Module ASB-3317:
Econometrics

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 include the linear regression model, ordinary least squares, goodness of fit and the explanatory power of a regression model, endogeneity, Instrumental variables, and regression analysis using panel data.

Assessment Criteria

threshold

Satisfactory standard: 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.

excellent

Excellent standard: A- to A* (70-100%). An outstanding performance, exceptionally able. 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.

good

High Standard: 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%). Good performance Some relevant information accurately deployed. General grasp of theoretical/conceptual/practical elements. Satisfactory integration of theory/practice/information in pursuit of the assessed work's objectives. Minor evidence of the use of creative and reflective skills.

Learning outcomes

  1. Demonstrate a critical awareness of the implicit assumptions and the limitations underlying empirical models.

  2. Understand and interpret surveys, reports and academic literature that contain a basic econometrics component.

  3. Demonstrate a solid theoretical and practical grounding in econometrics.

Assessment Methods

Type Name Description Weight
Assignment 40
Exam S1 2.5hrs 60

Teaching and Learning Strategy

Hours
Lecture

Lectures: 3 hours of lectures each week.

30
Practical classes and workshops

Computer workshops: 1 hour each week.

10
Private study

Review and reflect upon the course material.

160

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.

Resources

Pre- and Co-requisite Modules

Pre-requisite of:

Courses including this module

Compulsory in courses:

Optional in courses: