Statistics and Econometrics
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.
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|
BEE1024 and BEE1022 or BEE1025
|Duration of module:||
Duration (weeks) - term 1: |
11Duration (weeks) - term 2:
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 Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
|Contact hours||46||Lectures (2 hours per week)|
|Form of assessment||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Weekly exercises||5-15 questions per week||1-10||Written or verbal feedback|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Homework||10||5 problem sets (5-15 questions per set)||1-10||Written or verbal feedback|
|Assignment (empirical project)||15||maximum length 3 sides of A4||1-10||Written or verbal feedback|
|Test in January||25||1 hour||1-10||Written or verbal feedback|
|Exam in May||40||1.5||1-10||Written or verbal feedback|
|Assignment||10||maximum length 3 sides of A4||1-10||Written or verbal feedback|
Details of re-assessment (where required by referral or deferral)
|Original form of assessment||Form of re-assessment||ILOs re-assessed||Timescale for re-assessment|
|Homework, Assignment and Test||Exam 1.5 hours (50%)||1-10||August|
|Exam and Assignment||Exam 1.5 hours (50%)||1-10||August|
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.
- 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
- 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
Main Recommended Book:
Wooldridge, J.M. (2008), Introductory Econometrics, A Modern Approach, 4th Ed., United Kingdom: South-Western, Thomson Learning
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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Last revision date