ECO-30043 - Module Specification
Keele Business School
Faculty of Humanities and Social Sciences

Programme/Approved Electives for 2020/21

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

Completion of ECO-20042, Introduction to Econometrics

Barred Combinations

none

Description for 2020/21

The ability to analyse quantitative information and produce and evaluatate forecasts is a highly prized skill in business and industry. This module is designed to familiarize you with a variety of methods and techniques used for forecasting economic and business data and their use in economic and business decision-making.
The module will consider, in turn, applications and merits of various smoothing methods, time series decomposition, univariate time series and structural modelling forecasting methods. Methods of forecast evaluation will also be examined. The module is hands-on and students will learn how to apply the various forecasting techniques using real data. The module will develop further IT skills associated with the use of Stata and other software packages.

Aim of this module is to familiarize students with a variety of techniques in economic and business forecasting and to undertake independent study leading to the production, interpretation and evaluation of forecasts.

Intended Learning Outcomes

work independently, deploying judgement in the appropriate choice of forecasting technique and data analysis: 1
critically appraise and evaluate economic and business forecasts: 1
communicate and explain for a variety of audiences the key features of various forecasting techniques and their associated predictions: 1
produce a forecast and draw inference in relation to economic and business decisions: 1
collate and constructively integrate quantitative and qualitative information about real world economic and business activities in a report: 1
analyse data and produce forecasts for economic and business data using a variety of time series techniques: 1

Study hours

16 hours lectures
8 hours supervised computer lab sessions
126 hours project-based independent study

School Rules

None

Description of Module Assessment