Basic Econometrics (ECOM90001)

Graduate courseworkPoints: 12.5On Campus (Parkville)

You’re viewing the 2018 Handbook:
Or view archived Handbooks
You’re currently viewing the 2018 version of this subject

Overview

Availability
Semester 1
FeesLook up fees

This subject examines multiple regression analysis and its use in economics, management, finance, accounting and marketing. Topics will include the properties of estimators, hypothesis testing, specification error, multicollinearity, dummy variables, heteroskedasticity, serial correlation. Empirical assignments undertaken by the student form an integral part of the subject.

Intended learning outcomes

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



  • Apply the classical model of ordinary least squares to data sets drawn from economics, finance, accounting and management using single and multiple regression equations;
  • Test hypotheses concerning the relationship between variables;
  • Explain in detail the consequences of the violation of any one of the classical assumptions;
  • Test for violations of the classical assumptions;
  • Estimate models in the presence of non-classical errors and stochastic explanatory variables;
  • Diagnose model misspecification using the most appropriate tests, and where appropriate identify the appropriate remedial actions;
  • Use computer software to perform simple data descriptions and to graph relationships between variables, to estimate econometric models using OLS and Instrumental Variables, and to estimate simple dynamic models;
  • Apply econometric methods to real world data and perform diagnostic testing to ensure the model is adequately specified.

Generic skills

On successful completion of this subject, students should have improved the following generic skills:

  • Evaluation of ideas, views and evidence
  • Synthesis of ideas, views and evidence
  • Critical thinking
  • Application of theory to economic policy and business decision making
  • Accessing economic and other information
  • Summary and interpretation of information
  • Using computer programs
  • Statistical reasoning
  • Problem solving skills
  • Collaborative learning and teamwork
  • Written communication
  • Oral communication

Last updated: 3 November 2022