Applied Economics for Business

Module description

The ability to perform and critically discuss applied empirical work is central to a business economists’ job in today’s workplace. The volume of economic and financial data is ever increasing, and so are the opportunities to use this data to undertake empirical economic and business research. The quantitative methods, and the software used to apply them, becoming more and more sophisticated, and this module aims to provide training in both the empirical methods and in the application of those methods using a modern statistics software package.

Additional Information:

Employability: In today’s electronic world, all businesses are collecting data and need employees who can critically analyse the vast amount of data to smartly drive business decisions. This module attempts to bridge the gap between economic theories learnt in other modules and the data-driven world beyond the classroom.

Full module specification

Module title:	Applied Economics for Business
Module code:	BEE3062
Module level:	3
Academic year:	2023/4
Module lecturers:	Dr Pradeep Kumar - Convenor
Module credit:	15
ECTS value:	7.5
Pre-requisites:	Either BEE1022 or BEE1025; and BEE2024
Co-requisites:	Please note this module cannot be taken by students who have previously studied BEE2025 and BEE2026.
Duration of module:	Duration (weeks) - term 1: 11

Module aims

The aim of this module is to equip you with good practical skills in applied business economics, especially in the application of quantitative research techniques to research questions from different areas of business economics. The module will
focus on data skills (organisation and manipulation of data, descriptive and explorative analysis), survey data and applied econometrics (regression models). You will learn to apply those techniques using one of the main statistics software package.

ILO: Module-specific skills

1. demonstrate ability to understand the important features and properties of real-world data, and perform the necessary operations to organise and manipulate the data
2. apply appropriate quantitative techniques based on the research question and features of the data
3. perform independent empirical analysis using a statistical software

ILO: Discipline-specific skills

4. combine knowledge of economic theory with the necessary quantitative and data skills to undertake applied empirical work in business economics

ILO: Personal and key skills

5. demonstrate analytical and critical thinking
6. demonstrate the ability to use statistical software

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching Activities	Guided independent study	Placement / study abroad
27	123	0

Details of learning activities and teaching methods

Category	Hours of study time	Description
Scheduled Learning and Teaching	22 hours	Lectures
Scheduled Learning and Teaching	5 hours	Tutorials

Formative assessment

Form of assessment	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Data analysis exercises	One term	1-6	Verbal
Preparatory exercises for practical exam	One term	1-6	Verbal

Summative assessment (% of credit)

Coursework	Written exams	Practical exams
30	0	70

Details of summative assessment

Form of assessment	% of credit	Size of the assessment (eg length / duration)	ILOs assessed	Feedback method
Practical Exam	70	Three hours	1-6	Written
Homework	30	1 problem set with 10-15 questions	1-6	Written and Verbal
	0
	0
	0
	0

Details of re-assessment (where required by referral or deferral)

Original form of assessment	Form of re-assessment	ILOs re-assessed	Timescale for re-assessment
Practical exam and homework	Take-home assignment (100%)	1-6	August Examination Period

Syllabus plan

Module aims and limitations
Introduction to Statistical Software (STATA)
First steps in empirical analysis: descriptive statistics and explorative analysis
Organising your work
Hypothesis Testing
Applied linear regression, diagnostics and tests
Prediction, Goodness-of-fit and Modelling issues
Non-linear regression models
Binary choice models
Working with surveys

Indicative learning resources - Basic reading

Basic reading:

Hill, R.C, Griffiths, W.E and Lim, G.C (2011) Principles of Econometrics, 4^th edition, John Wiley & Sons.

Adkins, L.C. and Hill, R.C. (2011) Using Stata for Principles of Econometrics, 4^th edition, John Wiley & Sons.

Module has an active ELE page?

Yes

Indicative learning resources - Web based and electronic resources

ELE.

Indicative learning resources - Other resources

A Gentle Introduction to Stata by Alan C. Acock

Data Analysis Using Stata by Ulrich Kohler and Frauke Kreuter

Cortinhas, C. and Black, K. (2012), Statistics for Business and Management, 1^st European Edition, Wiley

Data:

UK Data Service (http://ukdataservice.ac.uk/ )

http://www.nber.org/data/

Origin date

10/07/2015

Last revision date

08/09/2020