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Econometric Theory II

Module description

This module builds on Econometric Theory I and further develops your knowledge and understanding of econometric and methodological research tools and the application of various econometric methods and techniques to real life problems.
Additional Information:

The methods covered in this module, such as those used to forecast inflation and GDP, are applicable across countries.
Resources for this module are available on the ELE (Exeter Learning Environment).
Students gain an understanding of the statistical techniques used to study topics such unemployment and forecasting inflation and economic growth which are all necessary skill for working in central banks. They also develop their numerical and problem-solving skills in learning these mathematical techniques.

Full module specification

Module title:Econometric Theory II
Module code:BEEM142
Module level:M
Academic year:2023/4
Module lecturers:
  • Dr Namhyun Kim - Convenor
Module credit:15
ECTS value:



BEEM139. Only available to students on the MRes Economics and MRES Economics (PHD Pathway) programmes.



Duration of module: Duration (weeks) - term 2:


Module aims

This module aims at providing the students with the necessary econometric and methodological research tools to equip them for carrying out empirical research projects as well as understand the contents of other modules.
The module is dedicated to the application of various econometric methods and techniques to real life problems.

ILO: Module-specific skills

  • 1. apply modern econometric techniques in the analysis of economic data

ILO: Discipline-specific skills

  • 2. formulate hypotheses of interest, derive the necessary tools to test this hypothesis and interpret the results
  • 3. show a specialised knowledge of applied aspects of econometrics that will enable him/her to carry out applied research or direct them towards an academic career

ILO: Personal and key skills

  • 4. have technical expertise in computing software, particularly econometric software, to tackle empirical problems
  • 5. demonstrate confidence in identifying, tackling and solving research problems

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled Learning and Teaching22Lectures
Scheduled Learning and Teaching10Tutorials
Independent Study118Independent study

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Weekly exercises5-15 questions per week1-5Oral/Written

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Assignment 202000 words1-5Oral/Written
Final Exam802 hours1-5Oral/Written

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Assignment Assignment (20%)1-5August
Final exam Final exam (80%)1-5August

Syllabus plan

• Topics:

• Topics in estimation techniques:

       1. Maximum Likelihood Estimation

       2. Generalized Method of Moments

• Topics in Microeconometrics:

     1. Binary choice Models and Limited Dependent Variables

       2. Panel Data Models

  • Topics in Time Series:

1. Univariate Time Series Models

2. Multivariate Time Series Models

3. Unit Roots and Cointegration


Indicative learning resources - Basic reading

Cameron, C. and P. Trivedi (2005), Microeconometrics: Methods and Applications, Cambridge University Press.
Greene, W. (2008), Econometric Analysis, New Jersey: Prentice Hall, 6th Edition. (main textbook.)
Hamilton, J. D. (1994), Time Series Analysis, Princeton University Press.

Module has an active ELE page?


Origin date


Last revision date