Statistics and Econometrics

Module description


This module follows on from the first year course BEE1022 Introduction to Statistics. It will equip you with the skills needed to successfully tackle many of the statistical and econometric problems that occur in economics, business and management.

Additional Information:

The whole content of this module is applicable across boundaries and is not specific to any country.

All of the resources for this module are available on the ELE (Exeter Learning Environment).

This module helps students develop data analysis techniques and skills which are essential for working in the government and the private sector.

Full module specification

Module title:Statistics and Econometrics
Module code:BEE2006
Module level:2
Academic year:2015/6
Module lecturers:
  • Dr Ana Fernandes - Convenor
  • Dr Cecilia Chen - Lecturer
Module credit:30
ECTS value:



BEE1024 and BEE1022 or BEE1025



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


Duration (weeks) - term 2:


Module aims

The aim of this module is to develop the knowledge and skills taught in BEE1022 Introduction to Statistics (or BEE1025 - Statistics for Business and Management)  and focuses on the analysis of economic data. Its aim is to equip students to tackle some statistical and many econometric problems in economics.

ILO: Module-specific skills

  • 1. demonstrate competent knowledge of a variety of statistical techniques (described in the syllabus plan) that can be used to estimate models, assess their correct specification and make inferences under different assumptions in the context of problems arising in the field of econometrics.
  • 2. solve satisfactorily a variety of problems in econometrics
  • 3. interpret correctly the estimated results and the statistical tests performed
  • 4. the ability to use competently the software Time Series Modelling or any other statistical software to compute empirical results

ILO: Discipline-specific skills

  • 5. explain satisfactorily the underlying models and techniques in economic research
  • 6. demonstrate good mathematical skills
  • 7. compare adequately econometric models with economic models

ILO: Personal and key skills

  • 8. correctly perform mathematical calculations
  • 9. demonstrate a competent level of logical thinking and analytical reasoning
  • 10. demonstrate good problem solving skills

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
Contact hours46Lectures (2 hours per week)

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Weekly exercises5-15 questions per week1-10Written or verbal feedback

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
Homework105 problem sets (5-15 questions per set)1-10Written or verbal feedback
Assignment (empirical project)15maximum length 3 sides of A41-10Written or verbal feedback
Test in January251 hour1-10Written or verbal feedback
Exam in May401.51-10Written or verbal feedback
Assignment10maximum length 3 sides of A41-10Written or verbal feedback

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

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Homework, Assignment and TestExam 1.5 hours (50%)1-10August
Exam and AssignmentExam 1.5 hours (50%)1-10August

Re-assessment notes

The average is taken across both terms and if the student fails overall they resit for the part(s) they have failed separately. For resits the mark is capped at 40.

Syllabus plan

Term 1

  • A refresher on some topics in Probability and Statistics
  • The Nature of Econometrics and Economic Data
  • The Simple Regression Model
  • Multiple Regression Analysis: Estimation
  • Multiple Regression Analysis: Inference
  • Multiple Regression Analysis: Further Issues
  • Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
  • Heteroskedasticity

Term 2

  • More on Specification and Data Problems
  • Basic Regression Analysis with Time Series Data
  • Further Issues in Using OLS in Time Series
  • Serial Correlation and Heteroskedasticity in Time Series Regressions
  • Pooling Cross Sections across Time: Simple Panel Data Models
  • Advanced Panel Data Models
  • Instrumental Variables Estimation and Two Stage Least Squares
  • Simultaneous Equation Models
  • Binary Response Models

Indicative learning resources - Basic reading

Basic reading:

Main Recommended Book:
Wooldridge, J.M. (2008), Introductory Econometrics, A Modern Approach, 4th Ed., United Kingdom: South-Western, Thomson Learning

Additional Resources:
Gujarati, D. N. (2003), Basic Econometrics, 4th edition, New York: McGraw–Hill.
Stock, J and Watson, M. (2006), Introductory Econometrics, London, Addison-Wesley 

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