AF5039 - Econometrics

What will I learn on this module?

Building on mathematical and statistical prior knowledge, the module introduces students to the theory and application of econometrics. You will learn classical econometric models such as simple and multiple regression analysis, assumptions and properties of statistical estimators, and the reasoning for violating these assumptions in specific cases. The module covers modelling and statistical inference techniques for single and multi-equation systems, and the use of these techniques with regard to data prediction, model evaluation and forecasting.

Outline Syllabus:
1. Review of Basic Statistics;
2. Simple Regression Analysis;
3. Properties of Regression Coefficients;
4. Inference Testing;
5. Multiple Regression Analysis;
6. Specification of Regression Variables;
7. Violations and Solutions of Classical Linear Assumptions;
8. Time Series Analysis;
9. Panel Data Models;
10. Forecasting Techniques.

You will develop skills that can be applied more widely, such as problem solving and data analysis skills, through writing of workshop questions and assessments; you will gain analytical academic writing skills relevant to the world of economics and finance.

How will I learn on this module?

You will learn on this module through lectures (12 hours), interactive workshops (24 hours) and tutor led (82 hours) and independent learning (82 hours). You will learn concepts and models in an applied way for all taught components in this module, for this you will work in IT labs producing results involving the analysis of real-world data. You will study and replicate examples from published empirical research projects in economics and finance. The emphasis will be on high levels of engagement in understanding theory, collecting and analysing real world data and interpreting results. Independent learning will use both theory in economics and application using statistical software. Directed learning will centre upon a range of activities including pre-reading, preparation for interactive activities, practice in IT lab, and use of the discussion board to learn and share knowledge. Independent learning will centre upon the students identifying and pursuing areas of interest in relation to econometrics models and by providing deeper/broader knowledge and understanding of the subject through a range of learning activities that will include extended reading, reflection, research and statistical calculations.

How will I be supported academically on this module?

You will be supported by a teaching and learning plan (TLP) that outlines the pattern and content of the formal sessions, together with tutor-directed study and independent reading. Support will be provided to you by a module lead and seminar and workshop tutors who will all provide support on a formative basis during each interactive session. Your lectures will be recorded and uploaded to the e-learning portal which you will be able to access to consolidate your knowledge and develop understanding. Your module is supported by an e-learning portal that houses lecture materials, seminar and workshop exercises and data files for use in workshop sessions. You will be provided with a wide-ranging electronic reading list that comprises of various academic reports, conference papers, video links and journal articles that will introduce you to the theory and application of the techniques introduced in the module. Your module assessment consists of empirically motivated work in economics and finance and you will be encouraged to remain an active participant in the learning process throughout the semester. Econometric software functions related to various models will be taught alongside module content to support your learning.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at:
(Reading List service online guide for academic staff this containing contact details for the Reading List team –

What will I be expected to achieve?

Knowledge & Understanding (KU):

• To understand and critique important econometric theories (MLO1)

• To formulate, analyse and test various econometric/ financial models. (MLO2).

Intellectual / Professional skills & abilities (IPSA):

• To use econometric software for the statistical analysis of data (MLO3).
• To appreciate the relevance of theory for empirical applications (MLO4).

Personal Values Attributes (PVA):

• You will develop a robust analytical skillset that will enable you to analyse and interpret a wide range of issues within and outside the disciplines of economics and finance. (MLO5).

How will I be assessed?

Formative assessment:
Formative assessment will take place through assignment discussion and reflection, discussion board activity on the e-learning platform, case study activity, and theory/practice related discussions. You will receive formative feedback throughout the module, particularly in relation to workshop and seminar tasks. Students should, however, be aware that formative feedback can, and will, occur in any communication with the academic tutor.

Summative assessment:
This is made up of two elements:
• 2 hour IT lab-based exam (40%)
• Assignment requiring 2,000 words (60%).
Together the two form of assessment will address MLO1- MLO4.





Module abstract

This module introduces the econometric theories and techniques that are important for both practitioners and researchers. It provides you with essential econometric skills and knowledge to analyse and interpret real-world data, and stimulates you to acquire and develop a theoretical and practical understanding of econometrics. The module’s content and structure provide a comprehensive overview of the econometric methods and analytical tools needed for the study of economics and finance, such as linear and multiple regressions, panel data and time series analysis, and forecasting techniques. Practical workshop sessions require the use of econometric software packages. At the end of this module you’ll be able to apply appropriate econometric techniques to a wide range of data, and to discuss and explain results concisely and consistently. By acquiring these critical skills, you’ll significantly enhance your profile in terms of employability and entrepreneurial opportunities.

Course info

UCAS Code L101

Credits 20

Level of Study Undergraduate

Mode of Study 3 years Full Time or 4 years with a placement (sandwich)/study abroad

Department Newcastle Business School

Location City Campus, Northumbria University

City Newcastle

Start September 2024 or September 2025

Fee Information

Module Information

All information is accurate at the time of sharing. 

Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.  

Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.


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