• University of Exeter Business School
• Module

Econometrics

Module description

Summary:

This module follows on from the first-year course BEE1023 Introduction to Econometrics. It broadens the knowledge of basic econometrics. It will equip you with the skills needed to successfully study econometric problems involving different types of variables and data structure, which are often analyzed in economics, business and management.

Internationalisation

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

Sustainability

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

Employability

This module helps you develop data analysis techniques and skills which are essential for working in the government and the private sector, such as the consulting industry.

Module aims - intentions of the module

The aim of this module is to develop the knowledge and skills taught in BEE1023 - Introduction to Econometrics and focus on applying econometric techniques to solve economic problems, from identifying causal effects of economic policies to quantify the existence of discrimination in the labour market. It will equip students with skills to tackle many econometric problems in economics involving the use of different types of data.  

Intended Learning Outcomes (ILOs)

ILO: Module-specific skills

On successfully completing the module you will be able to...

• 1. Demonstrate competent knowledge of a variety of econometric techniques;
• 2. Interpret correctly economic data and estimates.

ILO: Discipline-specific skills

On successfully completing the module you will be able to...

• 3. Explain satisfactorily the underlying models and techniques in economic research;
• 4. Demonstrate good mathematical and computational skills.

ILO: Personal and key skills

On successfully completing the module you will be able to...

• 5. Demonstrate a competent level of logical thinking and analytical reasoning;
• 6. Demonstrate good problem solving skills.

Syllabus plan

• Population vs. sample
• Law of large numbers and central limit theorem
• Linear prediction vs. linear econometric model
• Decomposition of effects for linear regression models
• Measurement error, omitted variable bias and simultaneity bias
• Instrumental variables and Two Stage Least Squares
• Nonlinear econometric models.

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

Details of learning activities and teaching methods

Formative assessment

Summative assessment (% of credit)

Details of summative assessment

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

Re-assessment notes

Deferral – if you have been deferred for any assessment you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 40%) you will be expected to submit the relevant assessment. The mark given for a re-assessment taken as a result of referral will be capped at 40%

Indicative learning resources - Basic reading

Basic reading: 

• Slides and notes prepared by lecturers and pedagogical articles (e.g. Journal of Economic Perspectives).

Optional reading:

• Stock, J. & Watson, M. (2016). Introduction to econometrics. London: Addison-Wesley.
• Wooldridge, J.M. (2020). Introductory econometrics: A modern approach (7^th ed.). Australia: Cengage. (Older editions can be used)

Key words search

Econometrics, Statistics, Quantitative Methods.