Econometrics and Forecasting Course Descriptor

Course Overview

In Economics, forecasting is perhaps one of the most misunderstood skills. It is not central to what most economists believe they do; yet the general public and mass media tend to assume it is central to the work of an economist. In this course, students are encouraged to develop their skills in informed forecasting that respects the conventions of econometric research, while also being aware of the limitations of this toolkit for predicting changes in the real economy.

This course focuses particularly on developing students’ skills in time series analysis and panel data analysis. We use various techniques to characterise and forecast the time-paths of stochastic processes and attempt to apply them empirically. Students may choose their own examples on parts of the assessment, including local or global datasets.

The course develops and tests students’ understanding of the relevant models (such as ARCH/GARCH and random walk models), as well as problem-solving using econometric conventions, including but not limited to relevant diagnostic tests.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Employability Skills

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students in their studies.
The scheduled teaching and learning activities for this course are:
Lectures/seminars

40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours.

• Version 1:all sessions in the same sized group

OR

• Version 2: most of the sessions in larger groups; some of the sessions in smaller groups

Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups. 

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Dedicated mathematics support will be available to all students during teaching weeks.

Indicative total learning hours for this course: 150

Assessment

Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.

Summative Assessments

Further information about the assessments can be found in the Course Syllabus.

Feedback

Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).

Indicative Reading

Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.

• Woolridge, J. (2009) Introductory Econometrics.
• Greene, W.H. (2017) Econometric Analysis

Any editions will suffice, however the priority will be on lecture slides.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below are used as a general guide and part of the approval/modification process only.

• The AR/MA/ARMA/ARIMA models
• Regression and the diagnostic tests
• Random Walk modelling
• The ARCH and GARCH models