Introduction to Econometrics
| Module title | Introduction to Econometrics |
|---|---|
| Module code | BEE1023 |
| Academic year | 2019/0 |
| Credits | 15 |
| Module staff | Dr Eva Poen (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 11 |
| Number students taking module (anticipated) | 300 |
|---|
Module description
This module introduces students to the theory and application of econometrics, building on the statistical methods learned in BEE1022 Introduction to Statistics.
Additional Information:
Employability
The module introduces methods of empirical analysis which are frequently employed in academia and businesses across many disciplines and industries.
Research in Teaching
Students will study and replicate examples from various empirical research projects in economics.
Module aims - intentions of the module
This module aims to familiarise students with bivariate and multivariate linear regression analysis. The contents of this module form the basis for all econometrics teaching in the undergraduate economics programmes.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. select, fit and interpret linear regression models in the context of economic theory
- 2. recognise, and perform tests for, the common problems that arise in econometric analysis.
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 3. acquire an awareness of the role and contribution that elementary econometric methods make in the understanding of models used in the study of economics.
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 4. improve your data analysis skills, your ability to understand certain technical materials and your ability to write concisely about numerical evidence.
Syllabus plan
- The Nature of Econometrics
- The Simple Regression Model
- Multiple Regression Analysis: Estimation
- Multiple Regression Analysis: Hypothesis Testing and Confidence Intervals
- Multiple Regression Analysis: Categorical variables and further issues
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 32 | 118 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Contact Hours | 22 | Lectures |
| Contact Hours | 10 | Tutorials |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Weekly tutorial problem sets | Weeks 2-11 | 1-4 | Verbal |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 0 | 100 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| 5 online quizzes | 10 | approx. 30 minutes each | 1-4 | Online assessment |
| Written Examination | 90 | 2 hours | 1-4 | Online 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 |
|---|---|---|---|
| Online quizzes and exam | Written examination (100%) 2 hours | 1-4 | Aug/Sep |
Indicative learning resources - Basic reading
Basic reading:
-
Wooldridge, J.M. (2015), Introductory Econometrics, 6th edition, CENGAGE Learning (main textbook).
- D.N. Gujarati and D.C. Porter (2009), Basic Econometrics, McGraw-Hill.
- G.S. Maddala and K. Lahiri (2009), Introduction to Econometrics, John Wiley & Sons Ltd.
| Credit value | 15 |
|---|---|
| Module ECTS | 7.5 |
| Module co-requisites | BEE1022 |
| NQF level (module) | 6 |
| Available as distance learning? | No |
| Origin date | 01/09/2006 |
| Last revision date | 20/02/2019 |