BSc International Business, Finance and Economics with Industrial/Professional Experience / Course details

Year of entry: 2020

Course unit details:
Econometrics

Unit code ECON20110
Credit rating 20
Unit level Level 2
Teaching period(s) Full year
Offered by Economics
Available as a free choice unit? Yes

Overview

To provide students with an understanding of the quantitative methods and tools that economists use and how they can be appropriately applied and interpreted. These methods and tools are used in practical and academic settings to test economic theories and measure magnitudes that are relevant for economic policy analysis and other decisions. These methods are a key element of the professional training an economist; they will provide a foundation for subsequent study of applied and quantitative topics and are useful in many careers in economics. The course aims to equip students with a number of core competencies including: (i) an awareness of the main empirical approach to economics, (ii) experience in the analysis and use of data and software packages as tools of quantitative and statistical analysis to answer topical economic questions, (iii) an understanding of the nature of uncertainty and methods of making inference in the presence of uncertainty.

The objectives of this course are that students will be able to:

•      understand the main techniques of quantitative economics and econometrics, including their strengths and limitations, at a level appropriate for an economics graduate

•      understand how these techniques can be applied to test economic theories and measure economic magnitudes, and have some knowledge of methods and results in selected areas of the applied economics literature

•      have some practical experience of the application of econometric methods based on practical exercises

•      have acquired the necessary skills and knowledge to be able to critically appraise work in the area of applied economics.

•      have a good intuitive and theoretical grasp of the dangers, pitfalls and problems encountered in doing applied modelling.

•      have the necessary background material so that they are able to go on to study more advanced and technical material in the area of econometrics.

•         use the R software package to obtain basic descriptive statistics using real world data and perform introductory econometric analysis.

Pre/co-requisites

Unit title Unit code Requirement type Description
Advanced Mathematics ECON10071 Pre-Requisite Compulsory
Advanced Statistics ECON10072 Pre-Requisite Compulsory
Pre-Requisites: ECON10071 & ECON10072

ECON10071 Adv Maths and ECON10072 Adv Stats

 

Aims

The aims of this course are:

  1. To provide students with an understanding of the quantitative methods and tools that economists use and how they can be appropriately applied and interpreted. These methods and tools are used in practical and academic settings to test economic theories and measure magnitudes that are relevant for economic policy analysis and other decisions. These methods are a key element of the professional training an economist; they will provide a foundation for subsequent study of applied and quantitative topics and are useful in many careers in economics.
  2. The course aims to equip students with a number of core competencies including: (i) an awareness of the main empirical approach to economics, (ii) experience in the analysis and use of data and software packages as tools of quantitative and statistical analysis to answer topical economic questions, (iii) an understanding of the nature of uncertainty and methods of making inference in the presence of uncertainty.


 

Learning outcomes

 The objectives of this course are that students will be able to:

  • understand the main techniques of quantitative economics and econometrics, including their strengths and limitations, at a level appropriate for an economics graduate
  • understand how these techniques can be applied to test economic theories and measure economic magnitudes, and have some knowledge of methods and results in selected areas of the applied economics literature
  • have some practical experience of the application of econometric methods based on practical exercises
  • have acquired the necessary skills and knowledge to be able to critically appraise work in the area of applied economics.
  • have a good intuitive and theoretical grasp of the dangers, pitfalls and problems encountered in doing applied modelling.
  • have the necessary background material so that they are able to go on to study more advanced and technical material in the area of econometrics.
  • use the R software package to obtain basic descriptive statistics using real world data and perform introductory econometric analysis.
     

Syllabus

This course will introduce students to the theory and practice of econometric analysis. Each week part of the lectures will focus on the theoretical underpinnings of econometric analysis, and the remaining part of the lectures and associated example and computer sessions will focus on the practice and application of these ideas, with the aim of providing students with practical and intuitive real world applications of the theory.

  • simple linear regression models
  • multiple regression analysis
  • inference
  • functional form and dummy variables
  • parameter properties
  • asymptotic inference
  • omitted variable bias
  • instrumental variables
  • introduction to panel data
  • time-series data and time-series modelling
  • heteroscedasticity
  • autocorrelation
  • structural breaks
  • binary dependent variable models
  • maximum likelihood
  • Bayesian inference

Teaching and learning methods

Lectures and exercise classes.

Employability skills

Analytical skills
Ability to analyse and interpret quantitative data.
Other
A fluency in using IT/computers for statistical research (programming skills).

Assessment methods

 5% Sem 1 Online quizzes x4

5% Sem 2 Online quizzes x4

35% Sem 1 Exam

35% Sem 2 Exam

10% Sem 1 Mid term

10% Sem 2 Mid term


 

Feedback methods

  • Weekly online quizzes
  • Tutorial feedback.
  • PASS groups.
  • Office hours.
  • Revision sessions.
  • Discussion boards.
     

Study hours

Scheduled activity hours
Assessment written exam 3
Lectures 32
Tutorials 14
Independent study hours
Independent study 151

Teaching staff

Staff member Role
Ralf Becker Unit coordinator
Rachel Griffith Unit coordinator

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