ECO-30051 - Module Specification
Keele Business School
Faculty of Humanities and Social Sciences

Programme/Approved Electives for 2024/25

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

ECO-20042

Barred Combinations

none

Description for 2024/25

The ability to analyse quantitative information and produce evidence-based policy analysis and evaluation is a highly prized skill in the public sector, business, industry and the financial world. This module is designed to familiarise you with a variety of methods and techniques used for handling and analysing economic, business and financial data and their use in economic and business decision-making.
Econometric techniques covered by the module include time series analysis, structural modelling of economic and business data, and panel data. 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.

The aim of this module is to teach students a variety of econometric and other methods in handling economic, financial and business data and to allow them to undertake independent study in which they demonstrate their familiarity with these methods, ability to produce an independent piece of substantial individual research, and ability to evaluate and interpret their results.

Intended Learning Outcomes

work independently, deploying judgement in the appropriate choice of econometric techniques and data analysis: 1
analyse economic, business and financial data using a variety of time series and panel-data techniques in an independent piece of substantial individual research: 1
critically appraise and evaluate results of quantitative research: 1
communicate and explain for a variety of audiences the key results and policy implications of their research: 1
collate and constructively integrate quantitative and qualitative information about real world economic and business activities in a report: 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