Data Analysis for Economists - ECON3140

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Autumn Term 4 15 (7.5) Luke Buchanan-Hodgman checkmark-circle


The module introduces students to fundamental key skills used by economists in the application of economics to real world issues. It develop students' use of information technology and their ability to access electronic and other secondary sources of data. In particular, the module promote students' computing and quantitative skills within a structured environment.
The module covers the following topics:

• Data collection and sampling, accessing and downloading electronic data
• Descriptive statistics, graphical and numerical techniques for summarising data
• Index numbers, Paasche and Laspeyres indices, chained and non-chained indices
• National income accounts, growth accounting, logarithm and exponent functions
• Investment decisions, discounting, NPV, internal rates of return


Contact hours

Total contact hours: 28 hours
Private study hours: 122
Total study hours: 150


This module is compulsory for all students studying single honours degrees in Economics and is optional for those students on joint Economics degree programmes.
This module is not available to students across other degree programmes in the University.

Method of assessment

Main Assessment Methods:

• Data Report 1 (2000 words) (25%)
• Data Report 2 (2000 words) (25%)
• Workshop Attendance (10%)
• Group Project (2500 words) (40%)

Indicative reading

Davis, G. and B. Pecar (2013), Business Statistics using Excel, 2nd Edition, OUP.

Etheridge, D. (2010), Excel Data Analysis: Your Visual Blueprint for Creating and Analyzing Data, Charts and Pivot Tables (3rd ed), John Wiley.

Barrow, M. (2013), Statistics for Economics, 6th Edition, Prentice Hall.

Whigham, D. (2007), Business Data Analysis using Excel, OUP.

See the library reading list for this module (Canterbury)

Learning outcomes

On successful completion of this module, you will be able to:
* search, identify and access secondary data sources.
* utilise spreadsheets, in particular, Microsoft Excel.
* utilise specialist data analysis and reporting tools e.g. Macrobond
* undertake graphical and numerical data analyses.
* apply data analysis techniques in the context of economic theory and policy.


  1. Credit level 4. Certificate level module usually taken in the first stage of an undergraduate degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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