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Applied Econometrics for Business

Module description

The ability to perform and critically discuss applied empirical work is central to a business 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 and business research. The quantitative methods, and the software used to apply them, becoming more and more sophisticated, and 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:

Employability: In today’s electronic world, all businesses are collecting data and need employees who can critically analyse the vast amount of data to smartly drive business decisions. This module attempts to bridge the gap between economic theories learnt in other modules and the data-driven world beyond the classroom.

Full module specification

Module title:Applied Econometrics for Business
Module code:BEE3071
Module level:3
Academic year:2023/4
Module lecturers:
  • Dr Pradeep Kumar - Convenor
Module credit:15
ECTS value:



Either BEE1022 or BEE1025 or BEA1012; and BEE2038 and BEE2039

Please note this module cannot be taken by students who have previously studied BEE2025 and BEE2026.

Duration of module: Duration (weeks) - term 1:


Module aims

The aim of this module is to equip you with good practical skills in applied business economics, especially in the application of quantitative research techniques to research questions from different areas of business economics. The module will focus on data skills (organisation and manipulation of data, descriptive and explorative analysis), survey data and applied econometrics (regression models). You will learn to apply those techniques using one of the main statistics software package.

ILO: Module-specific skills

  • 1. demonstrate ability to understand the important features and properties of real-world 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 a statistical software.

ILO: Discipline-specific skills

  • 4. combine knowledge of economic theory with the necessary quantitative and data skills to undertake applied empirical work in business economics.

ILO: Personal and key skills

  • 6. demonstrate analytical and critical thinking;
  • 7. demonstrate the ability to use 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
Scheduled Learning and Teaching Activity22Lectures
Scheduled Learning and Teaching Activity5Tutorials
Guided Independent Study123Reading, research, reflection; preparation for lectures and tutorials; preparation for assessments

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
DataOne term1-6Verbal
Preparatory Exercises for Practical ExamOne term1-6Verbal

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 exam703 hours1-6Written
Homework301 problem set with 10-15 questions1-6Written and verbal

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Practical Exam (70%)Take home assignment (70%)1-6August/September Reassessment Period
Homework (30%)1 problem set with 10-15 questions (30%)1-6August/September Reassessment Period

Syllabus plan

  • Module aims and limitations
  • Introduction to Statistical Software (STATA)
  • First steps in empirical analysis: descriptive statistics and explorative analysis
  • Organising your work
  • Hypothesis Testing
  • Applied linear regression, diagnostics and tests
  • Prediction, Goodness-of-fit and Modelling issues
  • Non-linear regression models
  • Binary choice models
  • Working with surveys

Indicative learning resources - Basic reading

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

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

Module has an active ELE page?


Indicative learning resources - Web based and electronic resources

A Gentle Introduction to Stata by Alan C. Acock

Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter

Cortinhas, C. and Black, K. (2012), Statistics for Business and Management, 1st European Edition, Wiley Data:

UK Data Service ( )

Origin date


Last revision date