic and business behaviour, and assist in policy formation. The subject is application orientated and practical work is performed using Windows-based statistical software.

Please note: assessment values are indicative only, details will be advised at the start of the subject.

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