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School of Social Sciences

Students outside a lecture theatre at The University of Manchester
BAEcon Economics
Learn how the social sciences can help you to understand today's world.

BAEcon Economics

Year of entry: 2018

Course unit details:
Business Forecasting

Unit code ECON30352
Credit rating 10
Unit level Level 3
Teaching period(s) Semester 2
Offered by Economics
Available as a free choice unit? Yes

Overview

See course Blackboard pages.
 

Pre/co-requisites

Unit title Unit code Requirement type Description
Econometrics ECON20110 Pre-Requisite Compulsory
Econometrics ECON30370 Co-Requisite Compulsory
Econometrics (10cp) ECON20110 Pre-Requisite Compulsory
Pre-requisite OR Co-requisite: ECON20110 or ECON30370 - either passed in previous year or taken concurrently

Or, if students have not taken ECON20110 in their second year, they can take ECON30370 (the same module) alongside this module.

Aims

To examine the theory and application of the basic classical forecasting tools used in management science and economics. To be aware of the open source software R as a resource for modelling.

Learning outcomes

At the end of this course you will be able to:

  1. Identify the presence of trend and seasonality in time series through the use of graphs and statistical hypothesis tests.
  2. Model time series using moving averages, exponential smoothing, and relevant ARIMA processes.
  3. Use these modeling techniques to obtain forecasts.
  4. Evaluate the performance of their own and other people’s forecasts.

Syllabus

  1. Introduction:  measuring forecast accuracy.
  2. Graphs, transformations, tests for randomness: e.g. autocorrelation.
  3. Elementary modelling: simple moving averages, exponential smoothing, diagnostics.
  4. An introduction to ARMA models, stationarity.
  5. Trend:  linear exponential smoothing,  ARIMA models.
  6. Seasonality: seasonal exponential smoothing, seasonal ARIMAs.
  7. Practical modelling: implementation via R, Box/Jenkins ARIMAs.
     

Teaching and learning methods

Lectures and exercise classes.

Employability skills

Analytical skills
Synthesis and analysis of data and information.
Problem solving
Other
Numeracy. Time management.

Assessment methods

Method Weight
Other 10%
Written exam 90%
  • End of Unit Coursework: R assessment (10%).
  • Final Exam: written answers (90%).

Feedback methods

  • One assessment using a question from the previous’ years exam.
  • Online quizzes.
  • Class exercises.
  • Computer lab class exercise (formative for the R coursework).
  • Office hours.

Recommended reading

  • Forecasting: Methods and Applications, (1998) by Makridakis, Wheelwright, Hyndman
  • The online text by Hyndman and Athanasopouulos , Forecasting: Principle and Practice, which is more R focused (http://otexts.com/fpp/)

Study hours

Scheduled activity hours
Assessment written exam 1.5
Lectures 16
Tutorials 7
Independent study hours
Independent study 75.5

Teaching staff

Staff member Role
Simon Peters Unit coordinator

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