NBS8331 : Introductory Econometrics
NBS8331 : Introductory Econometrics
- Offered for Year: 2024/25
- Module Leader(s): Dr Bahadir Dursun
- Owning School: Newcastle University Business School
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
Semester 1 Credit Value: | 10 |
ECTS Credits: | 5.0 |
European Credit Transfer System | |
Pre-requisite
Modules you must have done previously to study this module
Pre Requisite Comment
None
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
None
Aims
The module seeks to:
- explain how econometrics have been used and can be used to test theories in economics and finance literature
- provide a comprehensive set of fundamental technical skills necessary to pursue empirical research in economics and finance
- offer the opportunity to develop some key quantitative skills that are highly valued in the private sector
The module covers essential material from probability theory, data description, hypothesis testing, and regression analysis with a particular focus on the analysis of cross-sectional data.
Outline Of Syllabus
1. Simple Regression Model: population versus sample regression function, the method of Ordinary Least Squares (OLS), assumptions of the classical linear regression model, obtaining and interpreting the OLS estimates, statistical properties of estimators, measures of fit
2. Classical Normal Linear Regression Model: hypothesis testing and confidence interval estimation.
3. Extensions of the linear regression model: regression through the origin, units of measurement, standardization, logarithmic and semi-logarithmic models.
4. Multiple Regression Model: restricted least squares, tests for multiple linear restrictions.
5. Dummy Variable Regression Models: describing qualitative information, qualitative regressors, analysis of variance (ANOVA) models, regression with a mixture of quantitative and qualitative regressors (ANCOVA models).
6. Relaxing the assumptions of the classical model – multicollinearity, non-normality, heteroskedasticity, and serial correlation: consequences, detection, and robust inferences in their presence.
Learning Outcomes
Intended Knowledge Outcomes
By the end of the module students should:
- have a critical knowledge and understanding of the principles and methods of modern econometrics
- have set up the foundations for critically analysing the empirical economics and finance literature and informing their own practice
- be able to conduct certain types of empirical analyses of their own in support of research
Intended Skill Outcomes
By the end of the module students should:
- have developed the capacity to apply modern econometric methods and interpret the results of econometric software at an essential working level
- be able to use several econometric tools to conduct in-depth types of their own empirical investigations
- have developed problem solving skills and have become familiar with the use of econometric software
Teaching Methods
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Scheduled Learning And Teaching Activities | Lecture | 11 | 1:00 | 11:00 | pip |
Guided Independent Study | Assessment preparation and completion | 1 | 30:00 | 30:00 | N/A |
Guided Independent Study | Directed research and reading | 1 | 33:00 | 33:00 | Readings from the books |
Scheduled Learning And Teaching Activities | Small group teaching | 3 | 1:00 | 3:00 | pip: Small group teaching (seminars) |
Scheduled Learning And Teaching Activities | Workshops | 4 | 1:00 | 4:00 | PiP - Computing Cluster with STATA software |
Guided Independent Study | Independent study | 1 | 19:00 | 19:00 | N/A |
Total | 100:00 |
Teaching Rationale And Relationship
-Lectures provide the fundamental technical structure of the methods introduced and an overview of the essential empirical economic and financial modelling methods
- Seminars provide an opportunity to enhance both theoretical and practical (computer-based) aspects of modelling
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
Description | Length | Semester | When Set | Percentage | Comment |
---|---|---|---|---|---|
Written Examination | 90 | 1 | A | 100 | unseen exam |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
Description | Semester | When Set | Comment |
---|---|---|---|
Prob solv exercises | 1 | M | Group feedback on problem-based exercises in seminars and PC labs |
Prob solv exercises | 1 | M | Seminar questions provided |
Prob solv exercises | 1 | M | Weekly homework problem sets |
Assessment Rationale And Relationship
The 90 mins examination is an appropriate way to assess the theoretical understanding and problem solving skills under the time constraint as required in industry.
The alternative if there is a lockdown is a PC examination that will meet the same goals.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- NBS8331's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- NBS8331's past Exam Papers
General Notes
N/A
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Disclaimer
The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.