Unit information: Business and Economic Forecasting in 2026/27

Please note: Programme and unit information may change as the relevant academic field develops. We may also make changes to the structure of programmes and assessments to improve the student experience.

Unit name Business and Economic Forecasting
Unit code ECONM0030
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Crespo
Open unit status Not open
Units you must take before you take this one (pre-requisite units)

None

Units you must take alongside this one (co-requisite units)

None.

Units you may not take alongside this one

None

School/department School of Economics
Faculty Faculty of Social Sciences and Law

Unit Information

Why is this unit important?

Forecasting is an integral part of the decision-making activities in business, finance, economics, government, and many other fields. In recent years there have been extensive developments in the methods used in forecasting. In this course we look at different approaches and techniques that help decision makers make the best possible judgments about future events. The course will normally cover forecasting with structural regression models and univariate and multivariate time series models.

How does this unit fit into your programme of study?

The unit will discuss data acquisition as well as data handling. The course will enable students to be better prepared for dissertations, which might require the analysis of time series data. The techniques covered are widely used in Economics, Finance and Management, and a knowledge of them will also enable students to be better able to apply them in their future work. Students selecting this unit should have basic/introductory knowledge in statistics and/or econometrics.

Your learning on this unit

An overview of content

The aim of this unit is to teach basic time series methods in the context of real-world empirical problems. The first part of the course concentrates on univariate time series models which are required for the study of more advanced time series techniques that are taught in the second part of the course. Although several key theoretical concepts are introduced, the emphasis is on applying these econometric techniques to real-world forecasting problems in economics, finance and management.

How will students, personally, be different because of the unit?

The students will get an understanding of basic time series techniques, which are commonly used in economics and finance. The unit will enable students to use these techniques in their dissertation and to have a general understanding of published forecasting results.

Learning Outcomes

At the end of the course a successful student will be able to:

  1. interpret and analyse fundamental ideas in time series such as autocorrelation, stationarity, Box-Jenkins methodology, unit root tests and conditional heteroskedasticity;
  2. estimate time series models and use them to make forecasts;
  3. to be proficient in the application of different forecasting methodologies in order to use them in their future academic or professional career;
  4. apply the relevant statistical/econometrics computer package to estimate forecasting models in the context of real-world economic problems.

How you will learn

Teaching will be delivered through a combination of synchronous and asynchronous sessions such as face-to face for large and small groups, online learning resources and interactive learning activities. Some classes will be held in computer labs in which students will be given data sets and structured problem-solving exercises to gain “hands-on” practice in using the relevant statistical package: students will complete these exercises in their own time.

How you will be assessed

Tasks which help you learn and prepare you for summative tasks (formative):

The students will be asked to read an academic article and write a 1000-word essay based on their reading. This assignment is designed to examine the student’s ability to work with the concepts and techniques introduced in the course (ILO 1). In addition, five computer exercises will be covered during the term, which will enable students to apply the time series techniques to answer real-world empirical questions (ILOs 2 & 3) and to develop expertise in using the relevant statistical/econometrics computer package (ILO 4).

Tasks which count towards your unit mark (summative):

Coursework (100%) in two parts, consisting of a 1000-word essay, and questions relating to a dataset to estimate several models. Assesses ILOs 1-4

When assessment does not go to plan

When a student fails the unit and is eligible to resubmit, failed components will be reassessed on a like-for-like basis.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. ECONM0030).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the University Workload statement relating to this unit for more information.

Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates within the Regulations and Code of Practice for Taught Programmes.