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Module ASB-3317:

Module Facts

Run by Bangor Business School

20 Credits or 10 ECTS Credits

Semester 1

Organiser: Dr Chrysovalantis Vasilakis

Overall aims and purpose

The course introduces students to regression analysis, the pitfalls that empirical researchers confront when using these tools, and the methods they use to overcome them. Throughout there is a strong focus on trying to establish cause and effect, rather than just associations.

Course content

The course will cover the linear regression model (LRM), ordinary least squares, goodness of fit and the explanatory power of a regression model, hypothesis testing, model diagnostics, Heteroskedasticity, Multicollinearity, Dummy Variables, Autocorrelation, measurement error, simultaneity bias, endogeneity, Instrumental variables, Maximum Likelihood Estimation, Panel data (Static and Dynamic Models).

Assessment Criteria


D- to D+ (40-49%): No major omissions or inaccuracies in the deployment of information/skills. Some grasp of theoretical/conceptual/practical elements. Integration of theory/practice/information present intermittently in pursuit of the assessed work's objectives.


A- to A+ (70%+): Outstanding Performance. The relevant information accurately deployed. Excellent grasp of theoretical/conceptual/practice elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Strong evidence of the use of creative and reflective skills.


B- to B+ (60-69%): Very good performance Most of the relevant information accurately deployed. Good grasp of theoretical/conceptual/practical elements. Good integration of theory/practice/information in pursuit of the assessed work's objectives. Evidence of the use of creative and reflective skills.

C- to C+

C- to C+ (50-59%): Much of the relevant information and skills mostly accurately deployed. Adequate grasp of theoretical/conceptual/practical elements. Fair integration of theory/practice/information in the pursuit of the assessed work's objectives. Some evidence of the use of creative and reflective skills.

Learning outcomes

  1. Demonstrate team work skills in analysing a contemporary econometric issue.

  2. Collect and critically evaluate data from primary and secondary resources.

  3. Appropriately apply econometric techniques in the assessment of financial and banking issues.

  4. Demonstrate a thorough awareness of theoretical and practical aspects of econometrics.

  5. Demonstrate a critical awareness of the merits and pitfalls of the implicit assumptions and the limitations underlying empirical models.

  6. Demonstrate the ability to assess and interpret surveys, reports and academic literature that apply advanced econometrics.

Assessment Methods

Type Name Description Weight

An assignment provided to students such that to collect, manipulate data and apply the econometric techniques and interpret their results.

EXAM Exam Semester 1 - 2.5hrs

A 2,5 hour exam with three sections. Section A multiple choice questions. Section B and C have typically three equally weighted questions from which two need to be answered on each of these sections. A pocket calculator is essential and a formula sheet is given.


Teaching and Learning Strategy


Lectures: 3 hours of lectures each week (10 weeks x3 hours).

Practical classes and workshops

Computer workshops: 1 hour each week.

Private study

Review and reflect upon the course material.


Transferable skills

  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Teamwork - Able to constructively cooperate with others on a common task, and/or be part of a day-to-day working team
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • Abstraction. From the study of economic principles and models, students see how one can abstract the essential features of complex systems and provide a useable framework for evaluation and assessment of the effects of policy or other exogenous events. Through this, the typical student will acquire proficiency in how to simplify while still retaining relevance. This is an approach that they can then apply in other contexts, thereby becoming more effective problem-solvers and decision-makers.
  • Problem solving and critical analysis: analysing facts and circumstances to determine the cause of a problem and identifying and selecting appropriate solutions.
  • Research: the ability to analyse and evaluate a range of business data, sources of information and appropriate methodologies, which includes the need for strong digital literacy, and to use that research for evidence-based decision-making.
  • Numeracy: the use of quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.


Talis Reading list

Reading list

Stock and Watson Introduction to Econometrics: International Edition. C.Dougherty. Introductory to Econometrics

Pre- and Co-requisite Modules

Courses including this module

Compulsory in courses:

Optional in courses: