Applied Econometrics

Module description


 The ability to perform and critically discuss applied empirical work is central to an economists’ job in today’s workplace. The volume of economic and financial data is ever increasing, and so are the opportunities to use this data to undertake empirical economic research. Quantitative methods and the software used to apply them have become more and more sophisticated. This module aims to provide training in both the empirical methods and in the application of those methods using a modern statistics software package.

 Additional Information:


 The module contains many examples of research carried out internationally. Students are encouraged to think about applied topics relevant to the UK as well as Europe and overseas. The datasets used for this module come from various sources, many of them international organisations.


 The main aim of this module is to equip students with practical empirical skills and critical thinking which are highly sought after in the workplace.

 Research in Teaching

 As part of the module students will study and replicate example of empirical research.

Full module specification

Module title:Applied Econometrics
Module code:BEE2032
Module level:2
Academic year:2018/9
Module lecturers:
  • Dr Eva Poen - Convenor
Module credit:15
ECTS value:



Introduction to Econometrics BEE1023 and Econometrics BEE2031 (BEE2006)



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


Module aims

The aim of this module is to equip students with good practical skills in the application of quantitative research techniques to research questions from different areas of economics. The module will focus on data skills (organisation and manipulation of data, descriptive and explorative analysis) and applied econometrics (especially models for cross-sectional and panel data which have not been extensively covered in previous modules). Students will learn to apply those techniques using the professional statistics software package Stata.

ILO: Module-specific skills

  • 1. demonstrate ability to understand the important features and properties of economic data, and perform the necessary operations to organise and manipulate the data
  • 2. apply appropriate quantitative techniques based on the research question and features of the data
  • 3. perform independent empirical analysis using the software STATA

ILO: Discipline-specific skills

  • 4. combine knowledge of economic theory with the necessary quantitative and data skills to complete an empirical research task

ILO: Personal and key skills

  • 5. demonstrate analytical and critical thinking
  • 6. demonstrate the ability to use state-of-the-art statistical software

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
Schedule learning and teaching22 hoursLectures
Scheduled leaning and teaching5 hoursTutorials

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
In class discussion/exercisesWeeks 1 to 111-6Verbal/ELE

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
Practical Exam802.5 hours-6Discussion
Homework tasks 20Aprox. 4 pages1-6ELE/Turnitin

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Practical Exam & homework tasksPractical Exam (100%) 2.5 hours1-6August Examination Period

Re-assessment notes

Re-assessment to take place if the average of both assessment components is below 40.

Syllabus plan

Module aims and limitations

  • Introduction to Stata
  • First steps in empirical analysis: descriptive statistics and explorative analysis
  • Organising your work: do-files, logs and programs
  • Applied linear regression, diagnostics and tests
  • Nonlinear regression models
  • Missing data
  • Panel data: methods and applications
  • Introduction to time series data
  • Effective repetition of tasks
  • Programming in Stata

Indicative learning resources - Basic reading

Adkins, L.C. and Hill, R.C. (2011) Using Stata for Principles of Econometrics, 4th edition, John Wiley & Sons.

 Hill, R.C, Griffiths, W.E and Lim, G.C (2011) Principles of Econometrics, 4th edition, John Wiley & Sons.

 Cameron, A.C and Trivedi, P.K. (2010) Microeconometrics using Stata, revised edition, Stata Press.

Module has an active ELE page?


Indicative learning resources - Web based and electronic resources

UK Data Service ( )

Indicative learning resources - Other resources

A Gentle Introduction to Stata by Alan C. Acock

Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter

Interpreting and Visualizing Regression Models Using Stata by Michael N. Mitchell

An Introduction to Stata Programming by Christopher F. Baum

Origin date


Last revision date